Until recently, B2B marketers could reasonably assume that online research ran mostly through search. A buyer identified a problem, searched for information, visited websites, consulted a few other sources, compared vendors and eventually spoke with Sales. Search was never the only source – analysts, peers, events, experts and existing relationships have always shaped B2B decisions – but search engines acted as the primary interface through which buyers navigated digital information.
That model has not disappeared. What has changed is that another layer now sits across it. AI systems increasingly help buyers frame problems, gather information, compare approaches, identify potential vendors, build evaluation criteria, synthesise evidence and prepare the questions they will put to suppliers.
Direct Answer
An AI-mediated buying journey does not mean buyers have stopped using Google, vendor websites, analysts, peers, experts or salespeople. It means AI now sits alongside those sources, and sometimes between the buyer and those sources, helping them discover, organise, compare and interpret what is available.
For CMOs, that changes what digital visibility actually means. The question is no longer only whether buyers can find us. It is whether, when they use AI alongside search, websites, experts and third-party sources, they can build an accurate and sufficiently supported understanding of our company. That moves the marketing challenge from visibility on its own toward visibility, interpretation and evidence.
Key takeaways
- AI-mediated buying is becoming an additional discovery, synthesis and decision-support layer, not simply another traffic source.
- AI use has not eliminated traditional vendor research or human interaction.
- AI can influence research well beyond early discovery, including evaluation and late-stage decision support.
- Buyers move between AI, search, vendor information, experts and independent sources rather than relying on a single channel.
- For CMOs, the quality and interpretability of organisational knowledge now matter alongside reach and traffic.
What has actually changed in B2B buyer research under AI-mediated buying?
The clearest evidence is not that AI has replaced established buying behaviour, but that it has been inserted into it. The 6sense 2025 B2B Buyer Experience Report found that 94% of buyers in its study used LLMs during their buying process, yet those same buyers still averaged 16 interactions per person with the winning vendor, which is statistically similar to 2023.
In other words, the change is less a switch from search to AI, and more a case of search, websites, experts, peers, analysts and Sales being increasingly supported, mediated and synthesised through AI.
Research from Gartner points to the same hybrid environment, although the percentages should not be compared directly because the studies use different samples and different definitions of AI use. In a survey of 645 B2B buyers, Gartner found that buyers used an average of seven information sources during a recent purchase and that 45% had used GenAI, primarily to gather information about vendors and products. At the same time, 69% preferred to validate AI-generated insights with a salesperson.
The evidence therefore points toward addition rather than substitution. AI expands the information layer without removing the need for company information, independent sources or human validation.
The old and emerging B2B research environment
| Dimension | Search-led digital world | AI-mediated buying world |
| Starting point | Buyer searches using keywords and navigates results | Buyer can describe a problem, objective or scenario conversationally |
| Research process | Buyer visits and evaluates sources largely one by one | AI can help retrieve, organise and synthesise information from multiple sources |
| Discovery | Search ranking, known brands and familiar sources strongly shape discovery | Search still matters, while AI-assisted discovery introduces additional routes to information |
| Problem framing | Buyer defines the problem before searching for solutions | AI can help structure the problem, identify possibilities and generate questions |
| Comparison | Buyer manually assembles information and comparison criteria | AI can help summarise differences, organise criteria and structure comparisons |
| Content consumption | Buyer primarily consumes individual pages and assets | Buyer may first encounter information through a generated answer or synthesis |
| Role of the website | Destination for research | Destination for buyers and a source of knowledge that AI-enabled search may retrieve |
| Role of experts | Additional source of education and trust | Expert knowledge can become part of both human and AI-assisted research |
| Role of Sales | Important provider of product and vendor information | Increasingly valuable for context, validation and complex judgment |
| Marketing challenge | Be found | Be found and correctly interpreted |
| Primary risk | Low visibility | Low visibility, weak evidence or inaccurate/incomplete interpretation |
The point of the comparison is not that the left-hand column disappears. The new layer changes how information from that world is accessed and processed.
How one research question expands into many
Traditional search made much of the research process visible to the buyer, who searched for a question, opened several results, read them, returned to the search engine and searched again. AI-enabled research performs part of that expansion on the buyer’s behalf.
Google explains in its documentation that AI Overviews and AI Mode can use “query fan-out”, generating multiple related searches across subtopics and data sources to develop a response. A single broad question can therefore trigger several narrower investigations before an answer is presented. Google also states that its generative Search experiences use retrieval and grounding against pages from its Search index, as described in Google Search Central’s guidance on AI features and websites.
This matters for B2B marketing because buyers no longer need to conduct every step of discovery manually. A buyer who asks which approaches can reduce downtime in a multi-site manufacturing environment may be shown solution categories, implementation approaches, vendors, technical considerations, potential risks, customer evidence and further questions worth investigating, all from one prompt.
For CMOs, the implication is straightforward: visibility around a company name is a different problem from visibility around the problems, categories, questions and comparisons that lead buyers toward that company in the first place.
Why this matters beyond early discovery
One of the easiest mistakes is to treat AI visibility as a top-of-funnel issue. AI is certainly affecting discovery, but current buyer research indicates that its influence extends much further into the journey.
Forrester’s 2026 B2B marketing, sales and product predictions report that 61% of purchase influencers in 2025 said their organisation had a private GenAI engine to support purchasing, or planned to have one. More significantly, Forrester found that 30% of buyers viewed GenAI tools as a meaningful interaction type during the final commit stage of their purchase.
That challenges a convenient assumption: that AI helps buyers discover vendors and then disappears once the real buying process begins. The evidence suggests something more layered, with AI supporting different questions at different moments:
- Problem framing: what exactly are we trying to solve?
- Research: which approaches and categories exist?
- Vendor discovery: which companies might be relevant?
- Shortlisting: how do these vendors differ?
- Preference building: what are the strengths, weaknesses and risks?
- Vendor validation: what should we ask the supplier directly?
- Buying-group alignment: how should we summarise competing arguments for different stakeholders?
- Final decision: what evidence, trade-offs and risks should leadership consider?
Because the role changes from stage to stage, it is more accurate to describe AI as a decision-support layer available across the buying journey than to claim that every buyer uses it continuously at every stage.
AI does not remove the importance of human expertise
More AI does not automatically mean fewer human interactions. The evidence currently points toward a division of labour, in which buyers use AI and digital self-service to obtain, organise and compare information independently, and turn to people when they need context, judgment or validation.
Gartner illustrates the tension well. In March 2026, Gartner reported that 67% of surveyed B2B buyers preferred a rep-free buying experience, while its later research found that 69% wanted to validate AI-generated insights with Sales. Those findings are less contradictory than they look: buyers want autonomy when information can be self-served, and human expertise when uncertainty increases.
A buyer rarely needs a salesperson to explain something already available on a product page. They do need a person to answer whether the solution will work in their environment, what assumptions sit behind an ROI model, how it will integrate with existing technology, what implementation will demand from their team, which of the risks identified during research are actually material, and how the approach changes at their scale.
The value of the human interaction therefore shifts away from information access and toward interpretation, validation and confidence.
Why the company website still matters
AI-mediated buying does not make the corporate website obsolete; it expands the website’s role. The site remains a place where buyers evaluate the company directly, and in AI-enabled search experiences it can also become a source from which relevant information is retrieved.
Google’s July 2026 guidance makes this clear. Generative Search features continue to rely on core search ranking and quality systems, use retrieval-augmented generation to retrieve relevant webpages, and do not require a separate GEO-specific technical architecture. Google explicitly states that foundational SEO practices remain relevant to generative AI Search, and recommends creating original, useful, non-commodity content rather than simply increasing content volume.
That creates a useful distinction for B2B marketers. The question worth asking is not how much content the organisation has, but whether the website contains enough clear, useful and credible knowledge for a buyer, or a retrieval system, to understand what the company actually knows and does.
What AI-mediated buying changes for the CMO
The shift has at least four strategic implications.
1. Discovery can no longer be managed only around branded demand
Buyers may encounter the company while researching a problem, category, method, use case or comparison long before they search for its name.
Marketing therefore has to understand the information environment surrounding the problems the organisation wants to be associated with.
2. Content architecture matters as much as content production
Another hundred articles will not automatically make the organisation easier to understand. The information needs to communicate clearly what the company knows, which problems it solves, where its expertise sits, what evidence supports its claims, what differentiates its approach, and where it may not be relevant at all.
3. AI visibility cannot be separated completely from wider authority
Buyers do not rely on one information source; they move between corporate knowledge, experts, independent evidence and direct human conversations. Optimising a single page without considering that wider environment addresses only part of the problem.
4. Marketing’s responsibility increasingly extends beyond generating the click
The commercial question becomes what interpretation of the company the buyer has formed before anyone can observe the buying process, because that interpretation influences whether the company is investigated further, shortlisted or ignored.
What boards should be asking Marketing?
The board-level question should not be “what are we doing about GEO?”, and it certainly should not be “how do we rank number one in ChatGPT?”. Both are too narrow for the scale of the change. A more useful set of questions is:
- Are we visible around the problems and buying questions that matter strategically to the business?
- Can buyers clearly determine what we are genuinely good at?
- Does sufficient evidence exist to support our most important claims?
- Can buyers identify relevant experts inside the organisation?
- Do credible external sources reinforce, or contradict, the way we position ourselves?
- Can someone researching our category reach a reasonably accurate understanding of us before speaking with Sales?
- When buyers use AI to compare suppliers, what information about us is available for those systems to retrieve?
These questions move the conversation away from a new search tactic and toward a more fundamental issue: how the company is represented in the information environment where buying decisions are now formed.
FAQ
Does AI-mediated buying mean AI is replacing Google in B2B research?
No. The stronger interpretation is that AI is becoming part of the search and research environment.
Google itself is integrating generative AI directly into Search through products such as AI Overviews and AI Mode, while B2B buyers continue to use websites, experts, peers, analysts and salespeople. Google’s documentation explicitly describes how its AI search experiences can retrieve additional webpages and perform related searches while generating responses.
The transformation is therefore not search disappearing. It is search and other research sources increasingly being supplemented by AI-mediated discovery and synthesis.
Does an AI-mediated buying journey mean company websites matter less?
Not necessarily.
The website remains an important first-party source of information for buyers. It can also provide information that AI-enabled search systems retrieve.
The strategic role of the website therefore broadens from being primarily a traffic destination toward becoming part of the organisation’s external knowledge base.
Does AI now influence every stage of every B2B purchase?
No.
There is not enough evidence to claim that every buyer uses AI continuously at every stage.
What current research supports is that AI is widely used during B2B buying and that its use can extend well beyond discovery. For example, Forrester found that 30% of buyers in its research considered GenAI a meaningful interaction even during the final commit stage. See Forrester’s 2026 predictions.
It is therefore more accurate to think of AI as an available layer across the journey, with intensity varying by buyer, category and stage.
Should CMOs replace SEO with GEO or AEO?
No.
For Google specifically, its current guidance says that established SEO principles continue to apply to generative AI Search and that no special AI-specific markup is required. Google’s official generative AI Search guidance explicitly advises companies to focus on technical accessibility and useful, original, people-first content rather than AI-specific hacks.
The wider strategic challenge goes beyond SEO terminology: organisations need information that is discoverable, interpretable and credible across the environments buyers use.
What matters now
The meaningful transformation is not a move from Google to ChatGPT. It is a move from a buying environment in which buyers navigated digital information source by source, to one in which AI helps them discover, retrieve, organise and interpret a far wider information environment.
Search remains, and so do websites, experts, independent sources and Sales. AI has simply become another participant in how buyers move between them, and that changes the CMO’s problem. The company now needs to be discoverable when buyers investigate a problem, interpretable when information is assembled and compared, credible when claims are evaluated, and verifiable when the decision becomes serious.
HiFuture describes this environment as the AI-Mediated Buying Journey: AI becomes an available layer throughout the buying process, while human expertise, external evidence and direct vendor validation continue to matter. It connects directly to HiFuture’s wider view that AI-assisted buying does not replace the existing B2B information ecosystem, but changes how that ecosystem is accessed and interpreted.
The strategic implication is therefore not to optimise the company for machines instead of buyers. It is to build an information environment that works for buyers navigating independently, for AI systems retrieving and synthesising information, and for the humans who validate high-stakes decisions.
Next transformation: if AI has changed how buyers research, the next question is when preference is formed. Continue with “From Sales-Created Trust to Preference Built Before Sales.”
Source
Source note: Percentages are presented in the context of the cited studies. Study populations, definitions and methodologies differ and should not be combined into universal B2B benchmarks.
- 6sense, B2B Buyer Experience Report 2025
- Gartner, 69% of B2B buyers turn to sales reps to validate AI-generated insights
- Gartner, 67% of B2B buyers prefer a rep-free experience
- Forrester, B2B Marketing, Sales and Product Predictions 2026
- Forrester, The State of Business Buying 2026
- Google Search Central, AI features and your website
- Google Search Central, Guide to optimizing for generative AI features
