B2B buyers now use AI to frame problems, research vendors and compare options. In the 6sense 2025 B2B Buyer Experience Report, 94% of buyers said they had used large language models (LLMs) during their buying process. Search, vendor websites, analysts, peers and Sales still play their part. AI now works alongside all of them, and buyers often form a clear view of a vendor before that vendor knows a buying process has started. For marketing leaders, this changes where competition happens and what marketing has to influence.
AI is changing B2B buying through five connected shifts. Research is becoming AI-mediated, and buyer preference forms before Sales gets involved. Buyers judge authority through the company, its experts and independent proof, and they read all of those sources as one information ecosystem. Finally, a deal needs confidence across the whole buying group. AI did not start every one of these shifts, but it accelerates and amplifies them. Together they move a large part of B2B competition to a stage that vendors rarely see.
Key takeaways
- 94% of B2B buyers used LLMs during their buying process, while human and vendor interactions remained important (6sense, 2025).
- 94% of buyers ranked their shortlist before engaging sellers, and the vendor preferred at that point won 77% of the time (6sense, 2025).
- Across 9.5 million AI citations analysed by Meltwater and LinkedIn, LinkedIn was the second most-cited source, and 75% of its citations came from individual members (2026).
- Buyers and AI systems combine a company’s website, experts, PR, partners and Sales into one interpretation of that company.
- Buyer preference turns into a deal only when the buying group can justify, approve and implement the decision.
How is AI changing B2B research?
AI has become an always-on participant in the B2B buying journey. Buyers use it to frame problems, gather information, compare options and synthesise what they find. They also keep using search, vendor websites, analysts, peers, experts and Sales.
The 6sense 2025 B2B Buyer Experience Report shows both sides of this picture. 94% of buyers said they had used LLMs during their buying process, and human and vendor interactions remained important at the same time. HiFuture describes this reality as the AI-Mediated Buying Journey, in which AI continuously influences discovery, research, comparison, validation and decision-making.
This widens the core question for marketing. “Can buyers find us?” still matters. Marketing now also has to ask whether buyers, and the AI systems that help them, can build an accurate understanding of what the company knows, what it does and why it deserves consideration. Appearing in an AI answer is the first step. Correct interpretation is what gives a company a fair chance of making the shortlist.
Why does buyer preference form before Sales gets involved?
Buyers now complete much of their research, comparison and ranking on their own, so a preferred vendor often exists before the first sales conversation. In the same 6sense research, 94% of buyers said they had already ranked their shortlist before engaging with sellers. The vendor preferred at the end of that pre-contact phase won 77% of the time.
HiFuture calls this self-directed phase the Trust Formation Zone. It is the part of the journey where buyers and AI systems build trust, shortlists and preferences before anyone from Sales is involved.
For go-to-market teams, this means visible intent can be a late signal. A demo request or an inbound enquiry may be the result of influence that has already happened elsewhere. The buyer often arrives at the first conversation with a shortlist, assumptions about each vendor and an initial favourite. Sales then inherits an existing market interpretation and works to validate and deepen it.
Who do B2B buyers and AI systems trust?
Buyers build trust in a vendor through three complementary sources: what the company publishes, which identifiable experts visibly know the subject, and what independent sources say about the company. Corporate brand still matters, but it now sits inside a much wider set of signals that includes customer stories, partner validation and the people behind the company’s claims.
Visible experts play a particular role because they make organisational knowledge attributable. They show who understands the problem and what experience supports the company’s claims.
The same applies to AI-assisted discovery. In May 2026, Meltwater and LinkedIn analysed 9.5 million AI citations across six AI platforms and 16 B2B categories. LinkedIn ranked as the second most-cited source overall. 75% of LinkedIn citations came from individual members, compared with 25% from Company Pages.
The data describes citation sources, so it supports a careful conclusion. Identifiable human expertise is already part of the source environment that AI systems can surface. Expertise that stays invisible has fewer opportunities to influence a buying decision.
Figure 1. Share of LinkedIn citations in AI answers by source type. Source: Meltwater and LinkedIn, May 2026 (9.5 million AI citations, six AI platforms, 16 B2B categories).
HiFuture’s Authority Signals Model™ organises these sources into three groups.
| Signal group | Core question | Examples |
| Company Authority Signals | What does the organisation know and prove? | AI-readable website, case studies, methodologies, decision content such as pricing, ROI and comparisons |
| Human Authority Signals | Who demonstrates the expertise? | LinkedIn profiles, posts and articles, expert pages on the website, webinars, public speaking |
| Third-Party Authority Signals | Who independently validates it? | PR and analyst mentions, expert and company citations, customer testimonials, industry communities |
Figure 2. The Authority Signals Model™: company knowledge, visible expertise and independent validation shape how one company is interpreted. Source: HiFuture, 2026.
Why does consistency across sources matter in AI-assisted research?
Buyers encounter information about one company, even when that information comes from many teams inside it. The website, executive thought leadership, PR, customer evidence, partner marketing and Sales often have different owners. Buyers never see those internal silos.
AI-assisted research adds another layer. Google explains that AI Overviews and AI Mode may use a “query fan-out” technique, which issues multiple related searches across subtopics and data sources to develop a response. When information from different sources is retrieved and interpreted together, contradictions between those sources become easier to spot.
HiFuture calls the resulting condition Authority Fragmentation. In this condition, an organisation’s knowledge, expertise, evidence and external validation stay disconnected across people, teams, channels and sources. Buyers find it harder to build trust, and AI systems find it harder to form a clear and consistent interpretation of the company.
Consistency leaves room for different voices. Executives, experts, Sales and partners should each speak in their own words and from their own experience. Their perspectives should still reinforce one coherent understanding of what the organisation knows, what it does and what it can prove.
Why is buyer preference not enough to win a B2B deal?
Complex B2B purchases are decided by buying groups, so one person’s preference rarely closes a deal. A champion may prefer one vendor while Finance questions the economics, Security sees too much risk, IT doubts the implementation and Procurement challenges the commercial case.
Gartner research found that 74% of surveyed B2B buying teams demonstrated what Gartner described as “unhealthy conflict” during the decision process. Even after a preferred vendor emerges, the group still needs enough shared confidence to move forward.
HiFuture refers to this state as Collective Decision Confidence, the shared confidence a buying group needs to justify, approve and implement a decision. A vendor that wins early preference without building this confidence can still lose the deal or see it stall in “no decision”.
What do these shifts mean for marketing leaders?
Taken together, the five shifts change where B2B competition happens and what marketing has to influence. They lead to three practical implications for CMOs and their teams.
Marketing has to compete before the opportunity is visible
If buyers can form a shortlist before they make contact, demand capture sits downstream of an earlier competitive battle. Marketing has to shape how the company is understood before the buyer raises a hand.
Company expertise is a corporate growth asset
Executives, specialists, sellers and subject-matter experts carry knowledge that buyers want to see. Treating them only as personal brands or advocacy participants underuses that knowledge. The more useful question for leadership is which expertise the company needs to make externally visible, and through which people.
AI visibility needs orchestration across teams
Website content, expert voices, PR, customer proof, partners and Sales may have different owners. Buyers and AI systems still meet them as one information environment. The goal is to make these sources reinforce a coherent understanding of what the company knows, what it is credible for and why it should be considered.
In HiFuture’s view, these implications point to two distinct go-to-market battles. The first is Win Early Preference, which means building trust and buyer preference before Sales engagement. The second is Become Chosen, which means helping the buying group confidently validate and approve the decision. A company can lose before it sees the opportunity, and it can also lose after becoming the preferred option.
Authority Orchestration™ is the strategic marketing discipline HiFuture developed for this environment. It designs, connects and activates Authority Signals as one consistent ecosystem across the buying journey. As HiFuture puts it, “Buyers and LLMs don’t evaluate marketing activities individually. They evaluate the authority those activities create together.”
Figure 3. Five shifts in AI-era B2B buying. The table below adds the question each shift raises for marketing. Source: HiFuture, 2026.
| Shift | From → To | The question marketing must answer |
| 1 | Google-Led Research → AI-Mediated Buying Journey | Can buyers and AI systems build an accurate understanding of what we know and do? |
| 2 | Sales-Created Trust → Preference Built Before Sales | Are we shaping preference before the buyer contacts us? |
| 3 | Brand Trust → Company, Expert and Third-Party Trust | Which experts and external sources make our expertise credible? |
| 4 | Fragmented Information → Ecosystem Consistency | Do our website, experts, PR, partners and Sales tell the same story? |
| 5 | Individual Vendor Preference → Collective Decision Confidence | Can every member of the buying group justify choosing us? |
How can a marketing team check where it stands?
A useful first step is to compare how the company describes itself with how buyers and AI systems are likely to see it. These six checks give a practical starting point.
- Ask ChatGPT, Gemini, Perplexity and Claude the questions your buyers ask about your category, and record whether and how the company appears.
- Compare those descriptions with your own positioning and note where they differ.
- List the people whose expertise buyers should see, and check whether that expertise is visible under their own names.
- Read your website, sales deck, executive posts and recent PR coverage side by side, and mark every contradiction.
- Map the independent sources that validate your main claims, such as customers, partners, analysts and media.
- Review a recent lost or stalled deal and list which buying-group roles raised concerns that your content could have answered.
Frequently asked questions
What is an AI-mediated buying journey?
An AI-mediated buying journey is a B2B buying process in which AI continuously influences discovery, research, comparison, validation and decision-making. Buyers still use search, vendor websites, peers and Sales, while AI helps them frame problems, compare options and summarise information across those sources.
Does AI replace search in B2B research?
Current research shows AI working alongside existing sources. In the 6sense 2025 B2B Buyer Experience Report, 94% of buyers had used LLMs during their buying process, and human and vendor interactions remained important. A company therefore needs to be discoverable through search and correctly represented in AI-generated answers.
Why do individual experts matter for AI visibility?
Identifiable experts make company knowledge attributable to real people. In the Meltwater and LinkedIn analysis of 9.5 million AI citations, 75% of LinkedIn citations came from individual members and 25% from Company Pages. Expertise shared under a person’s name is part of the source environment AI systems can surface.
Is AI visibility the same as buyer preference?
AI visibility determines whether a company appears in AI-assisted research. Buyer preference depends on whether buyers and AI systems interpret the company correctly and trust what they find. A company needs visibility to be considered and authority to be preferred.
Where B2B competition happens now
The five shifts move a large part of B2B competition into stages that vendors rarely observe. Buyers research with AI, form preferences before contacting Sales, judge companies through many sources at once and need the whole buying group to agree before they commit. Marketing therefore has to influence how the company is understood long before an opportunity appears, and keep reinforcing that understanding after Sales joins.
If you are not sure whether your website, your experts and the sources around you tell the same story, we can help you find out. The HiFuture Authority Signals Assessment shows where your current signals support that story and where the gaps are.
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