Do we need a whole new SEO strategy for AI?

So do you need a whole new SEO strategy for AI? Well… Not a whole new strategy: A sharper version of the same strategy.

AI-powered search (AI Overviews, AI Mode, chat-style discovery) changes how people consume answers, but it doesn’t change what the systems are trying to do: surface the most useful content for a query.

Google’s own guidance still points you back to the basics: make helpful, reliable, people-first content, provide a good page experience, and make it easy for systems to understand what your page is about. Google for Developers

The real shift is that you now need to optimise for two outcomes at once:

• Classic SEO: rankings and clicks

• AEO/GEO: being the source that AI answers cite and summarise

What changed with AI, and what didn’t?

What changed

• Fewer clicks on some informational queries because the answer is shown first.

• More competition for “being the source” inside AI summaries.

• More value in clear structure, clean markup, and credible attribution.

Pew’s study is a good illustration: when an AI summary appeared, users clicked a traditional result in 8% of visits vs 15% when no AI summary appeared. Clicking a link in the AI summary itself happened in 1% of visits. Pew Research Center

So yes, the click curve has changed.

What didn’t

The systems still try to reward content that:

• satisfies intent

• adds value beyond the obvious

• demonstrates experience, expertise, and trust

That’s straight from Google’s own “helpful content” guidance. Google for Developers

Does AI mean SEO is dead?

No. But some old habits are.

If your whole plan was “publish lots of similar posts and win via volume,” AI makes that less effective. If your plan is “be the best resource on a topic and prove it,” AI can actually reward you more, because you’re easier to cite.

In our experience, AI hasn’t killed SEO. It’s punished average content. The gap between “good” and “same as everyone else” is wider now.

What’s the most important thing to keep in mind?

You already said it, and it’s the core of the whole answer:

The systems are still trying to surface content people actually find useful.

Google literally recommends self-assessing content with questions like:

• Does it provide original information or analysis?

• Does it demonstrate first-hand expertise?

• Will a reader leave feeling they achieved their goal? Google for Developers

That’s not an “AI strategy.” That’s a “make good stuff” strategy.

What does “human-first content” look like in 2026?

Human-first content is not “friendly tone and 2,000 words.” It’s usefulness per second.

Practical markers:

• The page answers the question quickly, then supports it.

• It includes specifics: examples, steps, screenshots, numbers, trade-offs.

• It’s written for someone trying to do something real, not for an algorithm.

In our experience, the biggest improvement is often the first 15 seconds. If the page doesn’t prove it will help immediately, people bounce, and AI systems have less reason to trust it.

How do we give original insights, real experience, and clear expertise?

This is the bit AI-generated content struggles with, and it’s your advantage.

Ways to do it without turning every post into a memoir:

• Add “what we’ve seen” patterns from real work

• Include decision frameworks and trade-offs (not just definitions)

• Show your working: why you recommend one approach over another

• Add proof: screenshots, templates, checklists, mini case studies

Google’s helpful content guidance explicitly asks whether content demonstrates first-hand expertise and goes beyond the obvious. Google for Developers

A simple rule that works well:

• Every major section should contain at least one detail that couldn’t be copy-pasted from 10 other blogs.

Do we need different content formats now?

You don’t need visuals and video everywhere, but you should use formats people prefer when they genuinely help.

AI has pushed a lot of users toward faster learning modes:

• short videos

• step-by-step visuals

• tool screenshots

• comparison tables (when the decision is complex)

The key is intent:

• If someone wants a definition, don’t bury it under a 5-minute video.

• If someone wants a process, visuals often beat paragraphs.

In our experience, the best “AI-ready” pages are the ones that mix:

• a fast direct answer

• scannable headings

• a strong visual or example where it reduces confusion

What does “clean structure and markup” mean in practice?

This is where a lot of “AI SEO” advice is overcomplicated. It’s mostly three things:

1) Structure that makes extraction easy

• question-based headings

• short answer blocks under each heading

• clear subsections (not huge walls of text)

• summaries and key takeaways where appropriate

This helps humans skim and helps systems understand what each section is about.

2) Schema markup that matches the page

Structured data doesn’t replace content. It labels it.

Google’s structured data guidelines are clear:

• Don’t mark up content that isn’t visible on the page.

• Don’t mark up misleading or irrelevant content. Google for Developers

That matters even more in an AI-heavy world, because consistency is trust.

3) Technical hygiene

If pages aren’t reliably crawlable, you’re invisible.

• correct canonicals

• no accidental noindex

• sensible internal linking

• fast rendering and clean templates

This isn’t glamorous, but it’s still a top cause of “we published loads and nothing happened.”

So what’s new in the strategy, if it’s not “a whole new SEO”?

Think of it as three additions to your existing SEO strategy:

Addition 1: You optimise for being cited, not just clicked

Clicks are lower on some queries, so you need visibility in the answer itself.

That pushes you toward:

• clearer definitions

• tighter writing

• more quotable sections

• credible authorship and sources

Pew also found that AI summaries and standard results cite a lot of widely trusted sources (Wikipedia, YouTube, Reddit). That’s a hint: recognisable authority still matters. Pew Research Center

Addition 2: You build topical depth, not just keyword coverage

AI systems and modern ranking systems are better at evaluating whether you actually “own” a topic.

This means:

• topic clusters

• internal linking that shows relationships

• consistent coverage of subtopics and follow-up questions

In our experience, this is where most sites are still sloppy. They have 50 posts, but they aren’t connected, and they don’t build toward “we’re the best answer.”

Addition 3: You treat authority as a product, not a tactic

Authority signals matter more when systems are summarising and selecting sources.

This includes:

• real backlinks from relevant sites

• brand mentions

• reviews and reputation signals (where relevant)

• strong About, author, and editorial pages

For 3way.social readers specifically: link building still matters, but the standard is higher. Relevance and placement quality are the difference between “authority” and “noise.” If you’re building links, focus on links that make sense in-context, from sites that live in your topic neighborhood.

What should we focus on most in 2026?

If you want the short list that lasts:

1. Intent satisfaction

• be the best answer, quickly

2. Originality and experience

• add what you’ve seen, tested, learned

• avoid “generic guide” content

3. Topical authority

• clusters, internal links, real coverage

4. Credibility

• authorship clarity, sources, reputation, backlinks

5. Machine readability

• clean structure, accurate schema, indexable pages Google for Developers

What’s less worth doing now?

• Publishing lots of near-duplicate articles targeting tiny keyword variations

• Over-optimising titles and headings while the content stays thin

• Treating schema as a hack instead of a label

• Building irrelevant backlinks just to inflate metrics

In our experience, the fastest way to fall behind in 2026 is chasing shortcuts while competitors build trust and depth.

The bottom line

You don’t need a whole new SEO strategy for AI.

You need to double down on the parts of SEO that were always supposed to matter:

• make genuinely useful content

• show real expertise and experience

• present it in formats people prefer when that helps

• keep your structure and markup clean so systems can understand it

AI didn’t change the destination, but it slightly changed the route people take to get there. If you keep building the best resource, and make it easy to interpret and trust, you’ll be fine long-term.