The CMO’s 2027 Decision: Lead the Commercial Intelligence System, or Risk Losing Ground on the ELT

Brian Shea
2 days ago
6 min read

"Lead, follow, or get out of the way" ~Lee Iacocca

CMOs are entering the 2027 planning cycle with more technology, more data, and more responsibility for growth than at any point in the function’s history. Yet their position on the executive leadership team may be becoming less secure, not more.

That tension is visible across several recent CMO studies. Gartner reports that marketing budgets remain at 7.8% of company revenue, 18% below their level four years ago, while 73% of CMOs describe the growth expectations placed on them as high, very high, or overly ambitious. At the same time, revenue growth is becoming a larger part of the CMO’s mandate, AI investment is accelerating, and CEOs and CFOs are demanding clearer evidence of financial contribution.

The mandate is expanding faster than the operating model.

That should concern every CMO preparing a 2027 strategy. The threat is not simply another budget reduction. The larger risk is that marketing becomes less central to how the enterprise makes growth decisions. When marketing cannot translate market change, buyer behavior, and customer intelligence into coordinated commercial action, its role can be reduced from growth leadership to campaign execution.

For CMOs, 2027 is becoming an inflection point: lead the enterprise toward a more intelligent commercial operating model, or risk losing influence within the ELT.

More technology is not producing more commercial intelligence

AI has quickly become one of marketing’s largest new investment priorities. Gartner reports that CMOs are allocating 15.3% of their budgets to AI, yet only 30% believe their organizations possess the maturity required to scale it effectively. Seventy percent say their internal marketing processes are not sufficiently mature to implement and scale AI.

Salesforce’s research exposes the same disconnect from a different angle. Although 75% of marketers report adopting AI, 84% acknowledge that they still run generic campaigns.

Marketers may have more powerful automation, but fragmented and irrelevant data continue to prevent the responsive, contextual engagement buyers increasingly expect.

This is not primarily an AI problem. It is an operating-model problem. If AI is added to a commercial system organized around disconnected campaigns, individual leads, late-stage intent, and functional handoffs, it will accelerate those same limitations. Marketing may produce more content, launch campaigns faster, and generate larger volumes of activity without materially improving when the company identifies an opportunity or how effectively it mobilizes around it.

The ELT will not indefinitely reward AI adoption as progress. It will eventually demand evidence that AI has improved revenue productivity, customer retention, market responsiveness, and the economics of growth.

Marketing is still being measured where demand is easiest to see

Under financial pressure, organizations naturally invest in activities that can be measured quickly. Gartner found that awareness and conversion now account for 62.6% of total media spending. Investment in loyalty and retention has fallen 29% since 2024 and now represents less than 15% of media budgets. Gartner also found that less AI-mature organizations may be overinvesting in channels and customer-journey stages that are easiest to automate and measure.

This creates a dangerous distortion. The marketing organization becomes increasingly efficient at capturing visible demand while remaining largely blind to where future demand is forming.

The same limitation appears in the continued reliance on MQLs, form fills, website activity, and conventional intent data. These indicators can help identify buyers who are already researching a category, but they rarely explain what changed inside the account, who is shaping the decision, whether the buying organization is aligned, or how far the buyer has progressed before becoming visible.

Traditional intent data still has value. The problem is timing. It often tells the commercial team which accounts have entered the market after those buyers have already begun defining their problem, establishing requirements, consulting trusted sources, and developing vendor preferences.

That is not early intelligence. It is improved visibility into a race that has already started.

The 95/5 problem is becoming a CMO leadership test

The LinkedIn B2B Institute’s 95/5 principle argues that approximately 5% of category buyers are in-market at a given time while the remaining 95% represent future demand. It also warns that lead-generation metrics can cause organizations to concentrate resources on the small share of buyers already shopping because those activities are easier to measure.

Many organizations have interpreted this as an argument for balancing brand and demand generation. That is important, but it does not go far enough.

The strategic question is whether the enterprise can recognize when conditions inside an account begin changing, before the account produces a conventional intent spike. Leadership transitions, new strategic priorities, capital commitments, regulatory pressures, acquisitions, expansion plans, customer problems, hiring patterns, ecosystem activity, and competitive disruption can all indicate that a future commercial decision is beginning to form.

A CMO capable of organizing this intelligence becomes more than the leader of marketing. That CMO helps the enterprise decide where to compete, when to engage, which buying organizations are forming, and how to shape demand before competitors see a formal opportunity.

A CMO who remains focused primarily on campaigns and attribution may find that those strategic decisions migrate elsewhere—to the CRO, chief growth officer, strategy function, data organization, or an AI transformation leader.

Signal‑Led GTM™ changes the CMO’s position

Signal‑Led GTM™ is not a new label for intent data or account-based marketing. It is a commercial operating model built around detecting consequential change, interpreting its commercial meaning, and coordinating the appropriate enterprise response.

Traditional demand generation asks, “Who responded?”

Conventional intent asks, “Who appears to be researching?”

Signal‑Led GTM™ asks, “Where is meaningful change occurring, what decision could it create, who will influence that decision, and what should we do before the opportunity becomes obvious?”

That distinction moves the CMO upstream. Marketing becomes responsible not only for generating demand but also for strengthening the organization’s ability to recognize and act on emerging demand. Market intelligence, account signals, buyer research, customer insight, product feedback, stakeholder movement, and ecosystem activity become part of one shared commercial intelligence environment.

The CMO is then positioned to help sales secure earlier access, help product understand emerging market needs, help customer success detect expansion and churn conditions, and help the CEO allocate resources toward opportunities with stronger evidence of future value.

This is a more consequential contribution than increasing MQL volume. It is also far more defensible within the ELT.

The metrics must change with the mandate

CMOs cannot claim a broader commercial role while continuing to rely primarily on marketing-sourced pipeline, lead volume, cost per lead, and attribution models designed around recorded touchpoints.

Those measures can remain, but they are insufficient for a Signal‑Led GTM operating model. The 2027 CMO scorecard should also answer:

Did we identify material account changes before competitors?
Did earlier intelligence improve access to executive stakeholders?
Did we enter buying conversations before requirements were fixed?
Did we improve conversion by prioritizing accounts with stronger signal evidence?
Did we shorten the time between market change and commercial action?
Did customer intelligence expose expansion or retention risk earlier?
Did marketing intelligence influence product, account, or investment decisions?
Did our commercial teams take coordinated action—or merely receive more alerts?

These questions connect marketing to decision quality, resource allocation, and revenue outcomes. They also shift the executive conversation from defending marketing activity to demonstrating commercial advantage.

Waiting until 2027 will be too late

A Signal‑Led GTM transformation cannot begin with the purchase of another data platform or the creation of an AI task force. It requires agreement on which signals matter, how those signals are interpreted, who owns the response, and how coordinated action occurs across marketing, sales, customer success, product, and executive leadership. That design work must begin before 2027 plans and budgets harden.

CMOs should enter the coming planning cycle prepared to make four changes.

First, define a signal architecture that extends beyond engagement and traditional intent data.
Second, create a Day 1 List of accounts where consequential change is occurring, including accounts that are not yet displaying conventional buying behavior.
Third, replace functional handoffs with explicit signal-to-action governance across the commercial organization.
Finally, establish executive measures that connect earlier intelligence to conversion, velocity, expansion, retention, and resource productivity.

The urgency is not based on the prediction that marketing will disappear. Marketing will remain essential. The question is whether the CMO will continue to lead it as an enterprise growth function or watch it become a narrower execution capability operating beneath another executive’s commercial mandate.

The research is sending CMOs a clear signal of its own. Budgets remain constrained. Growth expectations continue to rise. AI investment is running ahead of organizational maturity. Traditional demand channels are becoming less reliable. Buyers are becoming harder to observe, and the ELT is demanding stronger evidence of financial contribution.

The CMO who connects those conditions will recognize the opportunity: become the architect of the company’s commercial intelligence system.

The CMO who does not may discover that the 2027 organizational chart reflects a decision the ELT has already made.