5 B2B Marketing Predictions for 2027

B2B buyers are beginning to do more of their early research inside AI tools, and that changes what marketing teams can see. A buyer can ask an AI assistant which vendors to consider, compare several options, get a rough sense of pricing and arrive at a shortlist before visiting a single vendor website. From the marketer's perspective, very little may appear to have happened. There may be no form fill, no content download and no unusual change in site traffic.

This behavior is already common. Forrester's Buyers' Journey Survey of nearly 18,000 global business buyers found that 94% used AI during their buying process. Gartner's 2026 buyer research found that 67% of B2B buyers prefer a purchase with no sales rep, while 69% still contact a sales rep to validate information generated by AI.

The underlying problem for marketing is straightforward. Buyers are still researching, comparing vendors and forming preferences, while much of that activity may never appear in the systems marketers use to measure demand. For more than twenty years, B2B marketing has relied on observable actions such as website visits, downloads, form fills, email responses and attributed pipeline. As more research moves into AI assistants and other channels that marketers cannot observe directly, those measures describe a smaller share of the buying process.

In 2027, that gap will begin to change how B2B marketing is measured, where budgets go and which work marketing teams are expected to own. Here are five predictions.

Lead volume stops being a KPI

By December 2027, lead volume will be a diagnostic number rather than a board-level number. A B2B marketer who starts a quarterly business review with MQL counts will be reporting on a marketing process rather than overall market demand.

B2B marketing has often proved its value through measurable engagement. Forrester's research shows that eight of the top 12 criteria leaders use to evaluate B2B marketing depend on proof that a buyer interacted with a marketing asset. Marketing-sourced pipeline, marketing-influenced revenue and lead volume all require some record of buyer activity.

AI search reduces the amount of activity that marketers can observe. Forrester reports conversations with marketing leaders who have seen declines of 20% to 30% in web traffic and, in some cases, demand volume. At the same time, 90% of B2B marketing leaders now treat AI visibility as an investment-level priority or higher.

That creates a basic measurement problem. Marketing teams will spend more time trying to influence buyers before those buyers visit a website, submit a form or identify themselves, and that work can affect buying decisions without creating a record inside the marketing automation system. A company can therefore report strong lead metrics while becoming less visible during the buyer's research process.

Forrester is especially relevant because it acquired SiriusDecisions in 2019. SiriusDecisions helped establish the demand waterfall model used by many B2B teams, and Forrester now argues that current accountability models need to change as more buyer activity becomes difficult to measure.

The practical response is to keep lead volume while reducing its importance in executive reporting. Buying-group coverage, visibility across major AI answer systems and self-reported first source can provide additional evidence that traditional engagement data misses. Asking new opportunities how they first learned about the company is imperfect, but it captures information that no web analytics system can recover from a zero-click research process.

Companies that continue to optimize primarily for lead volume will spend more money improving a process that represents a smaller share of buyer activity.

Experts get their own budget line

In 2027, named subject-matter experts will produce more commercial value than many brand-owned channels, and B2B budgets will begin to include specific funding for them. These experts are likely to include engineers, product managers, technical specialists and editors.

Forrester's State of Business Buying, 2026 found that a typical buying decision now includes 13 internal stakeholders and nine external influencers. Buyers increasingly use AI during research, then validate what they find with peers, product experts and analysts.

That behavior gives identifiable experts more value. A company expert with a recognizable name can appear in articles, videos, podcasts, conference sessions and specialist publications, giving buyers a person whose expertise they can evaluate and associate with the company.

There may also be a benefit in AI search. Digiday reports that brands are using niche news creators as an earned-media source, and quotes an agency director who connects this activity with citations inside LLM responses. A named expert can therefore support both human trust and AI visibility.

In practical terms, companies should choose several people with useful expertise and give them editorial support, distribution support and a specific budget. The goal is to publish useful material under their names and place them in external channels where buyers already spend time. Companies that leave all of this activity inside corporate accounts will make it harder for buyers to find and evaluate the people who know the most about their products.

Spec pages become a marketing responsibility

In 2027, machine-readable product information will become a more important marketing asset. Marketing teams will take more responsibility for specification tables, comparison pages, compatibility data, implementation details and pricing information, while gated PDFs will become less useful for information that buyers need during product research.

Gartner forecasts that AI agents will handle $15 trillion in B2B purchases by 2028. The exact dollar estimate may prove wrong, but the operational requirement is clear: systems that compare products need accurate information in formats they can retrieve and understand.

Buyer behavior points in the same direction. Forrester found that more than 60% of business buyers now use a trial to reduce risk. Buyers want to confirm product claims and understand how a product works, what it supports, what it costs and how it compares with alternatives.

That makes detailed product information more important as marketing content. B2B marketers have spent years using forms to identify buyers before giving them access to useful material, while AI-mediated research makes that approach less effective when the information is necessary for product comparison.

The practical response is to publish price ranges where possible, create comparison tables, publish compatibility and specification information as structured text on webpages and keep product feeds current. Important product information should live on pages that search engines and AI systems can access rather than only inside PDFs.

Marketing does not need to own every product database, but it does need responsibility for whether buyers can find and understand the information. Companies that leave important product details inaccessible, incomplete or outdated will give buyers and AI systems less information to work with than competitors that publish it clearly.

Brand budgets increase, then decrease

B2B brand spending will increase during the first half of 2027 and get cut during the second half. The main reason will be weak measurement.

The increase is already visible. Marketing Week's State of Brand in B2B survey, published in September 2026, found that 58.4% of B2B firms increased their focus on brand building during the previous 12 months.

The same survey shows why those budgets are vulnerable. Long-term strategy is the main focus for only 8.5% of B2B firms, while 29.7% focus on targets that need to produce a return within six months. Brand spending may be rising, but many companies still judge marketing on a much shorter time horizon.

Gartner provides the second part of the argument. A survey of 426 senior marketing leaders found that 84% of companies had weak brand measurement systems. Gartner describes a recurring pattern in which companies underfund measurement, fail to show clear impact, lose executive support and then reduce brand budgets.

Those trends point toward a reversal during 2027. Marketing leaders will increase brand spending because buyers form preferences earlier and often before they contact sales. Later in the year, executives will ask for evidence that the spending produced results.

Many marketing teams will have weak evidence because the same changes that increase the importance of brand also reduce the amount of measurable engagement. The practical response is to set up brand measurement before increasing the budget, using regular brand tracking, share of search, geographic or segment holdouts where possible, and a clear definition of what evidence will be used to judge the investment.

Without that preparation, brand spending that increases early in the year is likely to face cuts later when the marketing team cannot show enough evidence of impact.

Execution beats another technology purchase

In 2027, B2B companies will get more growth from making their existing channels accurate and consistent than from adding another tool to the marketing technology stack.

McKinsey's tenth Global B2B Pulse Survey covers nearly 4,000 decision-makers in 13 countries. McKinsey found that buyers use an average of ten channels during a purchase, and that inconsistent information and poor access to knowledgeable support are leading reasons buyers change suppliers.

That matters because most B2B companies already have the basic digital infrastructure buyers expect. E-commerce, chat, sales outreach, websites and AI tools are common. The advantage comes from making those systems work together and present the same information.

A buyer should receive the same price, lead time, product description and implementation requirements from the website, sales team, reseller, chatbot and AI answer system. If those answers differ, the buyer has more work to do and has less confidence in the supplier. Conflicting information can also reduce the quality of AI-generated comparisons because those systems have no single reliable answer to use.

The practical step is simple: choose the ten questions buyers ask most often and compare the answers across the website, sales team, channel partners, chatbot and public AI systems. Fix the discrepancies before adding another platform.

Companies that fail to do this will continue to lose some buyers because their own channels provide inconsistent information during the purchase process.