Forrester Projects Ungoverned AI Will Cost B2B $10 Billion This Year. Governance Is Now a Revenue Strategy.

For most revenue leaders, AI governance has lived in the same mental bucket as data privacy training and expense policy updates. Necessary, boring, someone else's job. Forrester's latest B2B predictions argue that filing it there is about to get very expensive.

In its 2026 B2B marketing, sales, and product predictions, the research firm projects that B2B companies will lose more than $10 billion in enterprise value this year because of ungoverned generative AI. The figure covers the fallout from AI incidents, counted in declining stock prices, legal settlements, and fines, driven by what Forrester describes as an explosion of new and untested generative AI functionality colliding with employees who have not been trained to use it well.

The prediction lands at a moment when go-to-market teams are under enormous pressure to ship AI into everything: chat on the website, AI-assisted outreach, generated content, automated quoting. Forrester's warning is that the speed of that rollout has outrun the controls around it, and buyers are already feeling the difference. The firm found that 19% of buyers using generative AI tools in their purchase process feel less confident in their decisions because of inaccurate or unreliable information those tools produced.

Read that stat again from the seller's side. Nearly one in five AI-assisted buying journeys now ends with a buyer who trusts the process less, and much of the bad information poisoning those journeys is coming from vendors' own ungoverned AI output. That is not a compliance problem. That is a pipeline problem.

Why the old governance playbook fails here

Forrester's more uncomfortable finding is that the way most companies are responding does not work. Organizations are applying the governance practices built for internally developed software, centralized review boards and top-down policy documents, to commercial AI applications that marketing, sales, and product teams adopt on their own, often faster than IT can catalog them. Those top-down approaches, the firm argues, are inadequate for how generative AI actually spreads through a revenue organization.

The alternative Forrester prescribes has two parts: raise what it calls the AI intelligence quotient of employees, meaning practical skill in judging and using AI output, and democratize governance so the people closest to the tools share responsibility for using them safely. Sharyn Leaver, Forrester's chief research officer, framed the stakes in commercial terms rather than legal ones, saying that <a href="https://www.businesswire.com/news/home/20251028458309/en/Forresters-2026-B2B-Marketing-Sales-And-Product-Predictions-B2B-Companies-Will-Lose-More-Than-$10-Billion-Because-Of-Ungoverned-Use-Of-Generative-AI">"accountability and clarity will be the cornerstones of competitive advantage"</a> for B2B leaders in a volatile market.

The trust math that makes governance a revenue play

The reason governance now belongs on the revenue agenda, not just the risk register, is that buyer trust has become the scarce resource in AI-mediated deals. Gartner's recent buyer research points the same direction: 51% of B2B buyers say they are more likely to encounter misleading information from generative AI, and 69% want a human sales rep to validate AI-generated insights before they act on them. Buyers are arriving skeptical. The vendors whose AI output holds up under that scrutiny convert; the ones whose chatbots hallucinate pricing or whose AI-generated content contradicts the rep get filtered out early, often without ever knowing why.

Forrester's related predictions sharpen the point. The firm expects human expertise to rival generative AI in appeal as buyers seek validation, noting that 30% of buyers treated AI tools as a meaningful interaction at the final commit stage in 2025, against just 17% who said the same about product experts. It also predicts that one in five B2B sellers will be pulled into agent-led quote negotiations this year, with AI buyer agents demanding responses from seller-controlled agents in real time. Every one of those automated exchanges is an exchange your team does not manually review. If the AI on your side of the table is ungoverned, you are negotiating blind.

What revenue leaders should actually do

The data points to three moves. Start by inventorying the AI already touching your buyers, because most revenue organizations cannot list every AI-generated touchpoint in their funnel, which means they cannot audit what those touchpoints are claiming. From there, put accuracy standards on commercial AI output the same way you put them on pricing and legal language, with named owners in marketing, sales, and product rather than a distant review committee. And train for judgment, not just usage. Forrester's AI intelligence quotient framing is a useful one here: plenty of sellers can prompt a tool, but far fewer can tell when the output is wrong.

Practitioners who deploy AI inside live sales motions have converged on a similar rule. memoryBlue, the global sales acceleration firm, built its AI sales playbook around deciding explicitly where AI belongs in the process and where it does not, which is governance by another name: a documented, deliberate boundary instead of an accidental one.

The companies that get this right will not experience governance as a brake. In a market where buyers distrust roughly half of what AI tells them, being the vendor whose information reliably checks out is a differentiator competitors cannot copy overnight. The $10 billion Forrester is forecasting will not be distributed evenly. It will be paid by the companies that treated governance as paperwork, and collected by the ones that treated it as a sales advantage.