How To Rank in AI Overviews, ChatGPT and Other AI Tools

TL;DR
To “rank” in AI Overviews (Google), be recommended by ChatGPT (including the new Atlas browser experience), and be cited by Perplexity, you need people-first content with verifiable facts, clear structure, and clean technical signals. There’s no special schema that forces inclusion in Google’s AI features; eligibility is grounded in Search Essentials, helpful content and structured-data best practices, and Google counts AI Overviews/AI Mode traffic within the Search Console Performance (Web) report rather than a separate tab. Build answer-first pages; mark up entities; show authorship and maintenance; and monitor whether these pages are being cited and clicked.

1) What “ranking” means across engines (and why the mental model differs)

Google AI Overviews (AIO): On some queries—especially complex, multi-step ones—Search shows an AI-generated snapshot with links to learn more. You cannot “enable” AIO with a tag; there is no AIO schema. Google frames inclusion through the lens of helpful, reliable, people-first content and site eligibility. Traffic from AI Overviews/AI Mode is reported inside Search Console → Performance → Web.
ChatGPT / Atlas: OpenAI’s Atlas integrates ChatGPT into a Chromium-based browser with task-capable agents. Atlas can research across the web and compile briefings, which means it surfaces and links to public sources while you browse. Your goal is to be discoverable, citable, and useful when ChatGPT fetches and reasons over pages.
Perplexity: An “answer engine” with citations by default; its Deep Research mode explicitly runs dozens of searches and reads hundreds of sources to produce longer reports. Your goal is to provide quotable, evidence-rich sections and primary references that Perplexity can cite.

Implication: In AI Overviews and answer engines there isn’t a single linear “rank position.” Instead, you’re selected as a supporting source (cited link) or recommended as a next step. Optimising is about earning inclusion as a trustworthy citation.

2) The cross-engine foundation: people-first content with proof

Google’s guidance is blunt: create helpful, reliable content for people, not for manipulating rankings. Use the words users would use, demonstrate first-hand experience, and avoid thin summaries. These same qualities increase your odds of being linked by ChatGPT/Atlas and Perplexity when they assemble answers.

Build pages that:

Lead with the answer, then justify it (steps, thresholds, trade-offs). This mirrors AIO’s snapshot-then-links pattern and Perplexity’s citation style.
Make facts explicit (numbers, version constraints, compatibility). Clear, checkable claims are easy to quote.
Cite primary sources (standards, regulations, vendor docs).
Show authorship (bios with relevant experience) and maintenance (“Updated on…”). These map to the spirit of Google’s quality and E-E-A-T guidance (experience, expertise, authoritativeness, trust).

3) Technical clarity that reduces ambiguity

While there’s no AI-Overviews-specific markup, Google explains that it uses structured data to understand content and entities and lists supported features in the Search Gallery. Implement JSON-LD that matches visible text (Organization; Product/FAQ where relevant). Keep crawling/indexing fundamentals sound (sitemaps, internal linking, canonicalisation).

Also prioritise page experience: Google recommends achieving good Core Web Vitals; INP replaced FID as a Core Web Vital in March 2024. Fast, stable pages help users and align with what core ranking systems “seek to reward.”

4) Page patterns that get cited (and why)

Decision Guides with Thresholds
- Use an executive verdict (“For scenario Y, choose X; choose Z if…; avoid P when…”), then if/then thresholds and a comparison table.
- Why it works: AI Overviews aim to summarise nuanced decisions and link out; Perplexity quotes concise decision criteria and links the table.
Troubleshooters (procedural)
- Ordered steps, pre-checks, version specificity, rollback instructions, safety notes, and deep links to vendor docs.
- Why it works: Assistants can excerpt the step list and attribute your page, which readers can open for full context.
Policy/Regulatory Explainers (YMYL)
- Plain-English summary, who’s affected, timelines, exceptions, and links to the official text.
- Why it works: Minimises risk for assistants by grounding in primary sources; aligns with people-first reliability.

5) What’s unique to each engine—and how to tune for it

Google AI Overviews

Eligibility: No AIO switch. Inclusion is emergent from Search systems; focus on helpful content and technical health. Traffic is included in GSC Performance (Web), not a dedicated AIO report.
Queries to target: Complex, multi-step questions where a summary plus links adds value. Use users’ wording in titles and headings.

ChatGPT / Atlas

Atlas behaviour: ChatGPT performs browsing actions and compiles insights. Make your pages skimmable (executive summary, tables), machine-parsable (clean HTML, clear headings), and credible (citations).
Use case: Competitive research, vendor comparisons, step-by-step guides—be the most actionable and transparent source in your niche.

Perplexity

Citations by default: Answers and Deep Research show sources prominently; Deep Research runs multiple searches and reads many pages. Embed quotable claims and evidence blocks to be selected.

6) Monitoring whether it’s working

Search Console: Since AIO/AI Mode clicks and impressions are counted in “Web”, annotate content releases and watch queries, clicks, CTR for upgraded pages. Community guidance from Google support also reiterates this reporting placement.
AIO presence & citations: Use an AI-Overviews tracker to log whether AIO appears for target queries and which sources are linked inside the module. Treat it as directional (no single “rank”).
Perplexity mentions: Run periodic queries and Deep Research to see if/when your pages are cited.
Atlas referral patterns: When Atlas/ChatGPT browsing opens your site, engagement signals (time on page, conversions) indicate suitability as a citation.

7) A practical 60-day plan

Weeks 1–2: Research & scoping

Interview sales/support to capture decision-stage questions.
Export Search Console query data to see how users naturally phrase them (focus on low-CTR queries with impressions).
Build a conversation map: core question → constraints (budget, compliance, team size) → sub-questions.

Weeks 3–6: Production

Ship 8–12 answer-first pages using the three patterns above.
Implement Organization, FAQ (where genuinely helpful), and Product (where relevant) structured data and validate.
Add author bios and a change log on each page; include primary citations.
Improve INP/LCP/CLS for these pages first.

Weeks 7–8: Measurement & iteration

Log AIO presence and linked sources; compare linked competitors’ content anatomy and add missing facts (thresholds, exceptions, tables).
Monitor GSC Web clicks/CTR for the pages; highlight wins and losses against content updates.

8) Common pitfalls

Chasing gimmicks: There’s no “AIO schema” or hidden switch. Focus on people-first content and eligibility.
Thin summaries: Without evidence and sources, you’re harder to cite.
Ignoring performance: INP (Core Web Vital) now matters for interaction quality; slow UI undermines utility.

Bottom line

Across AI Overviews, ChatGPT/Atlas, and Perplexity, the winning pages are useful, verifiable, and legible—to humans and to machines. Write answer-first, evidence-rich resources, maintain them, and keep your technical house in order. Then measure: Are you being cited? Are those citations driving clicks in GSC “Web”? Iterate until you are the page every assistant feels safe to quote.

References (Harvard style)

Google (2025a) AI features and your website. Available at: https://developers.google.com/search/docs/appearance/ai-features (Accessed 26 Oct 2025).
Google (2025b) Creating helpful, reliable, people-first content. Available at: https://developers.google.com/search/docs/fundamentals/creating-helpful-content (Accessed 26 Oct 2025).
Google (n.d.) Introduction to structured data. Available at: https://developers.google.com/search/docs/appearance/structured-data/intro-structured-data (Accessed 26 Oct 2025).
Google (2025c) Find information in faster & easier ways with AI Overviews in Google Search. Available at: https://support.google.com/websearch/answer/14901683 (Accessed 26 Oct 2025).
Google (2025d) Is there any way to identify traffic coming from AI Mode or AI Overview? Google Support Community. Available at: https://support.google.com/webmasters/thread/382358989 (Accessed 26 Oct 2025).
OpenAI (2025) Introducing ChatGPT Atlas. Available at: https://openai.com/index/introducing-chatgpt-atlas/ (Accessed 26 Oct 2025).
OpenAI (2025) ChatGPT Atlas – Data controls and privacy. Available at: https://help.openai.com/en/articles/12574142-chatgpt-atlas-data-controls-and-privacy (Accessed 26 Oct 2025).
Perplexity (2025) Introducing Perplexity Deep Research. Available at: https://www.perplexity.ai/hub/blog/introducing-perplexity-deep-research (Accessed 26 Oct 2025).
web.dev (2024) INP is officially a Core Web Vital. Available at: https://web.dev/blog/inp-cwv-launch (Accessed 26 Oct 2025).