As AI replaces clicks with answers, user engagement moves deeper into the funnel. Here’s how SEO and content strategies must adapt.

AI Overviews or generated answers that are displayed at the top of the search results are enhancing the search experience of the searcher.

In the case of businesses that are dependent on content to generate search engine traffic the effect is much more negative.

This is not the first time that Google has been heading towards more helpful results, and zero-click searches are not a novel concept.

AI Overviews hasten this transition, taking away a lot of the traffic potential that search had previously delivered.

How AI changes the work of search

The pattern of search had been the same:

• One of the users typed a brief query, e.g., team building companies.
• Google has bounced back a page of sponsored and organic results.
• Reviewing and refining were done by the user.

The majority of the work was done towards the end of the process. 

Google ranked results in terms of intent and behavioral indicators, yet users still needed to page through the listings and make follow-up searches and assemble an answer.

AI reverses that flow:

• The user poses a more specific question.
• AI conducts several searches and processes the outputs.
• AI provides a summarized answer.

Refining is possible with traditional search, although with every new query, it essentially reinvents the experience.

In its turn, AI is conversational. The interactions are sequential on each other, with a close-in on what the user wants.

What is created is a more rapid, cleaner way to get an answer – and much less effort is needed by the user.

The path of least resistance

This change is significant as it is in accordance with a natural human tendency.

 It is human tendency to take the path of least resistance. When it is easier and gives a better outcome, it becomes adopted within a short period.

This is what search has done to the previous marketing media like the Yellow pages.

The desire to take the easiest way is an evolutionary aspect that probably worked well with human beings in the past. 

Nowadays, however, it tends to influence behavior in less deliberate ways such as the way people deal with information and ads.

AI may not be flawless, yet it is generally faster, simpler, and more productive compared to searching classical search results.

That advantage is that it is bound to be adopted on a large scale as AI is still incorporated into the sites, apps, and tools that people use.

What does this mean for search marketing?

Recent reports have indicated that an increasing number of users are entering research using AI tools instead of search engines.

Such researchers always find their opponents, yet the bigger picture is more of a moot one: AI is universal.

AI has become a default and so much a part of tools already in the hands of people that it is becoming so implicit. 

Search engines, messaging apps such as WhatsApp and mobile phones are all heading towards this way and this is not the end. 

As the Google AI will power up a large portion of the mobile devices, the transition to AI-first experiences will speed up as Google has signed a multiyear agreement with Apple.

One can easily imagine an AI-first future, just as desktop to mobile and then mobile-first.

What this change actually looks like

Generative responses are moving towards a point in which the user input is when they are already in the funnel and engagement is beginning more in the middle of the funnel with content that displays experience and expertise.

This is what the user would traditionally consume through the web of a company, or other proprietary platforms like YouTube.

This does not imply that top of funnel contents are no longer relevant. There remains the blogs, guides and videos, especially videos.

It can be questioned though as to whether that content is being distributed in the best way or whether relying on the conventional organic search is the only way.

In addition, with the development of the AI tools including Gemini and ChatGPT, it is now possible to delegate a lot of this work done by AI and save some time.

As a case in point, the shift will look as follows:

• In Mid market ERP platforms. Where the user is required to filter through results, compare alternatives, create spreadsheets and do massive manual verification.
• To Which mid-market ERP systems are best in manufacturing companies, interoperate with our current stack of X, Y and Z, and will not fail at implementation time?

This is switched to a position where the user has to work hard.

Greater sophistication in the question or input of a question leads to a much stronger output or response.

It might be said that the normal search had become a kind of garbage in, garbage out (GIGO) where brief, generalized queries gave results full of ads and mixed together results that took time to truly extract the information.

The result is user fatigue. Incessant clicking, advertisement evasion, and sifting through vastly different content is now a burden.

And even when users are at the destination they do not always get a better experience. Websites that are traffic-starved, filled with advertisements can be as annoying to browse and find useful information on.

AI provides a less cluttered and quicker experience that provides summarized advantages, disadvantages, and supporting data at every decision-making phase..

All this is possible within an AI tool, where it may never require the user to access the site where the content is created.

AI is rapidly becoming the interface of defaulting information. These are the initial years and experience will only get better and become quicker, smoother and more efficient as time goes by.

The point of the SEO vs GEO/AEO/AIO discussion is that, even though the landscape changes, SEO and GEO are not much different.

It is very much true and as it were, it is like the early days of SEO when the long-tail prospects existed. 

The depth of the mid-funnel content that you can now go has no longer to be read through by human beings.

Rather, it can be consumed by AI and summarized on the parts that are relevant.

The strategies are mostly similar. A lot of AI is yet to be utilized as it is still resting on the traditional search, and the SEO policies and implementation can be modified to make sure that no stone is left uncovered.

One should also avoid throwing the baby with the bathwater.

The value of SEO, PPC, and other similar avenues is not diminished in the sphere of AI.

How to adapt in an AI-first search environment

The game has changed. To plan in 2026 and beyond, an individual must consider the inevitable truth of change and adjust accordingly to survive in the world of AI search.

Website

With the conventional forms of SEO and PPC, users are likely to get the most suitable page to their query.

That can be high level funnel related marketing content that drives more into the journey or directly to product or service pages.

This continues to occur, with a certain rise in those visiting homepages as a result of brand searches following AI-based research.

Consequently, the navigation and communication in the websites will have to be extremely clear.

You should learn what users need and simplify the way to a specific content to the maximum.

The ALCHEMY web site planning model can be used to redesign websites in accordance with the needs of an AI-sensitive user.

Content 

The devil in the details in the era of AI.

 To get AI to suggest your brand or feature in a more and more fined researches, the most critical content that you have should be visible and accessible so that one can be retrieved and used to generate AI responses using retrieval-augmented generation, or RAG.

Marcus Sheridan frameworks like “They Ask, You Answer (TAYA) are especially effective in this case. 

The reasoning is straightforward: As long as the customers pose the question, they need to be answered.

The model revolves around five central spheres which were found out through the help of wide research that satisfy customer requirements, stimulate interaction, and give AI the specifications it requires to chart to actual queries on the user side.

This strategy is effective since it has logic. It will be beneficial to the users, enhance visibility, generate leads, and facilitate the selling process. It is not a theoretical AI strategy. It is good marketing.

TAYA has five major areas that it targets:

• Pricing and cost: When the users search the prices and fail to locate the same, they do not assume that they are required to make a call to seek enquiries. They even tend to expect that the item is prohibitively costly or they hold information, and they leave or request AI to provide the rate of a competitor. You need to clarify the cost determining factors even in case of custom pricing.
• Problems: Solve the glaring problems. This consists of issues with what you are offering, your market, and the disadvantages of certain solutions. Openness to limitations helps to establish trust better than over-positiveness.
• Oppositions and comparisons: Buyers are making a choice between alternatives. Failure to develop comparison content will make someone do it. Be objective. In case there is a more fit competitor to a particular usage scenario, state it and target your preferred customer profile.
• Reviews and ratings: People seek the best and take into consideration the peer opinion more than brand claims. Make sincere posts of products and services in your area, competitors too. It is an educational process to both the users and brand.
• Best in class: It is a common search query of users to find the best. The lists like the one made up of the Top AI marketing agencies in [city] are helpful, even though they contain the competitors. The incorporation of alternatives proves that customer fit is more important than self-promotion.

These five topics are among the most valuable data points that RAG systems have in 2026 in terms of AI and SEO.

The Value Proposition Canvas and the SCAMPER are some of the tools that can enable ideation and content variation, thus enabling AI to get to know your offerings better.

Checklist: RAG-friendly formatting tips

Do not dismember content into senseless bits. Rather, use formatting to support RAG systems browsing full resources:

• Write question-based headers: Replicate actual user queries in H2s and H3s, e.g. How much does X cost?
• Be head with the solution: Use the inverted pyramid. Begin with the direct response, and provide context.
• Attributes should be used as bullets: Bullets make RAG systems harvest structured information.
• Define abbreviations: Have one sentence long definitions of industry jargon.
• Connection to evidence: Use sources of statistics and findings to prove credibility.

Blog posts should be used as a source of knowledge to AI. The more implicit the information the more explicit the information the more retrievable your brand is.

Write for humans, not for bots

It will be necessary to repeat it: It should not be simplified just in order to make it easier to use by AI.

Google Search Liaison Danny Sullivan has made it clear that Google does not desire to have its content rewritten to chunks that AI can digest.

Most search systems and RAG pipelines have the capability of extracting relevant information in well structured, long form content.

No expertise needs to be watered down, no multiple versions of the same page have to be made.

A common example is the deep-linking to a particular part of a page of search results. It is not a new technology but established behavior.

Other formats, like FAQs, also have a natural benefit of being concise. Judge according to the question to be answered.

SEO v2026.0

These are positive changes. SEO is turning into a marketing-related activity and a marginalized field.

The world is changing and the emerging technologies are transforming the way individuals access information and make decisions. But still there are many fundamentals.

The same tricks of SEO still work, but AI has become a hyper consumer and summarizer of information that plays a role in the decision.

The challenge is to find, develop and organize such information in a way that as users pose a question, you already know the answer and you are already in the discussion.