Is traditional SEO still important after AI Mode?

Yes. AI Mode and AI Overviews draw their supporting links from Google's index, so a page that is not crawlable, indexed and eligible for a snippet cannot appear in them. Traditional SEO is the entry ticket to AI search.

Does AI SEO need different keywords?

It needs the same keywords plus the longer questions people ask AI assistants. Track the full questions your buyers ask, not only short keywords, and cover the follow-up questions a page should answer.

Do backlinks matter for AI search?

Links still help pages get found and trusted by search engines, which AI answers draw on. Mentions of your brand on trusted sites, linked or not, also shape how AI answers describe you.

Is AI SEO harder than traditional SEO?

The content work is about the same; the measurement is harder. AI answers vary between runs and users, so you track rates over many questions and runs instead of reading one position.

Which should I start with, AI SEO or traditional SEO?

Traditional SEO, because AI search depends on it. Fix crawling, indexing and the quality of your key pages first, then add AI crawler access, answer-first formatting and AI visibility tracking.

Can the same team handle both?

Usually yes. The writers, developers and SEO lead who do traditional SEO already do most of what AI search needs. The new skills are reading AI visibility data and earning mentions on the sites AI answers draw on.

AI SEO vs Traditional SEO: Same Base, New Scoreboard

AI SEO vs traditional SEO: the short answer

AI SEO is traditional SEO with two additions. The foundations do not change: pages must be crawlable, indexed, useful and trusted. What AI SEO adds is speed, as AI tools take on research and drafting, and a second scoreboard, as AI answers in ChatGPT, Perplexity, Gemini and Google's AI Overviews are measured by how often you are mentioned and cited rather than by where you rank.

Google treats the overlap as near total. Its guide to optimizing for generative AI features says that, from Google Search's perspective, optimizing for generative AI search is "still SEO." The differences sit in the details below. For the two meanings of the term itself, see what AI SEO means.

Side by side

	Traditional SEO	AI SEO adds
Goal	Rank pages in search results and earn clicks	Be mentioned and cited in AI answers, and do the work faster with AI
Research	Keywords, volumes, difficulty	Longer questions and buyer prompts; AI clusters the research
Content	Pages that match intent and beat competing results	Answer-first sections that can be quoted on their own; AI drafts, people check
Technical	Crawling, indexing, speed, structured data	Access for AI crawlers such as OAI-SearchBot and PerplexityBot
Authority	Backlinks and reputation	Mentions on the sites AI answers draw on, linked or not
Measurement	Rankings, clicks, traffic	Mention rate, citation rate and share of voice per AI engine
Tools	Keyword tool, rank tracker, site crawler	AI visibility tracker; AI writing and analysis tools

What stays the same

Getting found. Google's documentation on AI features says a page must be indexed and eligible to be shown with a snippet to appear as a supporting link in AI Overviews or AI Mode, with no additional requirements and no special schema.

Quality. The same guide asks for "non-commodity" content: expert or experienced takes that go beyond common knowledge. That has always been what ranks; AI answers raise the stakes because a generic page has nothing to offer a summary that has already read ten others.

Trust. Named authors, sourced claims and a reputation other sites confirm matter to rankings and to AI answers alike.

What is different

The target: one answer, not ten links

A results page ranks ten links and lets the searcher choose. An AI answer writes one response and cites a handful of sources. Being one of those sources is the goal, and the competition for it includes every page that covers the same ground.

Questions are longer, and the engine asks follow-ups

People type longer questions into AI search. In its October 2026 earnings remarks, Alphabet said AI Mode queries are on average three times longer than traditional searches. Google's AI features may also use what it calls query fan-out, "issuing multiple related searches across subtopics and data sources" to build a response. A page that answers the main question and the obvious follow-ups is more useful to that process than one that answers a single keyword.

The scoreboard

A rank tracker cannot tell you whether ChatGPT named you. AI answers also change from run to run, so a single check means little. The method that works is a fixed set of buyer questions, run through each engine on a schedule, with mention and citation rates reported over time. How to measure AI share of voice covers it in detail.

For Google's side, Search Console includes traffic from AI features in the Performance report's Web search type, and a separate generative AI report shows impressions in AI Overviews and AI Mode.

Who reads your robots.txt

Traditional SEO mostly cares about Googlebot and Bingbot. AI SEO adds crawlers such as OpenAI's OAI-SearchBot, which OpenAI says it uses to surface websites in ChatGPT's search features. Blocking it removes you from those answers. The AI crawler audit lists sixteen bots and what each does.

How the work gets done

The other half of AI SEO is process: AI tools cluster keywords, draft briefs and first drafts, write schema and suggest links, while people choose topics, add original insight and check facts. How to use AI for SEO lays out that workflow step by step.

Where to put effort

If your situation is...	Focus on
Pages are not indexed or the site is slow	Traditional technical SEO first; nothing else works until this does
You rank but get fewer clicks than before	Comparison and decision pages, plus tracking AI mentions to see where the value went
Competitors appear in AI answers and you do not	Answer-first pages, sourced claims and mentions on the sites the engines cite
You publish too slowly	AI-assisted research and drafting, with a person checking every page
You cannot tell what is working	A baseline for both scoreboards, compared monthly

Self-check

Are your important pages indexed and eligible for snippets?
Can AI crawlers such as OAI-SearchBot and PerplexityBot reach them?
Does each key page answer the main question in its first two sentences?
Do you know how often AI engines mention you for your top buyer questions?
Do you use AI to speed up research and drafting, with a person checking facts?

1 and 2 are traditional SEO; 3 sits in both; 4 and 5 are what AI SEO adds.

Risks of treating them as separate

Risk	How to manage it
Chasing AI tactics on a site Google cannot crawl	Fix crawling and indexing first; AI answers depend on them
Dropping traditional SEO because "AI killed SEO"	Keep earning rankings; they feed AI answers too
Running two teams with two strategies	One content plan, two scoreboards
Judging AI visibility on one check	Track rates over many prompts and weeks

Where Veritas fits

Veritas covers both columns of the table. The traditional side: keyword research, rankings and a site audit that checks pages for Google's crawler and AI crawlers in the same crawl. The AI side: an AI visibility tool that tracks ChatGPT, Perplexity, Gemini and Google AI Overviews, and drafts that carry a source for each claim.

The bottom line

AI SEO and traditional SEO are one discipline with two scoreboards. Keep the foundations, since AI search depends on them, and add AI crawler access, answer-first pages, mentions on trusted sites and AI visibility tracking. Use AI to do the work faster, and people to keep it accurate.

Want to see both scoreboards side by side? Get started with Veritas.

AI SEO vs Traditional SEO: What Is the Same, What Is Different