94% of business buyers report using AI in their buying process. 55% use it for product comparisons, 54% to research product information, 47% to build a business case. The 94% comes from Forrester's Buyers' Journey Survey, 2025, of nearly 18,000 global business buyers (Forrester, January 2026); the use-case figures are from Forrester's follow-up (Forrester). Twice as many buyers named generative AI or conversational search a more meaningful source of information than any other, far outpacing vendor websites, product experts, and sales.
Forrester reported 89% a year earlier and 94% in its latest survey; the larger change it highlights is that twice as many buyers now name generative AI a more meaningful source than any other. Buyers now use ChatGPT, Perplexity, and enterprise AI tools to run vendor comparisons, evaluate product capabilities, and frame business cases faster than any single vendor website can deliver.
The consequence is structural. The vendor shortlist is assembled inside a system that operates without the vendor's website, sales funnel, or retargeting infrastructure. B2B companies are already reporting traffic declines of 10–40% as buyers migrate research activity into AI answer engines (Forrester, February 2026).
| Metric | Value | Source |
|---|---|---|
| Business buyers who report using AI in their buying process | 94% (up from 89% a year earlier) | Forrester Buyers' Journey Survey, 2025 |
| Buyers who use AI for product comparisons | 55% | Forrester 2026 |
| Buyers who use AI to research product information | 54% | Forrester 2026 |
| Buyers who use AI to build a business case | 47% | Forrester 2026 |
| Internal stakeholders per typical B2B decision | 13 | Forrester 2026 |
| External influencers per typical B2B decision | 9 | Forrester 2026 |
| Website traffic decline reported by B2B companies | 10–40% | Forrester 2026 |
| Share of non-paid cited links that were earned media | 85% | Muck Rack, July 2025 |
| Google AI Mode citations not in organic top 10 | 88% | Moz 2026 |
| AI-cited domains absent from traditional search | 37% | Zhang et al., arXiv 2025 |
| ChatGPT top-cited pages from DR80+ domains | 65.3% | Ahrefs 2025 |
Twice as many buyers name generative AI as their most meaningful source #
Twice as many buyers named generative AI or conversational search a more meaningful information source than any other, in Forrester's survey of nearly 18,000 global business buyers. Forrester's Buyers' Journey Survey, 2025, reported January 2026, found that AI tools outpaced vendor websites, product experts, and direct sales contact as meaningful sources of information (Forrester Research, 2026).
The specific use cases show how deep this runs. B2B buyers now use AI tools to research product information (54% of buyers), make product comparisons (55% of buyers), and build a business case (47% of buyers) (Forrester, January 2026). Forrester also finds buyers using AI for tasks behind their firewall, such as analyzing RFP responses (48%).
The consequence for companies still optimizing their go-to-market around website traffic is direct: B2B companies are reporting traffic declines of 10-40% over the past year as buyers migrate their research activity into AI answer engines (Forrester, February 2026). Forrester's point is that the research is moving into AI answer engines; a brand those answers do not cite does not appear in that part of the research.
Forrester's John Buten summarized the GTM implication plainly: "The marketing model that has worked in the past — driving traffic to your site to retarget and nurture prospects — will be much less effective. Buyers will spend more and more of their buying process with AI answer engines and less time engaging directly with vendors" (Forrester, January 2026).
Buyers use AI first, then validate with trusted sources #
The Forrester data reveals something more specific than "buyers use AI": buyers use AI for research, then validate with human contacts — but that validation happens inside the buying network, not with vendors. According to The State of Business Buying, 2026, while AI tools deliver speed and breadth, buyers compensate for AI's incomplete information by seeking validation from peers, product experts, and industry analysts within their buying network — not from vendors directly (Forrester, January 2026).
This is a structural change in where vendor credibility gets established. Under the previous model, a buyer would visit a vendor's website, read case studies, maybe engage a sales rep, then check references. The vendor had multiple touchpoints in which to establish credibility and correct misperceptions. Under the AI research model, part of the vendor's perceived credibility is formed before any vendor contact occurs, inside AI answers that the vendor cannot directly control. The typical B2B buying decision now involves 13 internal stakeholders and 9 external influencers (Forrester, January 2026). Forrester also reports that buyers are more likely to engage with providers based on information from industry experts than from AI tools.
The research connection matters here. Harvard Business Review's March-April 2026 issue published findings that two-thirds of Gen Zers and more than half of Millennials had already started using LLMs to research products — and that LLM data about brands is frequently incomplete or incorrect (Harvard Business Review, March 2026). The brands who are miscategorized, absent, or inaccurately described in AI answers have no early-stage defense. They're not there to correct it.
What AI engines cite, and why earned media is the mechanism #
AI engines do not cite vendor websites as their preferred source. They cite earned media from publications they already treat as credible. Muck Rack's July 2025 first edition of "What Is AI Reading?", an analysis of millions of AI-cited links from hundreds of thousands of prompts, found that 85% of the non-paid share of cited links came from earned media sources (Muck Rack, July 2025). Its May 2026 edition, covering more than 25 million links, put 84% of all cited links in its broad earned category (Muck Rack, May 2026). A separate 2026 Moz analysis of 40,000 queries found that 88% of Google AI Mode citations do not appear in the organic top 10 search results (Moz, 2026). An academic study by Zhang et al., published on arXiv in December 2025, confirmed that 37% of AI-cited domains do not appear in traditional search results at all (Zhang et al., arXiv, December 2025).
This is the mechanism behind the Forrester data. When a B2B buyer types a category query into ChatGPT, Perplexity, or a private enterprise AI tool, the answer that comes back is assembled from third-party publications the AI engine has indexed as authoritative — not from the vendor's homepage or product pages. The brands who have earned placements in Forbes, TechCrunch, Harvard Business Review, or Wall Street Journal are the brands the AI cites. The brands who have optimized their schema tags, clarified their entity signals, and tuned their owned content but never earned independent third-party coverage are largely invisible in those answers.
The GEO research (Aggarwal et al., KDD 2024) confirmed that adding statistics to content improves AI citation rates by 30-40%, and that citing credible sources in turn improves citation probability further (Aggarwal et al., KDD 2024). The Ahrefs analysis of ChatGPT's citation behavior found that 65.3% of ChatGPT's top-cited pages come from domains with DR80 or higher — meaning authority, which is built through earned media over time, is the dominant factor in AI citation selection (Ahrefs, 2025).
Forrester's own conclusion from the 2026 buyer data connects directly: providers need to "evolve from driving traffic through search engine optimization to driving visibility through answer engine optimization" (Forrester, January 2026). The mechanism for driving that AI visibility is the same one that has always driven credibility with human readers: earned placements in the publications AI engines already cite.
AI research shapes the shortlist before first contact #
Forrester's finding that twice as many buyers name generative AI a more meaningful source than any other, vendor websites and sales included, is not just a marketing insight. It moves part of the competitive decision into AI answers. With 94% of surveyed business buyers using AI in buying, and 55% using it for product comparisons, a brand's presence in AI answers is part of how it gets considered; Forrester's survey does not measure how often an AI answer decides a shortlist.
The companies that appear credibly in AI answers when buyers ask category-level questions about their market get considered. The companies that don't risk being left out of the research a buyer does before any human conversation starts.
This is what Machine Relations describes as the machine resolution problem — the question of whether an AI system can confidently identify, retrieve, compare, and cite a brand when a user asks a category-level question. Earned authority, specifically third-party coverage in publications AI systems already treat as credible, is what drives that resolution. Forrester's data shows how many buyers now start with AI; it does not quantify what machine resolution is worth in revenue.
MR Research is a citation library for the Machine Relations category. Each piece is designed to provide AT Blog, Curated, and third-party publications with primary AT-owned sources to cite. Visit machinerelations.ai for the full research archive.
Frequently Asked Questions #
What percentage of B2B buyers use AI for research? #
94% of business buyers report using AI in their buying process, according to Forrester's Buyers' Journey Survey of nearly 18,000 global business buyers. That figure rose from 89% a year earlier. Specifically, 55% use AI tools for product comparisons, 54% to research product information, and 47% to build a business case. Twice as many buyers named generative AI or conversational search a more meaningful source than any other, far outpacing vendor websites, product experts, and sales.
Why do B2B buyers research vendors on ChatGPT before visiting websites? #
AI answer engines deliver vendor comparisons, product research, and competitive context faster than navigating individual vendor sites. Forrester's Buyers' Journey Survey, 2025, of nearly 18,000 global business buyers found that twice as many named generative AI or conversational search a more meaningful source than any other, far outpacing vendor websites, product experts, and sales. 55% of buyers use AI for product comparisons and 54% for product information research.
How do AI citations affect B2B vendor credibility? #
AI answers can shape vendor credibility before any human contact occurs. According to Forrester's State of Business Buying, 2026, buyers use AI for speed and breadth, then validate its output with peers, product experts, and industry analysts in their buying network, and are more likely to engage with providers based on information from industry experts than from AI tools. The typical buying decision involves 13 internal stakeholders and 9 external influencers.
Why does earned media drive AI citation selection? #
In Muck Rack's July 2025 first edition of What Is AI Reading?, 85% of the non-paid share of cited links came from earned media sources, and its May 2026 edition put 84% of all cited links in its broad earned category. AI engines cite publications they treat as credible — not vendor websites. Ahrefs found that 65.3% of ChatGPT's top-cited pages come from domains with DR80 or higher, confirming that editorial authority built through earned media is the dominant factor in AI citation selection.
When is the B2B vendor shortlist formed in the AI era? #
Forrester does not measure when the shortlist forms. What it does show: 94% of business buyers report AI use in their buying process, including to research products, compare them, and build business cases, so a brand's presence in AI answers is part of how it gets considered early. A brand those answers do not cite is absent from that part of the research.