Ninety-one percent of marketing leaders expect their budgets to grow in 2027, according to Forrester's Budget Planning Guides, a survey of more than 2,600 business and technology decision-makers published this July. That number on its own tells you almost nothing useful. What matters is a gap that three separate research firms, working independently of each other and using different methodologies, have now each measured and arrived at roughly the same conclusion about.
Three Analyst Firms, Measuring the Same Gap Independently
Forrester's warning is that spending more without modernizing the operating model underneath it will worsen fragmented data and technical debt rather than fix anything. Gartner's own 2026 CMO Spend Survey, a separate study of 401 senior marketing leaders, puts a number on exactly that gap: CMOs allocate an average of 15.3 percent of their marketing budget to AI, but only 30 percent describe their organization's AI readiness as mature enough to actually scale it. The 30 percent who qualify, Gartner's "AI strategists," put 21.3 percent of budget toward AI and 34.2 percent toward innovation generally, nearly double the innovation spend of everyone else, and Gartner's own read on why is pointed: those companies are reinvesting efficiency gains into more marketing capacity rather than pocketing them as savings.
Boston Consulting Group measured a version of the same gap from a different angle. Its survey of 300 CMOs, backed by 50 in-depth interviews, found that only 8 percent of CMOs run campaigns where multiple AI agents operate autonomously across workflows, and fewer than a third say they've transformed any significant portion of their marketing function with agent-based systems. Forty-two percent are still using AI as an assistant for individual tasks scattered across a handful of workflows, not as anything close to a coordinated system. BCG's own conclusion is that talent development, not technology access, is the actual bottleneck, with 80 percent of CMOs now making substantial investments specifically in AI-focused workforce development to close it.
Put Forrester, Gartner, and BCG side by side and the pattern holds across all three: budgets are rising, ambition is high, and the operational foundation most companies have built underneath that ambition is thin. That convergence, three firms, three methodologies, one conclusion, is what makes Forrester's specific funding guidance worth taking seriously rather than treating as one consultancy's opinion.
Build a Smarter 2027 Marketing Budget
Fund the Knowledge Layer Your AI Agents Actually Read From
Forrester's first recommendation is building or buying a governed, machine-readable knowledge layer, the structured internal documentation, policies, and system logic that lets an AI agent navigate a business correctly instead of guessing at it. Forrester's own language is blunt: "AI agents can't act on what they can't read." This isn't abstract. Liquid Death's chief media and digital commerce officer, Benoit Vatere, described building exactly this kind of foundation at Advertising Week New York in October, running 17 iterations of a proprietary AI operating system in three weeks specifically to get the company's data organized enough for AI to act on reliably. His own description of the discipline required: "I don't want to see any spreadsheets anymore." That's a two-person team building the knowledge layer Forrester is describing, in real time, because without it the AI tools sitting on top of it have nothing reliable to work from.
Fund Visibility Where AI Answer Engines Actually Look
The second funding priority reframes what brand visibility means once AI answer engines sit between a company and its buyers. Forrester's guidance names Reddit, YouTube, and review platforms as sources that may carry more weight with answer engines than a brand's own website. Coca-Cola is already operating on exactly this logic. Speaking at the same Advertising Week event, Josh Gurley, Coca-Cola's VP of Transformation and Strategic Growth, said decades of ensuring Coca-Cola was available at every point of sale no longer guarantees visibility once an AI agent filters a catalog down to two or three recommendations. His example was specific: a product missing basic attributes like gluten-free status simply gets left out of an agent's recommendation, no matter how much media spend sits behind it. Coca-Cola's response is to enrich product and catalog data rather than buy more advertising, the same prioritization Forrester is recommending industry-wide.
L'Oréal is running the same playbook at a larger scale. Chief digital and marketing officer Asmita Dubey told Fortune this month that a search which used to take a few minutes now takes about 11, because consumers are chatting with AI rather than scanning a results page, and her response has been to standardize product data across Google and Meta specifically so AI systems can interpret it correctly. Search Engine Journal's Greg Jarboe has proposed measuring this shift with a new metric entirely, Citation Share of Voice, tracking how often a brand gets cited inside an AI-generated answer rather than how it ranks on a results page. Duke University's CMO Survey, a separate 35th-edition study of 308 marketing leaders fielded this year, found that four in 10 companies are already running some form of generative engine optimization, while no marketing technology activity in that same survey scored above a 5 out of 7 on performance, a sign that the tools exist but most organizations haven't made them work yet.
The Pricing Shift Making AI Budgets Harder to Predict
Gartner's own survey data independently confirms something Techstrong IT first flagged as industry context: 56 percent of CMOs report increasing the share of their martech spending that runs on consumption-based pricing, billed by usage rather than a flat seat license. Half of those adopting consumption-based pricing are now in continuous contract renegotiation just to avoid unexpected overages, and 41 percent have built or are building real-time oversight controls specifically to monitor that spend. GitHub's shift of Copilot to usage-based billing, OpenAI's pay-as-you-go Codex pricing, and Anthropic's subscription changes are the vendor-side version of the same pattern. The budget increase marketing leaders are planning for 2027 isn't only new investment. A real portion of it is simply the cost of keeping pace with AI tools that now bill by how much they're actually used.
Fund Structured Experiments, Cut What Isn't Governed
Forrester's guidance calls for eliminating AI pilots that lack governance, clear ownership, defined success criteria, or a realistic path to scale, rather than trying to patch them. BCG's 8 percent figure, the share of CMOs running genuinely coordinated multi-agent campaigns, suggests most marketing organizations are still well inside the territory Forrester is warning against: real investment, limited governance, and no clear path from isolated pilot to scaled system. Forrester's alternative is structured testing with defined use cases, AI agents for content production, audience generation, brand governance, and customer engagement, paired with synthetic data tested alongside real customer research rather than trusted on its own.
What This Means Heading Into Planning Season
The organizations that come out ahead in 2027 won't be decided by budget size. Gartner, BCG, and Forrester each measured a version of the same gap between AI ambition and AI readiness this year, and the companies already closing it, Liquid Death building its own data discipline, Coca-Cola and L'Oréal rebuilding their product data for AI visibility- are doing it months ahead of the planning cycle most marketing leaders are about to enter. Sharyn Leaver's framing is the one worth carrying into that cycle: "The organizations that outperform in 2027 won't be those that spend the most on AI. They'll be the ones that invest in the foundations that make AI effective."
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Sources
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BCG Report Reveals AI Adoption Gap as Most CMOs Struggle to Scale Agentic Marketing (MarTech Edge)
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2027 Marketing Budgets: Why New Categories Beat Bigger AI Line Items (Search Engine Journal)
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How Liquid Death is Building an AI-Native Marketing Organization (Marketing Dive)
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As AI Reshapes the Consumer Journey, L'Oréal Is Rethinking Its Marketing Engine (Fortune)
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Forrester 2027 budget coverage, including usage-based AI pricing context (Techstrong IT)
