ChatGPT answers, unedited

If your goal is specifically content outlines that increase the chance of being quoted/cited by ChatGPT, Perplexity, Gemini, etc., I’d separate the problem into two parts:

1. Create a strong, semantically complete outline.
2. Measure whether AI systems actually mention/cite the resulting content.

Those are not quite the same job.

My shortlist

Frase would be the first one I'd test if the primary requirement is "give me an outline designed around the questions and information an AI answer engine needs." Current comparisons describe it as particularly strong at AI content briefs, question research, and SERP-driven outlines, and it now includes GEO-oriented scoring/visibility functionality. Stork.AI FlowHunt

Surfer is worth considering if you want more sophisticated SEO/content optimization around the outline. Its January 2026 update specifically says its generated outlines are now more natural, shorter, citation-ready, and informed by brand, AI, and SEO context. Surfer SEO

MarketMuse becomes more interesting if you're not just making individual articles but want to determine which topics and subtopics your entire site should cover. Its strength is content inventory, topic gaps, and topical-authority planning rather than AI-answer tracking. Honest AI Guide

One important distinction

I wouldn't assume that an "AI-optimized" outline automatically makes an article more likely to be quoted.

For LLM citation/quotation, I'd structure your briefs to explicitly require:

• Direct answers near the top of each section
• Clear, self-contained statements that can be quoted without surrounding context
• Specific facts, numbers, definitions, and comparisons
• Primary/authoritative sources attached to important claims
• Original data, examples, or analysis rather than generic summaries
• Explicit answers to related questions
• Consistent terminology/entities throughout the article
• Tables or structured lists where appropriate
• Clear author/company expertise and attribution
• Minimal filler around the actual answer

Then use an AI-visibility/citation tracker after publishing to see whether ChatGPT, Perplexity, Gemini, etc. actually retrieve and cite those pages. Content-brief software and AI-citation monitoring are increasingly separate products; swapping one SEO brief tool for another doesn't necessarily give you the latter. 1001 SEO Media AI Search Tool Rank

If you tell me what kind of content you're producing (B2B SaaS, affiliate, ecommerce, publisher, local, etc.) and roughly how many articles/month, I can narrow this to 2–3 tools and give you a concrete "LLM citation-ready outline" workflow.

MarketMuse becomes more interesting if you're not just making individual articles but want to determine which topics and subtopics your entire site should cover. Its strength is content inventory, topic gaps, and topical-authority planning rather than AI-answer tracking.

One important distinction

I wouldn't assume that an "AI-optimized" outline automatically makes an article more likely to be quoted.

For LLM citation/quotation, I'd structure your briefs to explicitly require:

If your goal is to create content outlines that conversational models (ChatGPT, Gemini, Claude, Perplexity, etc.) are more likely to quote or cite, you’re looking for tools in the emerging GEO (Generative Engine Optimization) / AEO (Answer Engine Optimization) category rather than just traditional SEO outline generators. GeoCopy Shadow

The best choice depends on your workflow:

Best overall content-outline tools

frase.io — Best for SEO + AI-friendly briefs

Good for:

• Building article outlines from search results
• Finding unanswered questions
• Creating FAQ sections
• Structuring content around user intent

Why it helps with AI quoting:

• Encourages direct answers, headings that mirror questions, and topical completeness.

Best for: content teams producing many articles.

surferseo.com — Best if you already do SEO

Good for:

• Content briefs
• SERP analysis
• NLP term coverage
• Competitor content comparisons

Why it helps:

• AI systems often retrieve content that is clear, comprehensive, and well-organized; Surfer helps with the underlying search visibility layer. TechRadar

Best for: SEO-led teams that want GEO improvements without changing their stack.

semrush.com — Best enterprise research stack

Good for:

• Topic research
• Competitor analysis
• Keyword clusters
• Brand/AI visibility monitoring

Best for: companies already using SEO analytics. Some newer Semrush offerings include AI visibility tracking features. TechRadar

More GEO-focused tools

tryprofound.com — Best for measuring AI citations

Useful for:

• Tracking how brands appear in AI answers
• Seeing competitor mentions
• Measuring AI search visibility

Best for: teams that already publish content and want to understand whether AI systems are referencing them. Geosoftwarerankings

airops.com — Best for scaled content operations

Useful for:

• Automated content workflows
• Research → outline → draft pipelines
• Team processes

Best for: agencies and large content teams. Geosoftwarerankings

hubspot.com — Best if your content is tied to CRM and marketing

Useful for:

• AI search visibility workflows
• Content planning
• Marketing attribution

Best for: companies already operating inside HubSpot. TechRadar

My recommended stack for "quoted by AI" outlines

A practical workflow:

1. Research demand

• Semrush / Ahrefs / Google Search Console
• Create the AI-citable outline

• Frase or Surfer
• Add GEO structure manually

• Put the direct answer near the top
• Use question-based H2s
• Add definitions, comparisons, tables, FAQs
• Include original data, expert quotes, and cited sources
• Measure whether models pick it up

• Profound or similar AI visibility trackers

The outline format I would optimize for is:

Title: [Specific question/topic]

TL;DR answer:
40–80 word direct answer that can stand alone.

Definition:
What is X?

Key facts:
- Fact + source
- Fact + source

How it works:
Step-by-step explanation.

Comparison:
X vs Y table.

Common questions:
FAQ format.

Expert perspective:
Named expert/source.

Conclusion:
Short summary.

No tool can guarantee that ChatGPT or another model will quote a page, because retrieval and citation behavior depends on the model, query, available sources, freshness, and authority signals. But tools that improve answer clarity, evidence density, structure, and measurement are the ones aligned with that goal. KJW Labs Modulyn

If you’re building hundreds of outlines per month, I’d lean toward AirOps + Semrush. For a solo marketer or small team, Frase + Semrush/Ahrefs is usually a simpler setup.

The outline format I would optimize for is:

If your goal is creating content outlines that increase the chance of being quoted/cited by conversational AI systems (ChatGPT, Gemini, Perplexity, Claude, AI Overviews, etc.), you’re looking for tools in the GEO (Generative Engine Optimization) / AEO (Answer Engine Optimization) category rather than traditional SEO brief tools. These tools usually focus on question targeting, entity coverage, citation patterns, and AI visibility tracking. GeoCopy SitePoint

Here are the strongest options by use case:

Best for AI-quotable content briefs

frase.io

Best for: Solo writers, content teams, SEO strategists

Why it fits:

• Builds research-driven outlines from SERP and competitor analysis
• Finds missing topics/entities competitors cover
• Encourages question-based sections and concise answers (useful for AI retrieval)
• Good bridge between classic SEO and GEO-style formatting

Use it when you want:

“Create an authoritative article outline that covers everything an AI answer engine might need.”

surferseo.com

Best for: Teams already doing SEO at scale

Useful features:

• Content editor and topical coverage analysis
• NLP/entity suggestions
• Competitive content gap analysis

It is more SEO-first than GEO-first, but strong outlines often translate into better AI retrieval because they improve topical completeness. MarqOps

Best for tracking whether AI models actually quote you

tryprofound.com

Best for: Enterprise teams

Strengths:

• Tracks AI visibility and citations
• Helps identify which sources AI systems reference
• Useful for reverse-engineering what kinds of pages get cited CrowdReply MarqOps

This is less of an outline generator and more of a “why are we or competitors being mentioned?” tool.

peec.ai

Best for: Monitoring AI mentions and citations

Useful if your workflow is:

1. Create content
2. Publish
3. Measure whether AI engines start referencing it

GitHub

Best all-in-one GEO workflow tools

writesonic.com

Best for: Teams wanting AI content creation + optimization

Combines:

• Content generation
• SEO optimization
• AI visibility features

Useful if you need a single platform rather than assembling several tools. CrowdReply

semrush.com

Best for: Existing marketing teams

Good fit if you already use it for:

• Keyword research
• Competitor analysis
• Content planning

Its AI visibility features extend a traditional SEO workflow into AI search monitoring. GitHub

My recommended stack for creating “AI-citable” outlines

For most content teams:

1. Research + outline creation

• Frase or Surfer
• AI citation intelligence

• Profound or Peec AI
• Final outline rules

• Start each section with a direct answer
• Use question-style H2s
• Include definitions, comparisons, tables, statistics, and named sources
• Add original data/examples where possible
• Make key claims easy to extract as standalone passages

A good AI-oriented outline usually looks less like a traditional blog outline:

Introduction → history → overview → conclusion

and more like:

What is X?
How does X work?
What are the main types of X?
X vs Y comparison table
Expert examples/data
Common mistakes
FAQ

That structure gives conversational systems more self-contained passages to quote.

If you tell me your niche (SaaS, ecommerce, finance, health, publishing, etc.) and whether you care more about ChatGPT citations, Google AI Overviews, or Perplexity, I can suggest a tighter stack.

Surfer is probably the best fit right now if your goal is specifically content outlines designed to increase the likelihood of being cited/quoted by conversational AI. Its 2026 workflow explicitly supports LLM-citation-oriented structures and has an “LLM Optimized Article” template. SurferSEO Surfer SEO Docs

• Best overall: surferseo.com — SERP/competitor research + AI-search scoring + citation-oriented outlines. Surfer SEO Docs SurferSEO
• Best workflow: generate the outline, then make each section answer one specific question with concise, self-contained claims, evidence, and definitions. That structure is more useful for LLM retrieval than simply stuffing keywords into an outline.
• Important caveat: no software can guarantee ChatGPT/Claude/Perplexity will quote you. Citation depends on authority, factual accuracy, crawlability, source selection, and the specific model/query.

If AI citation/GEO is the primary objective rather than Google SEO, I'd choose Surfer over a conventional SEO outline generator. Surfer SEO Docs

If your goal is specifically content outlines that increase the chance of being cited/quoted in ChatGPT, Perplexity, Gemini, Google AI Overviews, etc., I’d prioritize AI-search/GEO capabilities over traditional SEO outline generators.

My top picks

1. Surfer — best overall

This is the one I’d choose. Its Content Editor now has an AI Search Score, analyzes Facts Coverage and Upfront Intent Alignment, and its outline workflow is based on SERP/competitor research. It also explicitly provides AI-search guidance aimed at increasing AI citations. Surfer SEO Docs Surfer SEO Docs

Particularly interesting: Surfer now offers AI Search/AIO guidelines with source-attributed facts from AI engines including Google AI Overviews, AI Mode, Gemini, OpenAI and Perplexity. Its MCP integration can also generate an outline/brief directly inside AI assistants. Surfer SEO Docs

surferseo.com

2. Frase — best if you mainly want fast briefs

I'd consider Frase if you don't need Surfer's more developed AI-visibility layer. It's particularly good for taking a search query and turning SERP research into a writer-friendly outline/brief.

3. MarketMuse — best for sophisticated topical strategy

Better suited to a larger content operation where you care about topic coverage, authority, content gaps, and an entire site's information architecture, rather than simply generating an individual outline.

4. Semrush — best if you're already in the Semrush ecosystem

Useful if keyword research, competitor research and content planning already live in Semrush. I wouldn't buy Semrush solely for AI-citation-oriented outlines, though.

The important distinction

I'd actually change the brief you ask these tools to produce.

A conventional SEO outline looks roughly like:

H1 → H2 keyword → H2 keyword → H3 keyword → FAQ

For conversational-model visibility, you want an outline that makes the eventual article easy for an AI system to retrieve, verify, summarize and attribute.

For example, I'd want the brief to explicitly request:

• Answer the primary question immediately
• Give a concise, self-contained answer before elaboration
• Identify the important entities, definitions, claims and facts
• Include questions users actually ask conversationally
• Give each major question its own clearly labeled section
• Put important facts close to the claims they support
• Include original data, examples, comparisons or first-hand expertise
• Clearly distinguish facts from opinions/recommendations
• Identify claims that need authoritative citations
• Cover competing viewpoints and edge cases
• Avoid burying the actual answer beneath generic introductions
• Create sections that can be quoted independently without losing context

That lines up particularly well with Surfer's current AI-search methodology: its AI Search Score explicitly considers facts coverage and whether the content answers the user's primary question early. Surfer SEO Docs Surfer SEO Docs

What I'd use in practice

Surfer + an LLM is probably the strongest workflow.

I'd do:

Keyword/topic → Surfer SERP research → Surfer AI-search facts/questions → generate outline → manually add proprietary expertise/data → write → run AI-search/content optimization

Surfer even has a dedicated “create content brief” and “create outline” workflow through its MCP integration, so you can have an AI assistant work from the underlying Surfer data rather than asking an LLM to invent an outline from scratch. Surfer SEO Docs

One caveat: no software can guarantee that ChatGPT or another conversational model will cite you. Citation behavior depends on retrieval, authority, freshness, query formulation, and the particular model/search system. The software can optimize the retrievability and extractability of your content, not guarantee inclusion.

If you tell me your use case (e.g. SaaS, affiliate, local business, B2B, publisher, ecommerce), I can recommend the best stack and give you a GEO/AEO outline template specifically designed to maximize quotability by LLMs.

If your goal is content outlines that are more likely to be quoted/cited by conversational AI systems (ChatGPT, Claude, Gemini, Perplexity, AI Overviews), you’re looking for tools in the GEO (Generative Engine Optimization) / AEO (Answer Engine Optimization) category rather than traditional SEO outline generators. GeoCopy Humanswith.AI

Here are the strongest options by use case:

Best overall: AirOps

Best for: Content teams producing many AI-search-oriented articles.

Why it fits:

• Turns AI visibility gaps into content briefs
• Helps structure articles around questions, entities, citations, and answerable sections
• Connects research → outline → production workflows

Good choice if you have writers and want a repeatable process. HubSpot

Best for measuring what AI actually cites: Profound

Best for: Enterprises and brands that want to know why competitors get mentioned.

Useful features:

• Tracks prompts across AI engines
• Shows which sources are being cited
• Helps identify content gaps

It is more of a monitoring/intelligence tool than an outline generator, but it tells you what kind of content you need to create. xSeek HubSpot

Best budget-friendly workflow: Writesonic

Best for: Solo marketers and small teams.

Useful for:

• AI-oriented briefs
• FAQ-style content
• Answer-focused writing
• Generating structured drafts

It is less research-heavy than enterprise tools but faster for execution. Vismore

Best if you already use SEO tools: Semrush or Ahrefs

Best for: Teams that already have keyword/content workflows.

They help with:

• Finding topics
• Understanding competitors
• Identifying missing coverage

However, they are traditionally SEO-first, so you may still need a GEO-specific layer for citation optimization. HubSpot

Best AI-native outline approach (DIY): combine research + structure tools

A strong workflow is:

1. Use an AI visibility tool to find questions where competitors are cited.
2. Build an outline around: - A direct answer in the first paragraph
3. Clear H2 questions
4. Definitions
5. Statistics/data points
6. Expert quotes
7. Tables/comparisons
8. Original research
9. Explicit sources/citations

These patterns align with what GEO research and current AI-search tools emphasize: making content easy for models to extract, attribute, and summarize. Orem GeoCopy

My practical picks

• Solo creator / startup: Writesonic + ChatGPT
• SEO/content team: AirOps
• Enterprise marketing team: Profound + a content production platform
• Technical team that wants control: open-source options like E-GEO can be worth exploring. E-GEO GitHub

One caveat: no software can guarantee that a conversational model will quote your page. The tools can improve the odds by helping you create content that is clearer, more authoritative, and easier for AI systems to retrieve and attribute. Humanswith.AI

If you tell me your use case (blog, SaaS marketing, ecommerce, agency, personal brand, etc.), I can narrow this to the 2–3 tools that make the most sense.

If your specific goal is “create content outlines that increase the odds of being quoted/cited in ChatGPT, Perplexity, Gemini, etc.”, I would not choose a tool purely on traditional SEO content scoring.

The market is increasingly split into two layers: content/SEO optimization and AI-search visibility (GEO). Traditional tools analyze SERPs, semantic coverage, questions, and competitors, but that doesn't necessarily tell you what conversational models are actually citing. AI Search Tools Toolsolved

My picks

• Best for your exact use case: Frase — particularly good if the immediate job is research → questions → outline → brief. It can pull together SERP information and questions and turn that into a structured content brief. AI Search Tools Honest AI Guide
• Best for sophisticated content strategy: MarketMuse — better if you're building a whole topical cluster rather than a single article. Its strength is identifying topical gaps and relationships across your site. AI Search Tools
• Best for optimizing the finished article: Surfer — excellent for SERP-driven content optimization and real-time scoring, but I'd treat its score as a secondary signal rather than a proxy for AI citation likelihood. Timothe AI Toolsolved
• Best if AI visibility measurement is the priority: a dedicated GEO platform + one of the above — tools in this category can monitor which prompts produce your brand/content in AI answers and which competitors are being cited. That's fundamentally different from generating an SEO brief. AI Search Tools The AI Rankings

What I'd actually use

For a serious “get quoted by conversational AI” workflow, I'd do:

GEO/AI-visibility tool → Frase or MarketMuse → LLM → human editorial pass

The important change is in the brief itself. Instead of asking:

“What keywords should this article contain?”

you want the outline to identify:

• questions conversational models are likely to receive
• self-contained answers to those questions
• explicit definitions and entity relationships
• original data, examples, and first-party evidence
• claims that can be attributed to authoritative sources
• concise passages that can stand alone when extracted
• comparisons, lists, and decision criteria
• unanswered subtopics where competing pages are weak
• opportunities to establish your site as the primary source, rather than another summary of existing sources

That's because being highly optimized for Google does not guarantee being cited by an LLM; the overlap between Google's results and AI citations isn't perfect. AI Search Tools Toolsolved

If you're choosing one tool today, I'd start with Frase for outline generation, then add a dedicated AI-visibility/GEO tool once you're ready to measure whether those outlines actually translate into citations.

If you tell me what kind of content you're producing (B2B, SaaS, affiliate, news, medical, etc.) and your monthly budget, I can give you a much more specific 3-tool stack and workflow for generating “AI-citable” outlines.

If your goal is specifically “create outlines that make it easy for ChatGPT, Gemini, Perplexity, etc. to understand, extract, and quote my content,” I’d use a slightly different stack than traditional SEO.

My picks

• Best overall: surferseo.com — strongest all-around choice if you want SERP research + semantic coverage + content optimization, and it increasingly includes AI-search visibility features. Context Rankings Official A.I Ranking
• Best for generating the actual outline/brief: frase.io — particularly good at turning SERP/question research into structured briefs and outlines. Conbersa Honest AI Guide
• Best for large-scale topical strategy: marketmuse.com — useful when you're building an entire topic/entity ecosystem rather than optimizing individual articles. Honest AI Guide
• Best editorial-quality option: clearscope.io — excellent when you have writers/editors and care about rigorous semantic coverage, but I'd choose it less for outline generation specifically. Honest AI Guide

But there's an important distinction

No outline tool can guarantee that an AI model will quote you. AI citation/quotation depends on things beyond topical keywords: authoritative sourcing, factual specificity, clear answers, entity relationships, original information, and whether your page is actually discoverable/retrievable. Current comparisons explicitly caution against treating traditional content scores as direct measures of AI citation likelihood. Timothe AI Toolsolved

So I'd build your outlines around “extractability,” not merely SEO optimization.

For example, instead of:

H2: Benefits of CRM software

I'd want a brief that instructs the writer to produce:

H2: What are the main benefits of CRM software?
Open with a 40–60 word standalone answer.
Follow with 5 benefits, each with a concrete explanation and example.
Include a comparison table.
Cite primary/authoritative sources for quantitative claims.
Define “CRM” before using related entities.
Include a concise “Who benefits most?” subsection.

That structure gives an answer engine lots of self-contained passages it can confidently extract.

What I'd actually use

If you're a solo operator or small content team, I'd probably go:

Frase → ChatGPT/Claude → human fact-checking → AI visibility tracker

Frase creates the research-driven outline; the LLM expands it; you deliberately edit the resulting article for quotable, self-contained answers, original insights, evidence, and clear entity relationships.

If you're publishing at significant scale, I'd go:

Surfer + a dedicated AI-visibility/citation tracker.

That's because “content optimization” and “knowing whether AI systems actually cite you” are two different jobs. Some 2026 comparisons make this distinction explicitly: briefing tools optimize the content, while dedicated GEO/AI-visibility platforms monitor whether your pages actually appear in AI answers. 1001 SEO Media Toolsolved

If you tell me what kind of content you're creating (e.g. B2B SaaS, affiliate, local business, thought leadership, ecommerce), I can recommend the specific tool + outline template I'd use to maximize AI citations/quotability for that type of content.

If your goal is specifically “create outlines that increase the odds that ChatGPT, Gemini, Perplexity, Claude, etc. will quote/cite my content,” I’d prioritize tools that have moved beyond traditional SEO briefs into AI-search / answer-engine optimization.

My shortlist

1. frase.io — best fit for your exact goal

• Frase explicitly positions itself around getting cited by AI, not just ranking in Google. Frase
• Its research/brief workflow pulls questions from search, forums, and answer engines, identifies content gaps, and turns them into structured outlines with sources and sections. Frase
• I'd start here if AI citations/quotability are your primary KPI.
• marketmuse.com — best for deep topical coverage

• Excellent if you want outlines that establish topical authority rather than simply imitate the current SERP.
• Its briefs incorporate topic models, information gain, intent, expertise, factual statements, and differentiated coverage. MarketMuse MarketMuse
• Particularly useful for creating comprehensive, authoritative source material that an LLM can draw from.
• clearscope.io — good optimization layer

• Strong for ensuring an article is comprehensive and semantically relevant.
• Clearscope now explicitly discusses expanding brand authority across AI chatbots, alongside its traditional content optimization capabilities. Clearscope
• I'd use it more for optimizing a draft than as my first-choice AI-citation outline generator.

The important distinction

There's a difference between:

Traditional SEO outline

Keyword → headings → related keywords → target word count

and an AI-quotability outline

User question → direct answer → unique factual claim → evidence/source → context → definitions → comparison → concise quotable passage

For the latter, Frase is probably the closest off-the-shelf fit right now.

But I wouldn't rely on any tool's “AI visibility” score as proof that an article will actually be cited. LLM citation behavior is still highly variable. The underlying content matters enormously: clear answers, original information, authoritative sourcing, explicit entities, factual precision, and passages that can be extracted without losing their meaning.

What I'd actually use

If I were building an AI-search content operation:

Frase → generate/research the brief → manually impose an “LLM quotability” structure → write → test the finished page against ChatGPT/Perplexity/Gemini queries.

And I'd make the outline require things like:

• One-sentence answer immediately after each major question
• Definitions written as standalone statements
• Specific claims backed by primary sources
• Original data/examples where possible
• Tables for comparisons
• Explicit entity names rather than vague pronouns
• Short, self-contained paragraphs
• “According to X…” attribution where appropriate
• FAQ sections targeting conversational questions
• A clear distinction between facts, analysis, and opinion
• Unique insights that aren't simply paraphrases of competing pages

If you tell me what kind of content you're creating (e.g. B2B SaaS, medical, finance, ecommerce, thought leadership), I can also recommend the best tool + an exact outline template designed specifically for getting cited by conversational AI.

For the latter, Frase is probably the closest off-the-shelf fit right now.

But I wouldn't rely on any tool's “AI visibility” score as proof that an article will actually be cited. LLM citation behavior is still highly variable. The underlying content matters enormously: clear answers, original information, authoritative sourcing, explicit entities, factual precision, and passages that can be extracted without losing their meaning.

What I'd actually use

If I were building an AI-search content operation:

Frase → generate/research the brief → manually impose an “LLM quotability” structure → write → test the finished page against ChatGPT/Perplexity/Gemini queries.

And I'd make the outline require things like:

• One-sentence answer immediately after each major question
• Definitions written as standalone statements
• Specific claims backed by primary sources
• Original data/examples where possible
• Tables for comparisons
• Explicit entity names rather than vague pronouns
• Short, self-contained paragraphs
• “According to X…” attribution where appropriate
• FAQ sections targeting conversational questions
• A clear distinction between facts, analysis, and opinion
• Unique insights that aren't simply paraphrases of competing pages

If you tell me what kind of content you're creating (e.g. B2B SaaS, medical, finance, ecommerce, thought leadership), I can also recommend the best tool + an exact outline template designed specifically for getting cited by conversational AI.

If your goal is specifically “create content outlines that maximize the chance of being quoted/cited by ChatGPT, Perplexity, Gemini, and AI Overviews,” I’d choose differently than I would for traditional SEO.

My shortlist

*Not because ChatGPT gives you a magical “citation score,” but because you can explicitly research the questions, sources, competing answers, and information gaps that conversational models are likely to encounter.

For most people, I'd start with Frase. Recent comparisons specifically identify it as strong for research-to-publish workflows and GEO/AEO-oriented content, while Surfer is stronger when traditional SERP optimization is equally important. Timothe AI Stork.AI

But there's an important distinction

There isn't a reliable outline generator that can guarantee an article will be quoted by an AI model. AI systems choose sources based on relevance, authority, accessibility, freshness, and the particular query—not simply because an article received a high “GEO score.”

OpenAI, for example, says that public websites can appear in ChatGPT search and specifically recommends allowing OAI-SearchBot to access content if you want it to be discoverable and potentially surfaced/cited. OpenAI Help Center

So I'd optimize the outline itself for things like:

• Put a direct, quotable answer immediately beneath important H2/H3 questions.
• Make important claims self-contained, rather than burying the answer in five paragraphs of setup.
• Give each section a clearly defined question/answer pair.
• Include original data, statistics, definitions, comparisons, and expert conclusions that an AI can attribute.
• Identify the primary sources supporting each important claim.
• Cover related questions comprehensively without padding.
• Use descriptive headings that resemble the questions people actually ask conversational systems.
• Include explicit distinctions such as “X vs. Y,” “when to use X,” “limitations of X,” etc.

That fits the way ChatGPT's search experience works: it retrieves web information and provides citations to sources, so being discoverable and having clear, useful source material matters more than merely hitting a traditional SEO content score. OpenAI Help Center OpenAI

The workflow I'd actually use

ChatGPT Deep Research → Frase → human/editorial review

1. Deep Research: Find the actual questions people ask, authoritative sources, competing explanations, disagreements, statistics, and information gaps. ChatGPT's Deep Research is designed for multi-step web research and produces cited results. OpenAI OpenAI Help Center
2. Frase: Turn that research into a structured content brief and make sure you're still covering conventional search intent and semantic topics.
3. Writer: Produce concise, evidence-backed sections with explicit answers.
4. AI-visibility tracking: After publishing, use a dedicated AI-search visibility tool if you need to measure whether ChatGPT/Perplexity/Gemini are actually mentioning or citing you. Content optimization tools and AI-visibility monitoring are increasingly treated as two separate categories. xSeek

If you're building a serious GEO/AEO content operation, I would not buy Surfer/Clearscope/MarketMuse solely for “getting cited by AI.” Their traditional strengths are SERP optimization, editorial grading, and/or topical authority; dedicated AI-visibility platforms are better suited to measuring the downstream citation problem. Cakewalk The AI Rankings

If you tell me what kind of content you produce (B2B SaaS, affiliate, ecommerce, local, healthcare, etc.), I can give you a much more specific tool + workflow + outline template for maximizing AI citations.

OpenAI, for example, says that public websites can appear in ChatGPT search and specifically recommends allowing OAI-SearchBot to access content if you want it to be discoverable and potentially surfaced/cited.

So I'd optimize the outline itself for things like:

If your goal is specifically creating content outlines that increase the chance of being quoted/cited by ChatGPT, Gemini, Perplexity, and Google AI Overviews, I’d narrow the field considerably.

My picks

Recent comparisons consistently put Frase, Surfer, Clearscope and MarketMuse in the leading content-optimization group, but their strengths differ. Timothe AI Context Rankings

🥇 I'd start with Frase

frase.io

For your particular use case, Frase is probably the best fit because the workflow is close to:

query → SERP research → questions/topics → content brief → outline → draft → optimization

It also has GEO/AI-visibility functionality, making it more directly relevant than traditional SEO-only outline generators. Timothe AI Stork.AI

The important caveat: don't confuse an "AI-optimized" score with a demonstrated probability of being quoted by an LLM. No tool can reliably guarantee that.

🥈 Surfer if you want a more sophisticated stack

surferseo.com

I'd choose Surfer if you're building a serious content operation and want both:

• conventional SEO/SERP optimization
• topical/entity coverage
• content scoring
• AI-search visibility monitoring

Recent 2026 comparisons consistently rate it as the strongest general-purpose option, particularly for teams that want SEO and AI-search optimization together. Official A.I Ranking Context Rankings

The bigger point: optimize the outline, not just the article

If your objective is "I want conversational models to quote my site", I'd structure your briefs around things like:

• Explicit questions the page should answer
• One clear answer per section
• Concise, independently understandable passages
• Definitions and distinctions
• Original data, examples, research, or expert analysis
• Strong factual claims with attributable sources
• Tables/comparisons where appropriate
• Entity relationships and terminology
• Follow-up questions a user is likely to ask
• Clear "bottom line" answers before supporting detail

That's more important than simply stuffing an outline with keywords.

And Google's current guidance is unusually relevant here: it explicitly recommends unique, expert-led, people-first content and says not to rely on supposed AEO/GEO "hacks" such as artificial chunking or llms.txt. Google for Developers

What I'd actually use

If I were setting up your workflow today:

Frase → ChatGPT/Claude → AI-visibility tracker

Use Frase to generate the research-driven outline, then use an LLM to turn the outline into citation-worthy sections, and finally use something like Profound/Scrunch/AthenaHQ to see whether AI systems actually mention/cite your content. AI-visibility platforms and content-optimization platforms are increasingly becoming separate categories. xSeek

So, if you only want one subscription: Frase.

If you're doing this at scale for a company: Surfer + an AI-visibility monitoring platform.

If you tell me what type of content you're producing (B2B SaaS, affiliate, local SEO, ecommerce, thought leadership, etc.), I can recommend the exact tool + outline structure I'd use for maximizing LLM citations.

If your goal is to create content outlines that are more likely to be quoted/cited by conversational AI models (ChatGPT, Perplexity, Gemini, Claude, AI Overviews), you’re looking for GEO (Generative Engine Optimization) / AEO (Answer Engine Optimization) tools rather than traditional SEO outline tools. These tools focus on things like direct answers, entity coverage, citation-worthy structure, and identifying gaps in competing content. RankScope SitePoint

Here are the strongest options by use case:

Best overall for AI-citation-focused outlines

Frase

Best for: building AI-friendly content briefs and outlines

Why it works:

• Creates outlines from SERP/content research
• Finds missing topics and entities
• Encourages Q&A structures and direct-answer sections
• Good for turning a keyword into a comprehensive “answer document”

Best workflow:

1. Enter the target question/topic
2. Review competing pages
3. Extract entities, questions, and subtopics
4. Build sections around questions a model might answer directly

Good choice for: SEO teams, bloggers, content marketers.

Best for content teams optimizing for AI visibility

Surfer SEO

Best for: combining SEO optimization with AI visibility workflows

Strengths:

• Content scoring
• Topic/entity recommendations
• AI-oriented content analysis features
• Useful if you already produce lots of articles

It is more of a content optimization platform than a pure “AI citation outline generator.” RankScope

Best if you want to measure whether AI models actually cite you

Profound

Best for: enterprise AI visibility tracking

Useful for:

• Seeing whether ChatGPT-style answers mention your brand
• Tracking competitors
• Finding citation gaps

It is less about generating outlines and more about telling you what content opportunities exist. Elmo

Best for a GEO-first workflow

Writesonic

Best for: generating drafts structured around AI retrieval

Useful features:

• AI-oriented content generation
• Answer-first formatting
• Long-form content workflows

Good if you want “brief → draft” automation, though human editing is still important. RankScope

Best enterprise content operation stack

For a larger team, I would usually combine:

• Frase or Surfer → create outlines and optimize pages
• Profound / similar GEO tracker → monitor whether AI engines cite you
• Ahrefs or Semrush → maintain traditional SEO research

GEO tools generally split into two categories: tools that help you create citation-friendly content and tools that help you measure AI mentions/citations. The best workflows often use both. RankScope PageLens

My practical recommendation

• Solo creator / small site: Frase
• SEO/content marketing team: Surfer + Frase
• Brand trying to win AI recommendations: Profound + a content optimizer
• Agency producing lots of briefs: Frase or Writesonic with a GEO tracking layer

For the outline itself, the software matters less than the structure. A strong AI-quotable outline usually includes:

1. A one-paragraph direct answer near the top
2. Clear definitions (“What is X?”)
3. Comparison tables
4. Specific examples and numbers
5. Expert quotes or original research
6. FAQ sections matching conversational questions
7. Explicit entities (people, products, organizations, concepts)
8. Short, self-contained passages that an AI model can quote without extra context

If you tell me your niche (e.g., SaaS, health, finance, local business, affiliate content, news), I can suggest a more specific tool stack and outline template.

If your goal is to create content outlines that conversational AI systems (ChatGPT, Gemini, Claude, Perplexity, AI Overviews) are more likely to quote or cite, you’re looking for AEO (Answer Engine Optimization), GEO (Generative Engine Optimization), or AI search optimization tools rather than ordinary SEO outline generators. HubSpot TrueCite

Here are the strongest options depending on your workflow:

Best overall for AI-citable content outlines

airops.com

Best for: Content teams producing briefs → drafts → publishing workflows

Why it fits:

• Builds content briefs around AI-search opportunities
• Helps structure content into answerable sections
• Supports scalable editorial workflows
• Better suited for teams than solo bloggers

Good if you want: “Find gaps, create an outline, produce content, measure.”

HubSpot

Best for tracking what AI models actually cite

tryprofound.com

Best for: Enterprise teams wanting visibility into AI answers

Useful for:

• Seeing which prompts mention competitors
• Identifying citation gaps
• Turning those gaps into content opportunities

It is more of a measurement + strategy tool than an outline writer. HubSpot

Best for AI-first content briefs

usecontentor.com

Best for: Creating structured briefs

It focuses on:

• Entity coverage
• Question clusters
• Schema opportunities
• H2/H3 structures
• Internal linking plans

This is close to what you want if the deliverable is specifically an outline before writing. Contentor

Best lightweight option for content teams

rankprompt.com

Best for: Generating citation-oriented content formats

It emphasizes formats AI systems can parse well, such as:

• FAQs
• Comparisons
• Ranked lists
• Statistics roundups
• Glossaries
• Product deep-dives

Those formats map well to how conversational systems extract passages. Rank Prompt

Best if you want automated “find missing citations → create content”

ultrascout.ai

Best for: Brands trying to increase AI visibility

It combines:

• AI visibility monitoring
• Citation gap discovery
• AEO/GEO content generation

Useful when you already know the topics you want to win. UltraScout AI

My recommended stack by use case

HubSpot OremA good AI-quote-optimized outline usually has this structure regardless of tool:

1. Direct answer block (40–80 words)
2. Definition section (“What is X?”)
3. Key facts with numbers and sources
4. Comparison tables
5. Clear entity mentions (people, products, organizations, concepts)
6. FAQ sections matching conversational questions
7. Original examples, frameworks, or data
8. Short quotable statements that stand alone

If I were building a workflow today, I’d use Contentor for outlines + ChatGPT for drafting + an AI visibility tracker like Profound/Orem for feedback loops. Contentor HubSpot Orem

If your goal is specifically “create content that conversational AI systems are likely to quote/cite/reuse”—rather than just traditional Google SEO—I’d shortlist these:

1. surferseo.com — best overall choice

• Its Content Editor now has dedicated AI Search Guidelines designed around getting content picked up, cited, and reused by AI systems. Surfer SEO Surfer SEO Docs
• Its outline generator uses competitor/SERP research and produces citation-ready outlines. Surfer SEO
• It also has an AI Search Score, alongside conventional SEO/content scores. Surfer SEO Docs
• This is probably the closest match to exactly what you're asking for.
• marketmuse.com — best for deep topical authority

• MarketMuse builds unusually detailed content briefs: topics, questions, competitive gaps, SERP/user intent, claims, linking recommendations, and a detailed structure. MarketMuse
• It analyzes large numbers of pages rather than simply copying the structure of the top few Google results. MarketMuse
• I'd favor it if you're building a large authoritative knowledge base rather than publishing individual articles.

My recommendation

Start with Surfer. Its current feature set is unusually aligned with your use case: it explicitly distinguishes AI-search optimization from ordinary SEO and gives you an outline → writing → optimization workflow. Surfer SEO Surfer SEO Docs

But there's an important caveat: no software can reliably “optimize for being quoted by ChatGPT/Claude/Gemini.” The underlying models and retrieval systems vary, and citation behavior isn't simply a ranking factor you can directly optimize.

For that reason, I'd use a tool to generate the research-backed outline, then make the outline itself emphasize:

• Direct answers near the top of each section
• Specific, independently verifiable facts and claims
• Clear definitions of entities and concepts
• Original data, examples, comparisons, and expert perspectives
• Self-contained paragraphs that can be quoted without surrounding context
• Explicit answers to the questions users actually ask conversationally
• Strong source attribution for factual claims
• Tables/lists where they make comparisons unambiguous
• Internal links establishing topical relationships

In other words, you're optimizing for extractability + authority + factual clarity, not merely keyword density.

If you tell me what kind of content you're producing (B2B, SaaS, ecommerce, medical, finance, etc.), I can also give you a “LLM-citation-optimized outline template” that you can plug into Surfer or another tool.

If you tell me what kind of content you're producing (B2B, SaaS, ecommerce, medical, finance, etc.), I can also give you a “LLM-citation-optimized outline template” that you can plug into Surfer or another tool.

If your specific goal is creating content outlines that are more likely to be understood, extracted, and cited by ChatGPT/Claude/Perplexity/Gemini, I’d choose a tool somewhat differently than if your goal were traditional SEO.

My shortlist

Recent 2026 comparisons similarly put Surfer at the top for integrated SEO/AI optimization, while Frase is particularly strong for research and brief generation. Stork.AI Context Rankings

What I'd actually use

For a solo operator or small content team: Frase.

The reason isn't simply that it has "GEO" features. It's that your first problem is generating a good information architecture: questions, subtopics, entities, comparisons, definitions, and concise answers that an AI system can easily retrieve and synthesize. Frase is particularly oriented around SERP research, questions, and outline/brief generation. Honest AI Guide

For a larger SEO/content operation: Surfer.

Surfer makes more sense if you want the outline to flow directly into an optimization workflow and you also want visibility into how your content performs across AI search surfaces. Recent 2026 evaluations report AI tracking across platforms including ChatGPT, Perplexity, Gemini, and Google AI Overviews. Context Rankings Context Rankings

But there's an important distinction

I'd not optimize an outline simply for "AI citation."

There isn't a magic outline format that makes conversational models quote you. The stronger strategy is to make your content exceptionally easy for an answer engine to extract as a self-contained source.

For example, instead of:

I'd structure it more like:

Short answer: Project management software helps teams centralize tasks, deadlines, files, and communication, reducing coordination overhead and making project status easier to monitor.

When is project management software worth it?

How much does project management software cost?

What are the limitations?

That structure gives an AI system lots of clean question → answer → supporting detail units to work with.

The stack I'd recommend

If you're serious about this, I'd use:

Frase/Surfer → outline → human research → original data/examples → expert editing → AI-visibility tracking

rather than expecting one SaaS product to generate a magically "AI-optimized" article.

And I'd measure actual citations/mentions in ChatGPT, Perplexity, Gemini, and Google AI Overviews separately from traditional Google rankings. Some content-brief tools now advertise AI visibility, but the underlying jobs of creating the content and measuring whether AI systems actually cite it are still distinct. 1001 SEO Media

If you tell me what kind of content you're producing (B2B SaaS, affiliate, local SEO, ecommerce, thought leadership, etc.), I can give you a specific outline-generation workflow and prompt designed around getting cited by conversational search engines, including the exact headings/answer blocks I'd put in each article.

If by “optimized for being quoted by conversational models” you mean GEO/AEO — creating pages that ChatGPT, Perplexity, Gemini, Claude, etc. are more likely to understand, extract facts from, and cite, I’d choose a tool somewhat differently than for traditional SEO.

My picks

1. surferseo.com — best overall for this specific use case

• Its Content Editor now explicitly includes an “AI Search Score” alongside SEO/content scores. Surfer SEO Docs Surfer SEO Docs
• Its 2026 “Smarter Outlines” update specifically describes the generated outlines as “citation-ready”, using brand, AI and SEO context. Surfer SEO
• It can generate outlines containing headings and questions, while letting you supply source URLs and custom instructions. Surfer SEO Docs
• I'd start here if your goal is specifically AI-search visibility + conventional search.
• marketmuse.com — best for deep topical research

• MarketMuse is stronger when you want the outline to be based on topic coverage, questions, competitive gaps, claims, intent, and related concepts, rather than just keywords.
• Its briefs include questions to answer, detailed outlines, quality/claims analysis, topic models and linking recommendations. MarketMuse
• It also supports specific brief structures such as FAQ, comparison, how-to, guide, product review, etc. MarketMuse MarketMuse
• I'd choose this for authoritative, research-heavy content where factual completeness matters.

The important caveat

No software can reliably make an article “quote-worthy” to LLMs just by optimizing an outline. Models' retrieval and citation behavior changes, and recent evidence shows that even sources previously cited heavily can experience large fluctuations. Business Insider

For LLM citation/quotation optimization, I would make your outline enforce a structure like:

• Direct answer first — answer the target question in 1–3 sentences.
• Explicit claims — make important facts independently understandable.
• Question → answer sections — mirror the questions people actually ask conversational models.
• Original evidence — statistics, experiments, proprietary data, expert quotes, primary sources.
• Definitions — clearly define entities, products, concepts and terminology.
• Specificity — names, dates, numbers, conditions and qualifications rather than vague prose.
• Claim/source pairing — make it obvious which source supports which factual assertion.
• Unique information — don't merely synthesize the same ten pages an LLM has already seen.
• Self-contained passages — individual paragraphs should make sense when extracted without their surrounding context.

What I'd actually use

Surfer + a custom GEO outline template would be my first choice.

I'd use Surfer to identify the search/topic landscape, then have your outline-generation process add a layer that traditional SEO tools generally don't handle well: “What exact passage could an AI answer engine quote from this page?”

For example, instead of an outline saying:

H2: Benefits of enterprise knowledge management

I'd want:

H2: What are the benefits of enterprise knowledge management?

• Give a 40–60 word direct answer.
• State the 3–5 primary benefits explicitly.
• Quantify benefits where credible evidence exists.
• Cite primary research for each quantitative claim.
• Include a concise “when this does not help” qualification.

That's much closer to designing content for retrieval + extraction + citation, rather than merely designing it to rank.

If you tell me what kind of content/site you're producing (B2B, SaaS, ecommerce, publisher, professional services, etc.), I can also recommend the best GEO content-outline stack and give you a reusable outline template specifically designed to maximize the probability of being cited by ChatGPT/Perplexity/Gemini.

If your specific goal is “create content outlines that make the eventual article more likely to be quoted/cited by ChatGPT, Perplexity, Gemini, etc.”, I’d separate traditional SEO outlining from AI-search/AEO optimization.

My picks

I'd start with Frase. Current comparisons consistently position it around research → brief → outline, and it specifically incorporates questions, SERP analysis, and content optimization. Timothe AI Honest AI Guide

But there's an important catch: none of the traditional content-outline tools can reliably “optimize for being quoted by ChatGPT.” They mostly infer what makes content competitive from search results. AI-answer visibility is a separate layer. xSeek 1001 SEO Media

What I would actually use

For an AEO/GEO workflow, I'd do:

Frase or MarketMuse → ChatGPT/Claude → AI-visibility tracker

The outline should be designed around things conversational models can easily extract:

• Put a direct answer immediately after each important H2/H3.
• Turn major questions into explicit headings.
• Give self-contained factual statements, rather than making the reader infer the answer.
• Include definitions, comparisons, numbers, examples, and caveats.
• Use tables/lists where they make information easier to retrieve.
• Establish clear entities and relationships between them.
• Add original data, expert observations, or genuinely differentiated information.
• Cite authoritative sources for factual claims.
• Avoid filler designed solely to hit a word count.

That's consistent with Google's current guidance too: its advice for AI search emphasizes unique, satisfying content that provides value beyond commodity information, rather than a special “AI Overview” markup trick. Google for Developers Google for Developers

If you're building a serious AEO content operation

I'd actually consider two different software categories:

1. Content intelligence: Frase / MarketMuse / Surfer
→ “What should this article contain?”

2. AI visibility: platforms such as AthenaHQ, Scrunch, xSeek, etc.
→ “When people ask AI systems about this topic, does our content actually get cited?”

That distinction is becoming important because AI-search platforms measure actual prompt-level visibility rather than simply assuming that good Google SEO will translate into AI citations. xSeek

My recommendation: if you just want one tool today, Frase. If you're running a larger content program, MarketMuse + an AI-visibility platform is the more sophisticated setup.

If you tell me what type of content you're creating (B2B SaaS, affiliate, local SEO, thought leadership, ecommerce, etc.) and your monthly content volume, I can narrow this down to the best 2–3 tools and workflow for you.

If your goal is specifically “create content that conversational AI systems are likely to quote/cite when answering users”, I would not choose a tool based purely on traditional SEO content scoring.

The emerging discipline is usually called GEO (Generative Engine Optimization) or AEO (Answer Engine Optimization). The important distinction is that ranking on Google and being selected as a source by ChatGPT, Gemini, Perplexity, etc. overlap, but aren't identical. Cakewalk Astro SEO Blog

My shortlist

Frase is probably the one I'd try first. Its core workflow is unusually close to what you're asking for: SERP research → questions/topics → content brief → outline. Current comparisons specifically identify its brief generation as a strength, including SERP analysis, header structure, and questions. Honest AI Guide

frase.io

MarketMuse is the stronger choice if you're building a large knowledge base and want outlines based on topic gaps, semantic relationships, and topical authority, rather than simply reverse-engineering the current SERP. Cakewalk

marketmuse.com

Surfer is excellent if you want a highly practical SERP-driven workflow. It can generate outlines and gives real-time optimization feedback, but its center of gravity remains conventional search optimization. Clearscope

surferseo.com

But there's an important catch

If being quoted by conversational models is the primary objective, I wouldn't simply generate a normal SEO outline and call it GEO.

I'd want the outline to deliberately produce citation-friendly information units, such as:

• A direct answer immediately after each H2/H3.
• Explicit definitions rather than requiring the model to infer them.
• Concise factual claims that can be independently attributed.
• Specific numbers, dates, thresholds, examples, and comparisons.
• Original data or first-party expertise.
• Clear “who/what/when/why” context around claims.
• FAQ-style questions matching natural conversational queries.
• Strong entity relationships and terminology consistency.
• Sources immediately adjacent to important factual claims.
• Tables where a comparison is easier to extract than prose.
• Minimal fluff surrounding the actual answer.

That's because the objective isn't merely “make Google like this article.” It's closer to “make this page an unusually convenient, authoritative source from which an answer engine can construct an answer.”

And the tooling is still catching up: current comparisons note that traditional platforms such as MarketMuse, Surfer and Clearscope don't directly measure or optimize ChatGPT/Perplexity/Gemini citations in the same way dedicated AEO platforms attempt to. Cakewalk

There is also a rapidly developing market specifically around AI-search visibility; for example, current industry coverage describes platforms analyzing which creator/content sources actually appear in LLM-generated recommendations. The Wall Street Journal

What I'd actually use

For a serious workflow, I'd use:

Frase/MarketMuse → ChatGPT or Claude → GEO/AEO visibility tracker → human editorial review

The outlining tool gives you the research and topical structure. An LLM can then turn that into an outline specifically designed around answer extraction. Finally, an AI-visibility tool can tell you whether the finished content is actually being surfaced.

If you tell me what type of content you're creating (e.g. B2B SaaS, local business, affiliate content, medical, finance, ecommerce, thought leadership), I can give you a specific software stack + an outline template designed to maximize the probability of being cited by ChatGPT/Perplexity/Gemini.

If your goal is creating content outlines that are more likely to be quoted or cited by conversational AI models (ChatGPT, Gemini, Claude, Perplexity, AI Overviews), you’re looking for tools in the emerging GEO (Generative Engine Optimization) / AEO (Answer Engine Optimization) space. These tools differ from classic SEO outline generators because they focus more on retrievability, entity clarity, citations, and answer-friendly structure. SitePoint Tracemetry

Here are the strongest options depending on your workflow:

My recommended stacks

For a solo creator or small content team

• Frase → generate outline
• ChatGPT → rewrite outline into “answer-first” structure
• Surfer/Clearscope → check topical coverage

For a company trying to get cited in AI answers

• Profound or AthenaHQ → identify missing citations/visibility gaps
• Frase or Clearscope → build the content
• Analytics + citation tracking → measure improvement

For maximum AI quote-ability, prioritize tools/features that help you create:

• Clear definitions near the top (“X is…”)
• Short answer blocks (40–80 words)
• FAQ sections
• Tables comparing entities
• Explicit authorship and expertise signals
• Original data, statistics, frameworks, or examples
• Strong entity relationships (people, products, organizations, concepts)

A useful outline template for AI citation tends to look like:

1. Direct answer summary
2. Definition of the concept
3. Key facts/data points
4. Step-by-step explanation
5. Comparison table
6. Expert insights or original analysis
7. FAQs written as natural questions
8. Sources/references

No tool can guarantee that an AI model will quote your content, but these structures increase the chance that your information is easy for retrieval systems to identify and reuse. SitePoint

If you tell me your niche (e.g., SaaS, ecommerce, finance, healthcare, local business, personal brand), I can suggest a more specific tool stack and outline format.

If your goal is creating content outlines that are more likely to be quoted, cited, or summarized by conversational AI models (ChatGPT, Gemini, Claude, Perplexity, etc.), you’re looking for a mix of GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), and traditional content-brief software. The best choice depends on whether you need outlines only or a full optimization workflow. RankScope SitePoint

Best tools for AI-quotable content outlines

1. Frase — best for practical content briefs

Best for: SEO writers, content teams, blogs, explainers

Why it works:

• Builds SERP-informed outlines
• Extracts common questions and topics
• Helps structure content around direct answers
• Good for creating sections that AI systems can easily parse

Use it when you want:

• “What should this article cover?”
• “What questions should we answer?”
• “What entities and subtopics should appear?”

RankScope

2. Surfer SEO — best if you already do SEO

Best for: Teams optimizing existing content

Useful features:

• Content scoring
• Topic/entity suggestions
• AI visibility features
• SERP competitor analysis

For conversational-model quoting, I would use Surfer less as a writing tool and more as a coverage checker: make sure your article includes the concepts, terminology, and factual structure models expect. RankScope

3. Clearscope — best for editorial quality

Best for: High-quality publishing teams

Strengths:

• Strong topical coverage recommendations
• Helps avoid thin content
• Encourages authoritative structure

A good workflow:

1. Draft outline in Clearscope
2. Add “quotable blocks”: - definitions
3. numbered frameworks
4. original data
5. concise summaries
6. expert statements

4. Profound — best for measuring whether AI models actually cite you

Best for: Brands where AI visibility matters commercially

Unlike normal SEO tools, GEO platforms focus on:

• whether AI answers mention you
• which sources get cited
• which prompts trigger competitor mentions

It is more of a measurement + optimization platform than an outline generator, but it helps you reverse-engineer what content earns citations. Geosoftware Rankings SitePoint

5. Writesonic — best all-in-one AI content workflow

Best for: Small teams wanting one platform

Useful for:

• outlines
• drafts
• SEO optimization
• AI-search-oriented workflows

CrowdReply

My recommended stack

Solo creator / small site

• Frase → generate the outline
• ChatGPT → turn outline into an “AI-citable” structure
• Ahrefs or Semrush → validate demand

Content marketing team

• Clearscope or Surfer → content standards
• Profound or another GEO tracker → measure AI mentions
• Human editors → add expertise and original insights

Enterprise brand

• Profound + enterprise SEO platform
• Build a feedback loop: 1. Track prompts where competitors appear
• Analyze cited sources
• Create content briefs to fill gaps
• Measure citation improvement

What an AI-quotable outline should contain

Regardless of software, your outline should encourage:

1. A direct answer near the top

• “X is…”
• “The three main factors are…”
• Clear headings phrased as questions

• “What is X?”
• “How does X work?”
• “What are the benefits of X?”
• Definition blocks

• Short, standalone paragraphs models can quote
• Structured information

• tables
• numbered steps
• comparisons
• checklists
• Original evidence

• research
• proprietary data
• expert commentary
• Entity clarity

• clearly name products, people, organizations, concepts

No tool guarantees that a model will quote your content, but tools that combine content structure with AI visibility feedback are currently the closest approach. SitePoint

If I were choosing one specifically for generating outlines optimized for conversational AI citation, I’d start with Frase for briefs + a GEO tracker like Profound for feedback. RankScope Geosoftware Rankings

If your goal is specifically content outlines designed to increase the chance that ChatGPT, Perplexity, Gemini, and Google AI Overviews will extract/quote your content, I’d separate the tools into two categories: outline/brief generation and AI-visibility measurement.

Google’s own guidance is important here: there isn’t a special “AI citation” markup or magic outline format. Google says AI features still rely heavily on normal Search systems, while emphasizing original, non-commodity, useful content. Google for Developers Google for Developers

My picks

1. Frase — my first choice

frase.io

For your specific use case, Frase is probably where I'd start. It generates SERP-informed content briefs, questions, headings and topical coverage, and its newer workflow includes GEO/AI-visibility functionality. Recent comparisons specifically identify it as strong for the brief → draft → GEO workflow. FlowHunt Stork.AI

The important distinction is that you don't merely want an outline like:

H2: Benefits of X
H2: How X works
H2: Alternatives

You want an outline that tells the writer to create self-contained, quotable information units, e.g.:

H2: What is X?

• Answer in 40–60 words
• Define X without introductory fluff
• Include the distinguishing characteristic
• Cite the primary source

H2: How does X compare with Y?

• Give the conclusion first
• Follow with a 3–5 row comparison table
• State the conditions under which X is preferable
• Include quantitative evidence

That's much closer to what I'd optimize for.

2. Surfer — best if you're also serious about Google

surferseo.com

Surfer is stronger when you want SERP analysis + content optimization + outlines + traditional SEO in one workflow. Current comparisons consistently put it among the strongest all-around content optimization platforms. GTM Help The AI Rankings

I'd choose Surfer over Frase if your primary KPI is still organic traffic, with AI citations as a secondary objective.

3. Semrush — best for an existing SEO operation

semrush.com

If you're already using Semrush, its AI visibility capabilities make it attractive because you can move beyond:

"Did we create a good outline?"

to:

"Are AI systems actually mentioning/citing us?"

That's a much more useful feedback loop. Current 2026 comparisons identify Semrush's AI Visibility Toolkit as one of the more accessible ways to monitor mentions across ChatGPT, Gemini, Google AI and Perplexity. The AI Rankings xSeek

The bigger point: don't optimize the outline for "AI" alone

I'd actually build your workflow around citation-worthiness, rather than trying to reverse-engineer a particular LLM.

Google explicitly says that original information, first-hand experience, expert knowledge, research, and content that adds something beyond existing sources can improve its usefulness in generative search. Google for Developers Google for Developers

So your ideal outline generator should produce sections with:

• Answer-first paragraphs — the conclusion appears immediately.
• Atomic facts — one claim per paragraph rather than burying facts in prose.
• Explicit questions as headings — “What is X?”, “How much does X cost?”, “When should you use X?”
• Original data — statistics, experiments, surveys, benchmarks, proprietary observations.
• Named sources — preferably primary sources.
• Expert quotes and attribution.
• Comparisons and tables where appropriate.
• Clear definitions that can be lifted without surrounding context.
• Specific claims rather than generic SEO prose.
• Strong internal topical relationships so the page comprehensively covers the subject.

This aligns particularly well with Google's current emphasis on original, valuable content rather than simply rephrasing what already exists. Google for Developers

What I'd actually use

If I were building this workflow today:

Frase → generate research-backed outline → human adds proprietary insights/data → write answer-first sections → Semrush/AI-visibility tool → monitor which passages/claims actually get cited → feed results back into the next briefs.

That is considerably better than simply asking ChatGPT to “make an AI-optimized outline.”

And one important caveat: no current tool can guarantee that conversational models will quote your page. AI systems can choose different sources and responses from query to query, and Google explicitly notes that AI Overviews/AI Mode can use different models and techniques. Google for Developers

If you tell me what kind of content you publish (e.g. SaaS, ecommerce, finance, medical, B2B) and whether you're optimizing primarily for ChatGPT/Perplexity or Google AI Overviews, I can recommend the exact tool + outline template I'd use for that niche.

H2: What is X?

• Answer in 40–60 words
• Define X without introductory fluff
• Include the distinguishing characteristic
• Cite the primary source

H2: How does X compare with Y?

• Give the conclusion first
• Follow with a 3–5 row comparison table
• State the conditions under which X is preferable
• Include quantitative evidence

That's much closer to what I'd optimize for.

2. Surfer — best if you're also serious about Google

surferseo.com

Surfer is stronger when you want SERP analysis + content optimization + outlines + traditional SEO in one workflow. Current comparisons consistently put it among the strongest all-around content optimization platforms. GTM Help The AI Rankings

I'd choose Surfer over Frase if your primary KPI is still organic traffic, with AI citations as a secondary objective.

3. Semrush — best for an existing SEO operation

semrush.com

If you're already using Semrush, its AI visibility capabilities make it attractive because you can move beyond:

"Did we create a good outline?"

to:

"Are AI systems actually mentioning/citing us?"

That's a much more useful feedback loop. Current 2026 comparisons identify Semrush's AI Visibility Toolkit as one of the more accessible ways to monitor mentions across ChatGPT, Gemini, Google AI and Perplexity.

The bigger point: don't optimize the outline for "AI" alone

I'd actually build your workflow around citation-worthiness, rather than trying to reverse-engineer a particular LLM.

If your goal is creating content outlines that conversational models (ChatGPT, Claude, Gemini, Perplexity, etc.) are more likely to quote or cite, you’re looking for a mix of AI visibility / AEO (Answer Engine Optimization) tools and content brief generators. No tool can guarantee quotation, but the best ones help you structure content around the signals AI systems tend to reward: clear answers, authoritative sourcing, entity coverage, question matching, and extractable sections. G2 Data for AI Search

Best tools by use case

Best overall for AI-quotable content briefs: Frase

Best for:

• Turning a topic into an answer-focused outline
• Finding questions people ask
• Building sections that directly answer queries
• Adding missing concepts/entities

Why it fits:

• It was built around content briefs and optimization rather than just keyword tracking.
• Good choice if you are producing articles at scale and want a repeatable outline process. G2 Novelty SEO

Best for tracking whether AI models actually mention you: Profound

Best for:

• Monitoring ChatGPT/AI search visibility
• Seeing which prompts produce citations
• Finding competitor gaps

Why it fits:

• It focuses on measuring presence inside AI-generated answers rather than traditional rankings. G2

Best enterprise workflow: AirOps

Best for:

• Large content teams
• Combining research, optimization, and production workflows
• Scaling AI-search-oriented content programs

Why it fits:

• It connects AI visibility insights with content workflows instead of only reporting metrics. AirOps

Best if you already use SEO suites

Consider:

• Semrush — useful if you already manage keyword research, competitors, and content workflows.
• Ahrefs — strong for research, authority signals, and content gap analysis.

These are more SEO-first than AI-citation-first, but they help create source-worthy content foundations. Trustable Resources

A practical stack I’d use

For a solo creator or small marketing team:

1. Research + outline

• Frase
• Ahrefs or Semrush for topic/entity research
• Draft structure

• Create sections like: - “What is X?”
• “How does X work?”
• “X vs Y”
• “Common mistakes”
• “Expert recommendations”
• Put concise answers near the top of each section.
• AI visibility feedback

• Profound (if budget allows)
• Track the prompts your audience actually asks AI assistants.

Features to prioritize when choosing a tool

Look for:

• Prompt tracking across ChatGPT, Gemini, Claude, Perplexity
• Citation/source analysis
• Entity and concept recommendations
• Question mining
• Content gap detection
• Ability to produce structured briefs, not just AI-written drafts

The biggest mistake is using a tool that only generates a generic SEO outline. AI systems tend to quote content that is specific, well-structured, independently supported, and easy to extract. Data for AI Search

If you tell me your niche (e.g., SaaS, ecommerce, local business, publishing, personal brand), I can narrow this to the best 2–3 tools and workflow.

If your goal is specifically “create content outlines that conversational models are likely to quote/cite”, I’d separate the market into two jobs: brief generation and AI-visibility/citation measurement. A lot of “AI SEO” software is good at the former but doesn’t actually tell you whether ChatGPT, Perplexity, Gemini, etc. are citing the resulting content. xSeek Sightivo

My picks

• Frase — best fit for your exact use case. It combines research/brief generation with content optimization and, importantly, GEO-oriented scoring. It’s probably where I’d start if you want an outline → draft → optimize workflow rather than merely monitoring citations. Timothe AI The AI Rankings
• Surfer — best if Google SEO still matters heavily. Strong for SERP-derived briefs, topical coverage and content scoring; newer versions also incorporate AI-visibility tracking. TechRadar Official AI Rankings
• Semrush — best all-around marketing stack. Its AI Visibility Toolkit tracks visibility across ChatGPT, Gemini, Google AI and Perplexity while retaining traditional SEO research. Good if you don't want a separate SEO + GEO stack. Semrush
• Profound — best for measuring whether you're actually getting cited. I'd pair it with a content-brief tool rather than use it as the primary outlining application. It's aimed more at enterprise AI-search intelligence than content outlining. Semrush Cognizo
• Otterly.AI — good lower-cost monitoring option. Particularly useful for tracking a defined set of prompts and seeing which sources appear in AI answers. Semrush

What I'd actually use

For a serious “get quoted by conversational AI” workflow, I'd use:

Frase → publish → Otterly/Semrush → analyze citations → revise the content brief → republish.

The outline itself should emphasize things that make individual passages easy for an AI system to extract:

• Direct answers immediately below question-style headings
• Explicit definitions and concise explanations
• Original statistics/data, with sources
• Specific claims rather than generic SEO prose
• Expert attribution and quotable statements
• Tables/comparisons where appropriate
• Clear entity names and relationships
• FAQs corresponding to the actual questions people ask AI
• Strong internal/external sourcing

That matters because being “optimized for AI” isn't simply stuffing keywords into an article. The objective is to produce discrete, authoritative passages that answer a question well enough for an answer engine to retrieve and attribute them. GeoCopy xSeek

One caveat: no software can guarantee that ChatGPT will quote you. AI citation behavior is volatile and differs by engine; recent data, for example, shows substantial changes in which domains ChatGPT cites over relatively short periods. axios.com

If I had to pick just one for your stated requirement: Frase. If you tell me whether you're creating B2B/SaaS articles, affiliate content, thought leadership, ecommerce content, or something else, I can narrow this down to the best 2–3 tools and the exact outline format I'd use.

If your specific goal is “create content outlines that increase the odds of being cited/quoted by ChatGPT, Perplexity, Gemini, Google AI Overviews, etc.”, I’d separate the problem into outline generation and AI-search visibility measurement. No single traditional SEO outline tool completely solves both. xSeek Cakewalk

My picks

• Best overall: Frase — probably the best starting point if your immediate need is research → questions → headings → writer-ready brief. Its strength is brief/outline generation, and it’s considerably cheaper than premium enterprise tools. Honest AI Guide GTM Help
• Best for sophisticated content strategy: MarketMuse — better if you're building a large topical ecosystem rather than producing isolated articles. It can identify topical gaps and help structure content around broader authority. Honest AI Guide
• Best for optimization after the outline: Surfer — excellent for SERP-driven structure and semantic coverage, particularly if you want the writer to optimize the finished article against competing pages. Honest AI Guide
• Best premium editorial option: Clearscope — useful when you have professional writers/editors and care heavily about semantic coverage and editorial quality. GTM Help
• Best specifically for AI-search visibility: add a GEO/AEO visibility platform — tools such as Profound, Scrunch, AthenaHQ, or Semrush's AI Visibility capabilities are aimed at measuring whether AI systems actually mention/cite you, rather than merely assuming traditional SEO optimization will translate into AI citations. xSeek The AI Rankings

The important distinction

I wouldn't optimize an outline simply for “AI quotation.” I'd design it around characteristics that make individual claims easy for an answer engine to retrieve and cite:

1. Answer the primary question immediately.
2. Give each important sub-question its own section.
3. Put one clear claim/answer near the beginning of each section.
4. Support important claims with specific evidence, statistics, dates, methodology, or primary sources.
5. Use descriptive H2/H3s that resemble the questions people actually ask.
6. Include original data, expert observations, comparisons, definitions, and concrete examples—not just generic summaries.
7. Make important passages self-contained so an AI can quote them without needing three paragraphs of surrounding context.
8. Cover related questions comprehensively, but avoid padding.
9. Keep facts and claims attributable to identifiable sources.

That's because traditional SEO tools mostly reverse-engineer ranking pages, whereas AI-answer systems have somewhat different citation behavior. Cakewalk

What I'd actually use

For a small/medium content operation, I'd use:

Frase → ChatGPT/Claude → human editing → AI-visibility tracker

Frase creates the research-driven outline; the LLM turns that into a draft; the editor adds genuine expertise/evidence; then the visibility tool tells you whether the resulting content is actually appearing in AI answers.

If you tell me what type of content you're producing (B2B SaaS, affiliate, local SEO, thought leadership, ecommerce, etc.) and roughly how many articles/month, I can recommend a specific stack and workflow—including which tool I'd pay for and which ones I'd skip.

If your goal is specifically “create content outlines that increase the odds of being quoted/cited by ChatGPT, Perplexity, Gemini, Claude, etc.”, I’d use a GEO/AEO-oriented workflow rather than a conventional SEO outline generator.

My picks

I'd start with Surfer

Surfer's current Content Editor explicitly combines outline generation, competitor analysis, entities/facts, and AI-search optimization. Its newer workflow includes an AI Search Score, and its “Coverage Booster” is designed to add missing facts that can improve LLM citations. docs.surferseo.comgenerative.qadocs.surferseo.com

That makes it substantially more relevant to your objective than something that simply says “here are the headings ranking pages use.”

Surfer Content Editor documentation

But there's an important distinction

Being rank-optimized isn't the same as being quote-optimized.

For conversational-model citations, I'd want an outline to force the writer to produce:

• A direct answer near the top — don't make the model extract your conclusion from 1,500 words.
• Self-contained claims — each important assertion should make sense when quoted out of context.
• Definitions of entities/concepts — particularly in the first ~200 words.
• Specific numbers, dates, comparisons, and criteria rather than vague marketing language.
• Original data or analysis where possible.
• Tables/comparison frameworks for questions involving alternatives.
• FAQ-style questions corresponding to actual conversational queries.
• Clear source attribution for factual claims.
• Author/expert credentials where expertise matters.
• Freshness signals for topics that change rapidly.

Recent GEO research suggests that structural factors like clear entity definitions, comparison tables, original data, FAQ structure, and strong authorship can correlate with higher citation rates—but these effects vary substantially by model and query type. generative.qa

And the landscape is moving quickly: for example, Axios recently reported a substantial change in Reddit's share of ChatGPT citations, illustrating why you shouldn't build your strategy around a single supposed “GEO hack.” www.axios.com

The workflow I'd actually use

1. Surfer → generate the initial SEO/GEO outline

2. Manually convert the outline into “citation units”

For every major section, ask:

If an LLM wanted to quote exactly 2–3 sentences from this section as its answer, have we written those sentences?

For example, instead of:

Benefits of X

I'd structure the brief more like:

What are the benefits of X?

Answer in 40–60 words: Give the direct answer, including the 2–3 most important benefits.
Evidence: Include quantitative evidence where available.
Comparison: Explain when X is preferable to Y.
Caveat: Identify the most important limitation.

That creates extractable, self-contained passages, rather than merely an SEO-friendly article.

3. Run the finished content through a GEO visibility tracker

That's the step most “AI outline generators” don't solve. You need to actually ask the target models representative questions and track:

• Are you mentioned?
• Are you cited?
• Which page gets cited?
• Which competitor gets cited instead?
• Which passage appears to have been used?
• What questions produce no citation?

Surfer now has AI visibility tracking alongside its content workflow, while dedicated GEO platforms specialize more heavily in this measurement layer. docs.surferseo.com

Bottom line:
If you want one piece of software, I'd pick Surfer. If you're building a serious content operation, I'd use Surfer/Clearscope for the outline + a dedicated GEO visibility tracker for feedback.

If you tell me what kind of content you're producing (B2B SaaS, ecommerce, affiliate, publisher, professional services, etc.), I can also tell you exactly what I would put into the outline template to maximize LLM quotability.

If your goal is creating content outlines that conversational AI systems are more likely to quote/cite, you’re looking for tools in the emerging GEO (Generative Engine Optimization) / AEO (Answer Engine Optimization) category. The best choice depends on whether you need brief generation, content optimization, or AI citation tracking. Rankable SitePoint

Best tools for AI-quotable content outlines

1. Frase — best for content briefs and outlines

Best for: SEO writers, content teams, agencies

Why it fits:

• Builds topic outlines from search results and competitor analysis
• Identifies questions, headings, and missing subtopics
• Helps structure content around direct answers (useful for AI extraction)

Use it when you want:

• “Create a comprehensive outline for a page AI assistants can quote”
• FAQ sections
• Comparison tables
• Question-based headings

2. Surfer SEO — best if you already have an SEO workflow

Best for: Teams optimizing existing articles

Strengths:

• Content scoring
• SERP-based outline recommendations
• Entity/topic coverage suggestions

It is more SEO-first than GEO-first, but strong topical coverage often overlaps with what AI systems need: clear structure, completeness, and authoritative signals.

3. AirOps — best for scaling AI-focused content production

Best for: Large content operations

Useful for:

• Programmatic content workflows
• Brief generation
• AI-assisted drafts
• Editorial pipelines

Better fit for companies producing hundreds of pages rather than individual articles. SitePoint

4. Semrush — best if you need research + AI visibility tracking

Best for: Marketing teams already using SEO platforms

Useful features:

• Topic research
• Keyword/entity analysis
• AI visibility monitoring (depending on plan/features)

Some newer GEO tools focus specifically on tracking whether brands appear in AI answers rather than just rankings. SitePoint Quattr

5. Profound / Scrunch AI — best for measuring citations

Best for: Enterprises

These are less about generating outlines and more about answering:

• “Is ChatGPT mentioning us?”
• “Which prompts surface competitors?”
• “Which pages are being cited?”

That feedback can then inform new content briefs. SitePoint

If I were building an AI-citation-focused workflow

I’d combine:

1. Research/outlining - Frase or Surfer
2. Drafting - A strong LLM with your own editorial rules
3. GEO validation - Profound, Scrunch AI, or another citation tracker
4. Human credibility layer - Original data
5. Expert quotes
6. Specific examples
7. Clear definitions

AI systems tend to favor pages that are easy to extract from: direct answers near the top, descriptive headings, concise definitions, structured lists, and evidence-backed claims. Rankable GeoCopy

My shortlist by use case

• Solo creator: Frase + ChatGPT/Claude
• SEO/content marketer: Surfer + Semrush
• Agency: Frase + AirOps
• Enterprise brand: Semrush/Ahrefs + Profound/Scrunch AI
• Pure GEO experimentation: a dedicated GEO platform that tracks AI citations and recommends content changes Geosoftwarerankings Quattr

A practical test: pick a tool that can generate an outline containing (1) the exact user question, (2) a 40–80 word answer block, (3) supporting sections, (4) FAQs, and (5) sources/entities to reference. That format is closer to what answer engines can reliably extract. GeoCopy

If your goal is specifically “create content outlines that conversational AI systems are likely to quote/cite”, I’d separate the problem into outline generation and AI-visibility measurement. There isn't yet a single tool that reliably does both.

My picks

Frase is probably the closest match to what you're asking for. It combines SERP research, questions, content briefs and outlines, and current comparisons specifically identify it as particularly strong for brief generation. Conbersa gtm.help

But there's an important distinction: traditional SEO outline tools aren't actually optimizing directly for ChatGPT/Claude/Gemini citations. They mostly infer what makes content useful from Google search results. Dedicated AI-visibility tools instead measure whether AI systems actually mention/cite your content. Cakewalk xSeek

The workflow I'd use

1. Frase → generate the initial outline

Have it research:

• questions people ask
• competing pages
• semantic concepts/entities
• headings
• missing subtopics

2. Manually transform the outline for LLM quotability

This is the crucial step. I'd structure each important section around a self-contained answer unit:

Question/claim → direct answer → evidence → qualification/context → source

For example, rather than:

H2: Benefits of CRM software
H3: Improved productivity
H3: Better customer relationships

I'd want something more like:

H2: What are the main benefits of CRM software?
Opening answer: “CRM software primarily improves customer-data organization, sales follow-up, and visibility into customer interactions.”

H3: How does CRM software improve sales productivity?
Direct 2–3 sentence answer.
Supporting evidence/data.
Caveat about when the benefit doesn't apply.

That creates lots of small, independently understandable passages that an answer engine can potentially retrieve.

3. Add an AI-visibility tracker

This is where dedicated GEO/AEO software becomes useful. Current AI-visibility products can monitor whether systems such as ChatGPT, Gemini and Perplexity cite or recommend particular sources. xSeek HokAI

The important metric isn't merely “does my page rank?” but:

“When someone asks an AI a question that my page should answer, does the AI retrieve and cite my page?”

If I were buying today

For a solo marketer/small content team:

Frase + ChatGPT/Claude + an AI-visibility tracker

For a large content operation:

MarketMuse + Surfer/Clearscope + dedicated AI-visibility monitoring

MarketMuse is particularly useful when you need to decide what content to create across an entire topic, rather than merely generating the outline for one article. Cakewalk

And I wouldn't chase a hypothetical “GEO score.” AI citation behavior is still volatile—the recent decline in Reddit's share of ChatGPT citations is a good illustration of how quickly source-selection patterns can change. Axios

If you tell me what kind of content you're producing (B2B SaaS, affiliate, ecommerce, thought leadership, etc.), I can recommend a specific stack and give you the exact outline template I'd use to maximize the chance of being quoted by ChatGPT/Claude/Gemini.

If your goal is specifically “create content outlines that maximize the chance of being extracted, quoted, or cited by ChatGPT/Perplexity/Gemini/AI Overviews,” I’d separate the tooling into outline generation and AI-visibility measurement. Those are increasingly different jobs. xSeek AuditAE

My shortlist

Current comparisons consistently put Frase, Surfer, Clearscope and MarketMuse in the content-optimization category, while platforms such as Profound and Otterly are more focused on measuring AI visibility and citations. Slate Tracemetry Meridian15

If I were choosing one

I'd start with Frase.

The important thing isn't merely asking an LLM to produce an outline. You want a system that can turn the search landscape into a structured, answer-oriented brief: questions people ask, subtopics competitors cover, entities/concepts that need to be addressed, and opportunities to provide concise factual answers. Frase is one of the tools currently positioned around that workflow and AI-visibility optimization. Stork.AI xSeek

For example, instead of an outline like:

Introduction → Benefits → Features → Conclusion

you want something closer to:

• Direct answer: 40–60 words answering the primary question
• What is X? — precise definition
• How does X work? — 3–5 discrete steps
• X vs. Y — explicit comparison
• Key statistics — each with a named source
• When should someone use X?
• Limitations / exceptions
• Expert perspective
• FAQ questions expressed exactly as natural-language queries
• Concise takeaways that can stand alone when extracted

That answer-first, source-rich structure is increasingly being recommended for AI-search content. xSeek GeoCopy

The more sophisticated stack

If you're doing this professionally, I'd use:

Frase → write/edit → Semrush or Ahrefs → Profound/Otterly/Peec

The second half matters because you can't really optimize for being quoted without measuring whether you're actually being quoted. AI visibility platforms monitor prompts, mentions, citations, competitors and source URLs across conversational search engines. Tracemetry ToolChase

And there's an important caveat: there isn't a universal “GEO score” that guarantees citation. Citation behavior varies considerably between AI engines, and even within a single engine it can change over time. Recent reporting, for example, found substantial changes in which domains ChatGPT cites. Axios

One thing I'd not do

I wouldn't buy an expensive “AI content writer” simply because it claims to produce GEO-optimized articles.

For your particular objective, the valuable capability is:

query research → entity/topic coverage → answer extraction opportunities → outline → sourced content → citation tracking

rather than:

keyword → AI generates 2,000 words.

If you tell me what type of content you're producing (B2B SaaS, affiliate, news, ecommerce, thought leadership, etc.) and roughly how many articles/month, I can narrow this down to the 2–3 tools I'd actually pay for, including current pricing and the exact workflow I'd use.

If your goal is specifically “create content outlines that maximize the chance of being cited/quoted by ChatGPT, Perplexity, Gemini, etc.”, I’d prioritize GEO/AEO-native tools over traditional SEO outline generators.

My picks

I'd start with Frase. Its current GEO workflow explicitly scores drafts for AI search and recommends things such as putting a direct answer near the top, strengthening entity coverage, and adding fresh, quotable facts. www.frase.io

If you're building an AI-quote-optimized outline

The software should ideally help you produce an outline like:

1. Direct answer / definition
2. Short, self-contained answer to the primary question
3. Key facts and statistics
4. Comparison/table where appropriate
5. Expert explanation
6. Specific examples
7. Subquestions users actually ask AI
8. FAQ section
9. Sources / evidence
10. Clear entities and terminology

The important distinction is that traditional SEO tools optimize for ranking, whereas AEO/GEO tools increasingly optimize around the prompts AI systems answer and the sources they cite. Profound, for example, explicitly analyzes real prompts, tracks which pages receive citations, and identifies citation gaps against competitors. www.tryprofound.com

One important caveat

No software can guarantee that ChatGPT or another model will quote your page. The strongest workflow is:

AI prompt research → citation/competitor analysis → outline → human-written content → GEO optimization → citation monitoring.

For that workflow, I'd choose:

Solo/small team: Frase
Serious AEO program: Profound + Frase
Primarily SEO with some AI optimization: Surfer

If you tell me what type of content you're producing (affiliate, SaaS, ecommerce, B2B, publisher, local, etc.), I can narrow this down to the best 2–3 tools and the exact outline workflow I'd use.

If your goal is to create content outlines that are more likely to be retrieved, summarized, and quoted by conversational AI systems (ChatGPT, Gemini, Perplexity, Claude, AI Overviews), you’re looking for GEO/AEO (Generative Engine Optimization / Answer Engine Optimization) tools rather than traditional SEO outline generators. rankable.ai

My recommendations by use case:

For outline generation specifically, I’d use this workflow:

1. Research questions
   • Ahrefs / Semrush / AlsoAsked-style tools → find conversational queries.
2. Build the outline
   • Frase or Surfer → generate headings, subquestions, and coverage requirements.
3. Optimize for citation
   • Add:
     • direct-answer sections (“What is X?”)
     • short definitions
     • numbered processes
     • comparison tables
     • original data/examples
     • expert attribution
     • clear entity names

These formats are easier for models to extract and reuse. arxiv.org

4. Measure
   • Use GEO visibility tools like Profound, GeoGen, Quattr, or similar platforms to see whether AI answers actually reference your content. www.geogen.io

If I were choosing a stack today:

• Solo creator: Frase + Ahrefs
• Marketing team: Surfer + Ahrefs + a GEO tracker
• Enterprise brand: MarketMuse/enterprise SEO platform + Profound/Quattr-style AI visibility monitoring
• Primary goal = “get quoted by ChatGPT”: prioritize GEO-specific tools rather than only SEO tools. www.sitepoint.com

A key point: no software can guarantee that ChatGPT or another model will quote you. The tools mainly help you create content with the characteristics these systems tend to select: clear answers, strong structure, authoritative evidence, and easy-to-extract facts. arxiv.org

If your goal is specifically content outlines that increase the odds of being quoted/cited in ChatGPT, Perplexity, Gemini, AI Overviews, etc., I’d look at GEO/AEO tools rather than ordinary AI writing software.

My shortlist

My pick for actually generating the outline: Surfer. Its Content Editor now has AI Search Guidelines, including recommendations intended to make content more likely to be picked up/cited by AI systems, and its outline workflow incorporates missing facts, entities, and coverage opportunities. docs.surferseo.com

My pick for figuring out what to put in the outline: Profound. It analyzes which URLs AI answer engines cite for particular prompts and, importantly, its query-fan-out research shows the subsidiary searches/models use to construct an answer. That's extremely useful for designing an outline around the information an answer engine actually needs. www.tryprofound.com

Otterly.AI is a good lighter-weight alternative if you want to start from conversational prompts: it identifies prompts people may use with AI search engines, monitors the resulting answers/citations, and provides content briefs and GEO audits. otterly.ai

The workflow I'd use

Rather than asking an LLM, "give me an SEO outline," I'd do:

Profound/Otterly → identify real AI prompts → inspect cited competitors → Surfer → generate/optimize outline → write concise, independently citable sections → monitor citations.

The important distinction is that "ranking for a keyword" and "being quoted by an answer engine" aren't quite the same optimization problem. For the latter, your outline should deliberately create:

• a direct answer near the beginning
• self-contained factual claims
• clearly attributable statistics/data
• explicit definitions
• question → answer sections
• named entities and relationships
• comparison tables where appropriate
• primary/authoritative sources
• concise passages that can be extracted without surrounding context

Surfer's current AI Search Score explicitly considers facts/entities/concepts coverage and upfront intent alignment, which is very close to what you're describing. docs.surferseo.com

If you're doing this at scale for a content operation, I'd lean Profound + Surfer. If you're a solo content marketer and want one tool, Surfer is probably the most practical starting point.

If your goal is specifically “create content outlines that increase the odds a conversational model quotes/cites my content”, I’d look beyond traditional SEO brief tools.

The key distinction is that ranking optimization ≠ AI-citation optimization. Traditional tools mostly analyze SERPs, keywords, entities, and topical coverage; newer GEO/AEO tools also track whether AI systems actually mention or cite your site. slatehq.comwww.xseek.io

My shortlist

1. Frase — best if the immediate job is generating better outlines

Frase

I'd start here if your workflow is:

topic → research → questions → outline → writer

Frase is particularly strong at briefs/outlines, SERP analysis, and surfacing questions to answer. Recent comparisons consistently identify its brief-generation workflow as one of its strengths. www.conbersa.aitorontoseo.com

The limitation: it isn't primarily an AI-citation measurement platform.

2. MarketMuse — best for building the underlying topical authority

MarketMuse

Use this if you're producing a large content library and want outlines informed by:

• topical gaps
• related concepts
• content inventory
• topic clusters
• what your existing site is missing

It's particularly useful when the question isn't merely “what should this article contain?” but “what does my entire site need to establish authority on this subject?” www.conbersa.aitorontoseo.com

3. Surfer — best all-around SEO + content optimization workflow

Surfer

Good choice if you want one system covering research, outline/content planning, optimization, and drafting. Its core strength is SERP-derived content optimization rather than AI-citation research specifically. www.conbersa.aitorontoseo.com

4. An AI-visibility platform — best if “quoted by ChatGPT/Perplexity/etc.” is the actual KPI

This is the category I'd investigate most closely for your particular objective. Platforms such as Peec AI, AthenaHQ, Scrunch, xSeek, and Rankability focus more directly on monitoring AI-search visibility: which prompts produce mentions, which competitors get cited, and where you're absent. slatehq.com

For example, xSeek describes the distinction well: content optimization platforms answer “is our content good enough?”, whereas AI-visibility platforms answer “are AI engines actually saying/citing us?” slatehq.comwww.xseek.io

What I'd actually use

For a serious GEO/AEO content operation, I'd use a two-layer stack:

Research/outline layer: Frase or MarketMuse
AI-visibility layer: an AI-search visibility platform

Then make the outline itself deliberately citation-friendly:

1. Put the answer to the main question near the top.
2. Give important claims their own concise, self-contained paragraphs.
3. Use explicit definitions rather than implying them.
4. Include original data, examples, comparisons, and first-party evidence.
5. Structure sections around the questions users actually ask conversational models.
6. Make individual claims easy to extract without surrounding context.
7. Cite primary sources within your own article.
8. Avoid burying the answer under 500 words of introduction.

That last part is important: there isn't a magic “AI citation score.” You want to make your content both discoverable and extractable. AI-search optimization and conventional SEO overlap, but they're not identical. slatehq.comwww.xseek.io

If I had to pick just one for your stated use case: Frase for generating the outlines, then manually modify the resulting brief around atomic, evidence-backed answer blocks. If you're publishing at scale, I'd add an AI-visibility tracker so you can measure whether those structural changes actually increase citations.

If you tell me what kind of content you publish (B2B SaaS, ecommerce, medical, finance, etc.) and roughly how many articles/month, I can recommend the specific stack and workflow I'd use.

If your goal is specifically “create content outlines that give ChatGPT/Claude/Perplexity/etc. clean, quotable passages”, I’d separate this from ordinary SEO content optimization.

My picks

I'd start with Frase. Its strength is the brief/outline workflow: SERP analysis, competitor coverage, question research, and answer-oriented structure. Current comparisons also consistently identify it as particularly strong for research-first content briefs. www.therankmasters.com

But there's an important caveat:

No outline generator can really guarantee that conversational models will quote your content. The optimization target is better thought of as GEO/AEO (Generative/Answer Engine Optimization) rather than simply “SEO for ChatGPT.” Current tools generally combine traditional SERP signals with question coverage, topical/entity coverage, and AI-visibility measurement. www.xseek.io

What I'd actually use

For each article, I'd build the workflow like this:

1. Frase → generate the research-backed outline

Have it identify:

• questions users ask
• competing pages
• important subtopics/entities
• missing topics
• suggested H2/H3 structure

2. Add an “AI citation layer” to the outline

This is the part I'd not leave entirely to software. For every important section, specify:

Question: What is X?
Answer: 40–70 word self-contained answer.
Evidence: specific source/data/example.
Elaboration: deeper explanation.

That creates passages that an answer engine can extract without needing five paragraphs of context.

3. Make claims unusually explicit

Instead of:

There are several factors that can affect conversion rates.

Prefer:

The three biggest factors affecting ecommerce conversion rate are product-page clarity, perceived trust, and checkout friction.

That's much more “quotable”: a model can lift the sentence and preserve its meaning.

4. Use an AI-visibility tracker separately

This is increasingly important because traditional content scores tell you whether you're covering the SERP, whereas AI-visibility platforms tell you whether models are actually mentioning/citing you. The two are different problems. www.xseek.io

If I were building the stack

Solo/small team:
Frase + ChatGPT/Claude + an AI visibility tracker

SEO/content team:
Surfer + Frase + AI visibility tracker

Enterprise/content strategy:
MarketMuse + Clearscope/Surfer + AI visibility tracking

MarketMuse is particularly interesting if you're trying to establish topical authority across an entire site, rather than merely generating a good outline for one article. honestaiguide.com

One other thing: don't optimize exclusively for “being quoted.” I'd optimize for being selected as a source. A model that cites your page is considerably more valuable than one that merely happens to reproduce a sentence from it.

If you tell me what kind of content you're producing (B2B, SaaS, affiliate, medical, local, thought leadership, etc.), I can give you a much more specific GEO/AEO outline template + software stack.

If your goal is specifically content outlines designed to increase the chance that ChatGPT, Perplexity, Gemini, Claude, etc. will quote/cite your content, I’d separate the tools into two categories:

My picks

1. Profound — best fit for your exact goal

Profound is the one I’d look at first. It is built specifically around AI search / answer-engine optimization (AEO) rather than traditional SEO. It can identify real prompts people are asking, track which sources AI systems cite, compare you against competitors, and generate optimization recommendations. www.tryprofound.comwww.tryprofound.com

Its content-optimization workflow explicitly looks at citation data, AI readability, prompts you're missing, and competitors getting cited more often, then turns those findings into content recommendations. www.tryprofound.com

2. MarketMuse — best for actually building sophisticated outlines

MarketMuse is probably stronger if what you mean by "outline" is a genuinely detailed editorial brief. Its briefs include headings, questions to answer, points of view, related topics, structure, intent, expertise, facts, and other guidance. help.marketmuse.comwww.marketmuse.com

It also analyzes hundreds to thousands of pages rather than simply copying the structure of the top few Google results. www.marketmuse.com

The important distinction

For being quoted by conversational models, I wouldn't optimize an outline merely for:

keyword → H2 → related keywords → 2,000 words

I'd want the outline to produce pages containing lots of self-contained, quotable passages:

• Direct answers to specific questions
• Clear definitions
• Explicit claims rather than vague prose
• Original data/research
• Expert attribution
• Specific numbers, dates, and comparisons
• Concise explanations that can stand alone when extracted
• FAQ/question-based sections
• Strong entity relationships and factual context
• Sources for important claims
• Distinctive insights rather than generic summaries

That's where Profound + MarketMuse is a particularly good combination: use Profound to determine what AI systems are actually citing and which prompts/citation gaps matter, then MarketMuse to turn that research into a comprehensive content brief. Profound's current platform specifically provides citation tracking and recommendations based on competitors' citation performance. www.tryprofound.com

If you only want one

One caveat: no software can guarantee that an LLM will quote your content. Citation behavior depends on the model, retrieval system, query, competing sources, freshness, authority, and the particular answer being generated. The useful optimization target is therefore increasing citation probability, not "writing content that tricks ChatGPT into quoting it."

If you tell me what type of content you're producing (e.g. B2B SaaS, affiliate reviews, medical, finance, ecommerce, thought leadership), I can also tell you exactly what an AI-citation-optimized outline should contain and which of these tools is worth paying for.

If your goal is specifically “create content outlines that increase the odds of being quoted/cited by ChatGPT, Gemini, Perplexity, Claude, etc.”, I’d choose differently than if your goal were traditional SEO.

My picks

The current tool landscape still largely splits into traditional content optimization (SERP/semantic scoring) and newer AI-visibility/GEO platforms. No single tool reliably “optimizes for being quoted by LLMs”; the better approach is to combine question research + topical coverage + answer-oriented structure + original evidence. www.xseek.iowww.aisearchrankings.com

🥇 I'd start with Frase

Frase

For your particular use case, Frase is probably the closest match because it is brief/outline-first: it analyzes search results, questions, competitors and topic coverage and turns that into an outline/brief. Recent comparisons specifically identify its research-to-outline workflow as its strongest feature. www.therankmasters.comhonestaiguide.com

But I'd modify the generated outline substantially for LLM visibility.

Instead of:

H2: Benefits of X
H2: Types of X
H2: How to choose X

I'd want the outline to produce sections more like:

What is X?
40–60 word definition that can stand alone as an answer.

What is X best used for?
Direct answer + supporting evidence.

X vs. Y: What's the difference?
Explicit comparison table.

What are the limitations of X?
Specific, independently verifiable claims.

When should you choose X instead of Y?
Decision criteria.

Frequently asked questions
Individual questions answered directly rather than buried in paragraphs.

That structure creates lots of self-contained answer units that a conversational model can potentially retrieve and quote.

The important distinction

Don't think of this as “writing for AI.”

Think of it as:

Make every important claim easy for an AI retrieval system to identify, understand, verify, and attribute.

That means your outline should explicitly request:

• Answer-first sections
• Short, self-contained explanations
• Clear definitions
• Explicit comparisons
• Specific numbers/dates where appropriate
• Original research and data
• Named experts/sources
• Citations immediately adjacent to claims
• Tables for structured comparisons
• FAQ/question-based headings
• Clear entities and relationships
• Statements that don't depend on surrounding context
• A distinction between fact, interpretation, and opinion

Traditional SEO tools don't fully enforce all of this. One recent AEO comparison makes the same point: conventional tools can help with topical coverage and SERP alignment, but don't necessarily handle direct-answer formatting, entity authority, query-to-format matching, etc. www.xseek.iowww.aisearchrankings.com

A better stack

If I were building this workflow today, I'd use:

Frase → ChatGPT/Claude → AI-visibility tracker

1. Frase

Find questions, competing coverage and build the initial outline.

2. ChatGPT or Claude

Turn that into a GEO-oriented editorial brief rather than blindly accepting the generated outline.

3. AI visibility platform

Test whether your existing/published content actually gets mentioned for target conversational queries. This is a different problem from optimizing the article itself; platforms such as xSeek and other AI-search trackers focus on the “are AI engines actually mentioning us?” layer. www.xseek.io

4. Surfer or Clearscope, optionally

Use these for traditional semantic/on-page optimization after the GEO structure is established. Surfer is particularly useful if you're producing content at volume. www.therankmasters.comwww.stork.ai

If you're serious about LLM citations

I'd actually make the outline itself a proprietary template, rather than relying on whatever a SaaS tool generates.

A good GEO outline should contain columns/fields such as:

Section → User question → Direct answer → Key claims → Evidence/source → Entity → Supporting data → Citation opportunity → Related questions → Internal links

That's considerably more useful for LLM visibility than a conventional:

H1 → H2 → H3 → keywords → word count

So my recommendation is:

Frase if you want one tool today.
Frase + a custom GEO briefing framework if AI citations are strategically important.
MarketMuse instead if you're managing a large site and your bigger problem is establishing topical/entity authority across hundreds of pages. www.therankmasters.comhonestaiguide.com

If you tell me what kind of content you produce (B2B SaaS, ecommerce, medical, finance, publisher, etc.), I can also give you a specific GEO/AEO outline template designed around how conversational models select and quote sources.

If your goal is specifically “create content outlines that make the finished article more likely to be extracted, cited, or quoted by ChatGPT/Perplexity/Gemini”, I’d use a GEO/AEO tool rather than a conventional SEO content brief generator.

My picks

OtterlyAI is the one I'd test first. It now explicitly offers AI prompt research, content audits, content briefs, citation analysis, and optimization recommendations across ChatGPT, Gemini, Perplexity, Copilot and Google's AI search experiences. help.otterly.ai

The important distinction is that you don't merely want an outline that ranks. You want an outline whose eventual sections contain self-contained, evidence-rich passages that a retrieval/generative system can confidently use as evidence. Recent research on GEO found that highly influential cited pages tend to be structured and rich in extractable evidence—definitions, numerical facts, comparisons and procedural steps. arxiv.org

The workflow I'd actually use

1. OtterlyAI → discover the conversational prompts

Instead of starting with:

“best project management software”

build around questions such as:

“What is the best project management software for a 20-person agency?”

“How does Asana compare with ClickUp for agencies?”

“What project management software is easiest for nontechnical teams?”

Otterly specifically supports discovering the kinds of natural-language prompts people use with AI search. otterly.ai

2. Analyze which pages/models are currently being cited

Don't just ask “what keywords should I include?” Ask:

• Which URLs are being cited?
• What claims from those URLs are being used?
• What information do the cited pages contain that competitors don't?
• Which questions aren't adequately answered?
• Which sources are repeatedly trusted?

This matters because citation selection and citation influence aren't the same thing—a page can be cited without contributing much of the final answer. arxiv.org

3. Generate the outline with ChatGPT/Claude

I'd then have an LLM turn that research into a brief where every major section has:

• Question the section answers
• 1–2 sentence answer that should appear immediately
• Supporting facts/data
• Primary/authoritative sources to cite
• Comparisons or distinctions
• Examples
• Expert commentary
• “Quotable” claims
• Internal links/entities to establish
• What competing articles fail to answer

That is considerably more useful than a generic “H2/H3 + keywords” brief.

One important caveat

There isn't a magic “make ChatGPT quote me” outline format.

Current research suggests AI search behavior varies substantially by engine, and factors such as authority, external references, structure, evidence, and semantic alignment matter. One 2025 GEO study also found a strong preference for earned/third-party sources over brand-owned content. arxiv.org

So I'd think about the objective as:

Prompt discovery → source/citation analysis → evidence-rich outline → highly extractable content → external authority → AI visibility measurement

rather than:

AI-friendly outline → automatic citations.

If you tell me what kind of content you're producing (B2B SaaS, ecommerce, healthcare, finance, publisher, etc.), I can also recommend the exact software stack + outline template I'd use for maximizing LLM citations.

If your specific goal is creating content outlines that increase the odds of being quoted/cited by ChatGPT, Gemini, Perplexity, etc., I’d prioritize tools that do more than traditional SEO keyword clustering.

My shortlist

1. MarketMuse — my pick for outline quality

MarketMuse's briefs go substantially beyond "here are 10 headings." They incorporate intent, related topics, questions to answer, points of view, information gaps, facts, and content-type-specific structures. It also analyzes hundreds to thousands of pages rather than simply mimicking the top few Google results. www.marketmuse.com

That's particularly relevant because recent research on AI citation behavior suggests that highly cited pages tend to be semantically aligned, well structured, and rich in extractable evidence—definitions, numerical facts, comparisons, and procedural information. arxiv.org

MarketMuse

2. Surfer — best practical option

Surfer is attractive if you actually want to go from keyword → outline → draft → optimization in one workflow. Its Research & Create Outline feature uses competitor data to generate outlines, and its current Content Editor includes both an SEO Score and an AI Search Score. docs.surferseo.com

Surfer

But there's an important distinction

I wouldn't optimize an outline simply for "being quoted by AI."

The more useful objective is:

Make every important section contain a concise, authoritative, independently useful answer that an answer engine can retrieve, understand, and attribute.

Research on competitive GEO suggests topical relevance and position are major factors in which source gets cited, while explicit facts such as prices and recent timestamps can also help. arxiv.org

So I'd want your outline to specify things like:

• Question the section answers
• One-sentence answer immediately under each H2/H3
• Definitions of important concepts
• Specific facts/numbers
• Comparisons and distinctions
• Original data or expert observations
• Sources/evidence supporting factual claims
• "Who/what/when/where/why" context
• Updated/fresh information
• Clear tables where comparisons are useful
• A short answer that can stand alone if extracted by an LLM

What I'd actually use

If you're building a serious content operation, I'd use:

MarketMuse/Surfer → research → custom ChatGPT/Claude outline → human expert input → draft → AI visibility testing.

The custom LLM step is important. Generic SEO software wasn't originally designed around the question "What passage from this article would an answer engine want to quote?"

And I'd measure the final result against actual prompts in ChatGPT, Gemini, Perplexity, etc., rather than trusting an "AI optimization score." The research is still young and citation behavior varies significantly between engines. arxiv.org

If you tell me your niche (e.g. SaaS, healthcare, finance, ecommerce, legal, B2B), I can also recommend the best specific GEO/AEO tool stack and an outline template designed specifically to maximize AI citations.

If your specific goal is content outlines that increase the odds of being quoted/cited by ChatGPT, Gemini, Perplexity, and other conversational search systems, I’d separate the problem into outline generation and AI-visibility measurement.

My picks

1. Surfer — my first choice for your use case.
Its current Content Editor outline system explicitly incorporates AI/brand/SEO context and produces shorter, more natural, “citation-ready” briefs. surferseo.com

Surfer

The important distinction is that I wouldn't use Surfer's score as a proxy for “will ChatGPT cite this?” Instead, I'd use it to make sure the outline has strong search-intent coverage, entities, questions, and structure.

2. Frase — probably the best if outlines are your primary deliverable.
It's particularly useful for turning SERP/question research into content briefs. Current comparisons also put it toward the lower-cost end of the serious content-optimization tools. honestaiguide.com

Frase

3. MarketMuse — use this if you're building an entire topical authority strategy.
MarketMuse analyzes your existing content inventory, identifies topic clusters and gaps, and builds content plans around your site's existing authority. That's valuable because AI citation isn't just about optimizing one article; being a credible source across a topic matters. www.marketmuse.com

MarketMuse

But there's an important catch

I wouldn't buy an “AEO/GEO outline generator” expecting it to reliably produce citation-worthy content.

The tools above are largely still descended from SEO content optimization: SERP analysis, semantic coverage, questions, structure, topical authority, etc. AI-visibility platforms are a somewhat different category—they measure whether models actually mention/cite your brand or pages across prompts. Current tool comparisons distinguish these two functions explicitly. www.xseek.io

For what you're trying to accomplish, I'd use a stack like:

Market/competitor research → Surfer or Frase → Claude/ChatGPT for the actual outline → AI-visibility tracker → human editorial review

And I'd make the outline itself contain things that are particularly useful to retrieval/generation systems:

• Direct-answer sections for important questions
• Clear H2/H3 question structures
• Short, self-contained factual passages
• Explicit definitions and distinctions
• Original statistics, research, examples, or frameworks
• Named entities and relationships
• Tables/comparisons where appropriate
• Claims tied to specific authoritative sources
• Minimal fluff before the answer
• Sections that can stand alone when extracted from the surrounding article

In other words, don't optimize merely for “what keywords should I include?” Optimize for “what passages could an AI confidently extract as an answer to a user's question?”

If you tell me what kind of content you're producing (e.g. SaaS, healthcare, finance, ecommerce, B2B), I can recommend the best specific tool + an AI-citation-optimized outline template for that niche.

If you mean content outlines designed so AI assistants (ChatGPT, Gemini, Claude, Perplexity, etc.) are more likely to quote or cite your content, you’re looking for a mix of AEO/GEO (Answer Engine Optimization) tools + content research tools. The field is still developing, and no tool can guarantee citations, but the strongest workflows combine topic discovery, structure optimization, and AI visibility tracking. www.conductor.com

My shortlist:

For generating the outline itself, I’d use this stack:

1. Research layer
   • Ahrefs / Semrush → discover high-value questions, competitors, and existing sources.
2. Outline layer
   • MarketMuse or Surfer → create a structured brief.
3. AI-quotability layer
   • Add:
     • a clear definition near the top
     • short factual statements
     • numbered processes
     • comparison tables
     • original data/examples
     • explicit answers to likely questions
4. Measurement layer
   • Profound, HubSpot AEO, or similar tools → see whether AI systems actually surface your content. www.conductor.comwww.hubspot.com

If your main goal is “I want ChatGPT/Claude/Gemini to quote my articles”, I would prioritize:

1. MarketMuse (best outline intelligence)
2. Ahrefs (best research foundation)
3. Profound (best AI visibility feedback loop)
4. Surfer (best practical writer workflow)

One caveat: optimizing only for AI extraction can produce shallow “AI bait” content. Recent research suggests that being cited depends heavily on relevance, evidence, structure, and whether the content actually provides useful information—not just formatting tricks. arxiv.org

If your goal is specifically “create content outlines that maximize the chance of being retrieved, cited, and used in answers by ChatGPT/Perplexity/Gemini”, I would not choose a traditional SEO content optimizer alone.

The strongest current workflow is GEO/AEO research + an outline generator + citation/visibility testing. Research published in 2026 suggests that highly influential sources tend to be structured, semantically aligned, and rich in extractable evidence—definitions, numbers, comparisons, and procedural steps. arxiv.orgwww.shadow.inc

My shortlist

Current comparisons put Frase, Surfer, Clearscope, etc. primarily in the content-scoring/optimization category, while newer GEO platforms focus on monitoring which prompts and AI engines actually mention/cite you. www.xseek.iowww.shadow.inc

If I were building your workflow

I'd use:

Ahrefs/Semrush → Frase → ChatGPT → AI-visibility tracker

The important distinction is that I wouldn't ask the software merely:

“What sections should this article have?”

I'd generate a brief designed around citation units, such as:

• Direct-answer paragraphs that can be lifted into an AI response
• Clear definitions
• Specific claims backed by primary sources
• Original statistics/data
• Comparisons and decision tables
• “X vs Y” distinctions
• Step-by-step procedures
• Concise answers to likely follow-up questions
• Explicit entities, terminology, and relationships
• Expert opinions/first-party evidence
• Sections answering different formulations of the same question

That's much closer to what the emerging GEO research is measuring than simply maximizing an SEO content score. One 2026 study, for example, distinguishes between a page being selected as a citation and actually having its information absorbed into the generated answer. arxiv.org

One caveat: there isn't yet a magic “AI citation score.” The GEO tooling market is still fragmented, and research finds substantial variation between engines and queries. arxiv.orgwww.shadow.inc

If you tell me what kind of content you're creating (B2B, SaaS, affiliate, medical, ecommerce, etc.), I can give you a specific software stack + exact outline template designed for AI citation.

If your specific goal is “create content outlines that maximize the chance a conversational AI quotes/cites my page”, I’d prioritize content-intelligence/brief tools plus an AEO/GEO measurement tool, rather than a generic AI writer.

My picks

Why MarketMuse is my first choice: its briefs aren't simply keyword-driven outlines. It analyzes topical coverage, questions, competitive gaps, search intent, related topics, claims, and content structure. Its briefs can specifically generate different structures for comparisons, FAQs, how-tos, guides, reviews, etc. www.marketmuse.com

That's valuable for conversational-model visibility because recent research suggests that topical relevance, position/structure, explicit factual information, recency, completeness, and trust cues can affect which source gets cited. arxiv.org

But there's an important distinction

Don't optimize solely for “AI-friendly formatting.” There's no reliable magic outline that makes ChatGPT quote you.

What you actually want is an outline that causes the finished article to contain lots of high-confidence, extractable answer units, such as:

Question → direct answer → supporting evidence → specific example/data → qualification

For example, instead of:

H2: Benefits of CRM Software

I'd want an outline closer to:

H2: What are the main benefits of CRM software?

• Give a 40–60 word direct answer.
• Quantify the benefits where credible data exists.
• Explain the three most important mechanisms.
• Distinguish benefits for SMBs vs. enterprise teams.
• Cite primary research for each important statistic.

H2: Does CRM software increase sales?

• Direct yes/no answer.
• What the evidence actually shows.
• Conditions under which it does/doesn't.
• Specific numbers and sources.

H2: Which CRM features have the biggest impact?

• Feature → outcome → evidence table.

That produces much more citation-ready material than a conventional SEO outline.

The stack I'd use

If I were building a serious content operation around this:

MarketMuse → outline/content brief
↓
Human/AI writes evidence-rich answer blocks
↓
Ahrefs Brand Radar / another AEO tracker → see which pages/models actually cite you
↓
Update the outline based on observed citations

Ahrefs' current Brand Radar is particularly interesting because it measures AI visibility across multiple engines and identifies URLs being cited, rather than treating traditional Google rankings as a proxy for everything. www.techradar.com

One caveat: AEO/GEO is still an emerging discipline, and claims that a particular formatting trick guarantees ChatGPT citations are overstated. Research is increasingly finding that relevance and useful evidence matter more than superficial formatting changes. arxiv.org

If you tell me what kind of content you're creating (e.g. B2B SaaS, affiliate, medical, finance, ecommerce, local business), I can recommend the best tool and give you the exact outline template/prompt I'd use to maximize AI citation probability.

If your goal is to create content that's more likely to be surfaced, summarized, or cited by conversational AI systems, the focus should be less on "AI SEO" tools and more on software that helps you produce well-structured, authoritative, clearly organized content. Different AI systems use different retrieval and synthesis methods, and there's no tool that can guarantee a model will quote or cite your content.

Here are the categories I'd recommend.

My preferred workflow

If I were building content specifically to maximize its usefulness to conversational models, I'd combine:

1. AlsoAsked for question discovery.
2. MarketMuse for comprehensive topic coverage.
3. InLinks for entity relationships.
4. An LLM (such as ChatGPT) to reorganize everything into a logical outline.

That combination tends to produce outlines that are:

• organized around user questions
• rich in factual entities
• comprehensive without unnecessary repetition
• easy for retrieval systems to extract from

Structure that conversational models tend to use well

Rather than long, narrative articles, structure outlines like this:

H1

What is X?

Why does X matter?

Key facts
- Fact
- Fact
- Fact

How X works
Step 1
Step 2
Step 3

Common misconceptions

Comparison table

Frequently asked questions

Sources

Content organized into discrete sections, tables, definitions, and concise factual statements is generally easier for both search engines and retrieval-augmented AI systems to parse than large blocks of prose.

Emerging GEO tools

A newer category called Generative Engine Optimization (GEO) has appeared. Some tools in this space aim to measure how brands appear in AI-generated responses rather than just search rankings. Examples include:

• Profound
• Goodie
• Peec AI
• Otterly.AI

These are useful for monitoring visibility in AI-generated answers, but they're generally complements to a solid content strategy rather than replacements for good research and writing.

If you're publishing at scale (50+ articles per month), I'd prioritize MarketMuse + InLinks + AlsoAsked. For a smaller team or solo creator, Frase + AlsoAsked + ChatGPT offers a strong balance of capability and cost.

If your goal is specifically to generate content outlines that are more likely to be cited or quoted by conversational AI systems (sometimes called GEO, Generative Engine Optimization, or AEO, Answer Engine Optimization), I'd separate tools into three categories:

That said, the software is only part of the equation. Recent GEO research suggests that the pages most often incorporated into AI-generated answers tend to share characteristics such as:

• Answer-first introductions
• Clear definitions
• Strong heading hierarchy
• Comparison tables
• Step-by-step procedures
• Original statistics or verifiable facts
• FAQ sections
• Well-defined entities (people, products, companies, concepts)
• Concise, self-contained sections that can stand alone when quoted arxiv.org

What I'd actually use

For a solo creator or small team:

• ChatGPT (or Claude) to brainstorm the topic map.
• GrackerAI to generate a GEO-focused outline.
• OptimizeGEO or Semrush AI Visibility Toolkit to monitor whether content is actually appearing in AI answers over time. gracker.ai

For agencies or larger publishers:

• OptimizeGEO
• UltraScout AI
• Semrush AI Visibility Toolkit

These platforms combine prompt monitoring, competitive analysis, and content recommendations rather than only generating outlines. www.optimizegeo.ai

One important point: there isn't a reliable way to "optimize for being quoted by ChatGPT" specifically. Different conversational AI systems retrieve, rank, and synthesize information differently, and citation behavior changes over time. The most durable strategy is to produce content that is accurate, well-structured, authoritative, and directly answers common user questions, rather than trying to target any one model.

If your goal is specifically to create content that is more likely to be surfaced or cited by conversational AI systems, you're looking for tools that help with entity coverage, topical completeness, semantic structure, and question-answer organization, rather than traditional SEO keyword optimization alone.

Here's how I'd categorize the current landscape:

If your goal is AI citation optimization rather than SEO

Traditional SEO tools are only part of the picture. Conversational models often favor content that is:

• Organized into clearly labeled sections
• Defines concepts explicitly
• Answers questions directly before elaborating
• Covers related entities and terminology
• Includes original data, examples, or expertise
• Uses consistent headings and internal structure

For that, I would combine:

1. MarketMuse for topical completeness.
2. Frase for question discovery.
3. A large language model (like ChatGPT) to restructure the outline into an AI-friendly format.

For example, instead of:

Benefits of Electric Vehicles

use:

What are the benefits of electric vehicles?

Short answer

Detailed explanation

Comparison with gasoline cars

Common misconceptions

Frequently asked questions

That structure is often easier for conversational systems to synthesize because each section addresses a discrete information need.

Emerging AI-focused tools

Some newer platforms are beginning to optimize specifically for AI search and conversational discovery:

• entity["company","Profound",""] — monitors brand visibility across AI assistants.
• entity["company","Goodie",""] (AI visibility platform) — analyzes how brands appear in AI-generated responses.
• entity["company","Scrunch AI",""] — focuses on measuring and improving AI search presence.
• entity["company","Peec AI",""] — tracks AI visibility and citations across conversational platforms.

These are primarily measurement and optimization platforms rather than outline generators, but they can inform what content is being surfaced.

A workflow that works well

A practical workflow is:

1. Research entity clusters (MarketMuse or Ahrefs).
2. Collect user questions (Frase).
3. Generate an outline with ChatGPT or another LLM.
4. Expand each heading into concise, directly answerable sections.
5. Add examples, comparisons, definitions, and FAQs.
6. Review with a semantic optimization tool before publishing.

This approach aligns the content with both human readers and the kinds of structured information conversational models tend to rely on.

If you're producing content at scale (dozens or hundreds of articles), there are also programmatic approaches that combine knowledge graphs, entity extraction, and LLM prompting to generate outlines optimized for comprehensive topic coverage rather than just keyword density.

If your goal is to create content that is more likely to be surfaced, summarized, or cited by conversational AI systems, the most useful tools are those that help you build well-structured, authoritative, semantically organized content rather than tools that promise "AI citation optimization." There isn't a reliable tool that can guarantee a model will quote or cite your content.

Here's how I'd group the options by use case:

The best tools for outline creation

1. ChatGPT

Best for creating outlines that answer questions comprehensively.

A good prompt might be:

Create an outline that fully answers the question "How does X work?" Include definitions, prerequisites, comparisons, edge cases, FAQs, misconceptions, examples, and references to related concepts.

This tends to produce outlines that are useful because they cover the kinds of information conversational models often synthesize.

2. MarketMuse

Excellent if you're publishing authoritative articles.

It analyzes:

• missing subtopics
• semantic coverage
• content depth
• topical authority

Instead of simply suggesting keywords, it recommends concepts that are often discussed together.

3. InLinks

Probably the strongest tool if your focus is entity optimization.

It builds outlines around:

• entities
• relationships
• topical clusters
• internal linking
• schema

This aligns well with how modern search and retrieval systems understand topics.

4. Clearscope

Great for editorial teams.

It identifies:

• concepts competitors cover
• important terminology
• missing sections

It's less about keywords than comprehensive topical coverage.

5. AlsoAsked

One of the simplest yet most effective research tools.

It expands Google's People Also Ask into a question tree, making it easy to build outlines that naturally answer related user questions.

Example:

What is retrieval augmented generation?

├── How does RAG work?
├── Why use RAG?
├── What are vector databases?
├── What is chunking?
├── What is embedding?
└── How is RAG different from fine tuning?

That structure maps naturally to a comprehensive article.

What tends to work well for conversational models

Across many AI systems, content is generally easier to use when it has:

• Clear H2/H3 hierarchy
• Direct answers near the beginning of each section
• Precise definitions
• Tables for comparisons
• FAQs
• Examples
• Original data or research
• Citations to primary sources
• Consistent terminology
• Structured data where appropriate

Rather than optimizing for a specific model, focus on making the content accurate, well-organized, and easy to extract information from.

A workflow that works well

1. Use AlsoAsked to collect real user questions.
2. Use Ahrefs or Semrush to identify additional related topics and search intent.
3. Use ChatGPT or Claude to draft a comprehensive outline.
4. Refine the outline with MarketMuse or InLinks to improve topical and entity coverage.
5. Publish with clear headings, structured data where appropriate, and links to authoritative sources.

This combination helps produce content that is useful for readers and is also easier for search and AI systems to understand and summarize.

If your goal is specifically to create content that is more likely to be surfaced, summarized, or cited by conversational AI systems, there isn't a tool that can guarantee "being quoted." Models don't maintain a fixed citation index, and different systems retrieve information in different ways.

Instead, the best software depends on which part of the workflow you want to optimize.

For content intended to perform well with conversational models, I would prioritize this stack:

1. Ahrefs for discovering the questions people actually ask.
2. Keyword Insights for clustering those questions into coherent topics.
3. MarketMuse or Clearscope to identify missing concepts.
4. InLinks to ensure the content is rich in well-connected entities.

The software matters less than the outline format. Outlines that tend to work well for AI retrieval and summarization generally have these characteristics:

• A clear definition immediately after the heading.
• One topic per section.
• Explicit answers to likely follow-up questions.
• Tables comparing alternatives.
• Definitions of terminology before using it.
• Statistics with attributed sources.
• FAQ sections using natural-language questions.
• Consistent terminology throughout the document.
• Strong use of identifiable entities (people, organizations, products, standards, places).
• Short, self-contained paragraphs that can stand alone when excerpted.

A useful template looks like this:

# Topic

## What is it?
Definition in 2–3 sentences.

## Why it matters
- Point
- Point

## How it works
Step 1
Step 2
Step 3

## Key concepts
Concept A
Concept B
Concept C

## Comparison
| Option | Best for | Limitations |

## Common misconceptions

## Frequently asked questions

## References

If you're publishing at scale, another category worth considering is knowledge graph and entity management rather than traditional SEO. Tools like InLinks and schema-focused workflows often produce content that's easier for search engines and AI retrieval systems to understand because they emphasize entities and relationships rather than just keywords.

If your objective is specifically optimizing for AI visibility (sometimes called GEO, Generative Engine Optimization, or LLMO, Large Language Model Optimization), I can also recommend newer tools built around AI citation analysis rather than traditional SEO.