TL;DR: There are not sixteen different jobs here. Almost every AI answer engine grounds on one of four retrieval sources: Google’s index, Bing’s index, a proprietary crawl, or an aggregate of other people’s results. Once you know which bucket an engine sits in, you already know most of what to do for it. The genuinely engine specific work is a short list, and three or four engines are worth deliberate effort for a service business. The rest follow for free.
The four retrieval buckets
Chasing engines one at a time is how you end up doing the same work sixteen times. Group them by where they actually get their sources and the picture collapses into something manageable.
| Bucket | Engines | What moves the needle |
|---|---|---|
| Grounds on Google | Google AI Overviews, Google AI Mode, Gemini, Google Assistant | Your Google ranking and Google indexable structure |
| Grounds on Bing | ChatGPT search, Microsoft Copilot | Your Bing presence, which most firms never check |
| Own crawl or index | Perplexity, Brave, Kagi, Andi, Liner | Crawler access, freshness, third party corroboration |
| Aggregates others | DuckDuckGo AI, Poe, Komo, You.com | Breadth. You win by being cited in the engines underneath |
The practical consequence: if you fix your Google presence and your Bing presence, you have addressed the two buckets that carry the most query volume. Everything else is incremental.
Grounds on Google
Google AI Overviews and AI Mode. Structure each page to answer one question directly in the first two sentences, back it with original data and schema, and earn the entity signals that prove authority. Page one is no longer sufficient on its own: only about 38 percent of cited pages appear in the organic top ten, so citation depends on extractability as much as ranking.
Gemini. Grounds on Google Search, so your Google ranking and Google indexable structure carry more weight here than for any Bing backed engine. There is no separate Gemini optimisation worth the name. Rank in Google and you are most of the way there.
Google Assistant. Same index, voice shaped output. Favours short, declarative answers and complete Google Business Profile data for anything local.
Grounds on Bing
ChatGPT search. Retrieves through OAI-SearchBot against a Bing derived index. This is the single most overlooked gap we see: firms obsess over Google and have never once looked at Bing Webmaster Tools. If you are not in Bing’s index you are not in ChatGPT’s retrieval, whatever your Google position.
Microsoft Copilot. Answers from the Bing index with Microsoft’s own ranking layer on top. Fix Bing once and both improve.
Runs its own index
These reward crawler access and corroboration rather than rank position.
Perplexity. Runs a real time web search on every query rather than leaning on training data, so recency and crawl access matter more here than anywhere else. It also leans unusually hard on discussion content. Per the Wix Studio AI Search Lab dataset, discussion sources account for 17.35 percent of Perplexity citations, more than double the cross engine average. Reddit threads and forum answers frequently outrank brand owned pages. If you want Perplexity, you need to exist in conversations, not just on your own site.
Brave. Independent index, more than 50 million queries a day, and its Search API is licensed as a retrieval backend for other AI products. A citation here can surface in places you did not optimise for.
Kagi. Grounds on its own index built on its own crawler plus licensed sources, with an aggressive quality filter. Rewards clean, low clutter pages. Small audience, but a high value one.
Andi. Runs a proprietary semantic index that reads full page content, scores over 450 signals per page, and filters spam aggressively. Judges meaning and credibility rather than keyword overlap.
Liner. Built for research, running on an index of roughly 460 million scholarly documents alongside the open web. Rewards credible, well sourced, clearly structured pages more than most engines. Relevant if you publish original data.
Aggregators and multi model front ends
DuckDuckGo AI, Poe, Komo, You.com. These sit on top of other engines or let users pick a model. You do not optimise for them directly. A brand cited across ChatGPT, Claude and Gemini appears no matter which bot the user picks; a brand cited in only one appears only when that one is selected. Breadth is the whole strategy.
The agentic ones, which change the stakes
ChatGPT Atlas is a browser that acts rather than an assistant that answers. It reads live pages and, in agent mode, fills forms and starts checkouts. A page that is easy for an agent to read and act on is now a conversion surface, not just a citation target.
Arc Search dispatches a Browse for Me agent that opens five to seven pages, extracts the key facts and assembles one answer. You are optimising to be in that handful.
Genspark runs a multi agent pipeline that plans, executes and verifies across steps, so it checks claims harder than a retrieve and cite engine does. Unsupported assertions get dropped.
Phind answers inside VS Code with the developer’s own codebase as context. Only relevant if you sell to developers, but if you do, your documentation competes at the moment someone is writing code against your product.
Which of these deserve your time
For a law firm, a cosmetic surgery practice or a B2B company, the honest ranking:
- Google AI Overviews and AI Mode. Largest volume by a wide margin.
- ChatGPT search. Second largest, and the Bing dependency means it is often the easiest win available.
- Perplexity. Smaller, but the users are in research mode and convert well.
- Everything else. Follows from the above. Do not build a separate workstream.
Mistral’s Le Chat, Samsung Galaxy AI, Apple Intelligence, Alexa Plus, Meta AI, DeepSeek, Grok and Felo each have their own quirks, and several serve specific language or regional audiences well. None justify dedicated effort for a US service business before the first three are handled.
What actually earns the citation, in every bucket
The engine specific detail above matters less than four things that apply everywhere:
- Crawler access. Confirm you are not blocking OAI-SearchBot, PerplexityBot, ClaudeBot or Google-Extended. See our list of AI crawlers.
- A direct answer in the first two sentences. Engines lift extractable statements. Burying the answer under 400 words of preamble is the most common reason good pages never get cited.
- Third party corroboration. Every engine weights what other credible sources say about you. This is the part that cannot be done on your own website, and it is why digital PR drives AI visibility.
- Freshness. Retrieval based engines check dates. A 2024 page answering a 2026 question loses to a worse page that is current.
Local businesses
If you serve a geography, the profile matters more than the website. AI engines ground local recommendations in Google Business Profile data, so a complete profile with consistent NAP, real reviews and accurate categories is the foundation. Our guide to Google Business Profile categories for law firms covers the part most firms get wrong.
Can you do this without backlinks?
Partly, and less than people hope. Perplexity’s heavy weighting of discussion content means a well regarded Reddit presence genuinely can carry you there. ChatGPT is comparatively more conservative and leans harder on established sources. So you can buy yourself a foothold in one or two engines without links, but the engines with the most volume are the ones where earned authority matters most. Treat a no backlink approach as a start, not a strategy.
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