That playbook is now colliding with a structural shift inside the buyer's own organization.
The Boston Consulting Group (BCG) 2026 global survey of 300 Chief Marketing Officers (CMOs) reveals that this function has become one of the most consequential AI decision centers in the enterprise.
However, there's a common execution gap. It's about who has the talent to act on the AI budget. B2B CMOs are further behind than their consumer counterparts on the capability that determines Applied-AI ROI.
Why Applied-AI Practitioner Talent Matters
Nearly all CMOs, 96 percent, told BCG that AI is driving end to end transformation of their function, yet only about a third have moved beyond isolated pilots into genuine agent-led workflows.
That gap between stated ambition and operational reality is the defining tension of this year's data, and it should recalibrate how vendors read a CMO's public AI posture.
Roughly half of CMOs now say marketing itself owns AI investment decisions, compared with just 14 percent led by the CEO or board. That marks a real departure from the rest of the enterprise, where BCG's AI Radar found 72 percent of CEOs still see themselves as the primary AI decision maker.
Marketing has effectively won a mandate the rest of the C-suite has not yet ceded elsewhere. But the skilled and experienced AI talent constraint is the sharpest finding for tech vendors to supplement.
CMOs across pharmaceuticals, media, and fashion told BCG some version of the same sentence: the AI practitioner talent does not exist to recruit and hire, so they have to create it themselves.
About 80 percent of CMOs are now making significant investments in AI specific up-skilling, precisely because the external labor market cannot supply what agentic Applied-AI marketing requires.
And the B2B gap is explicit in the numbers. Only 20 percent of B2B CMOs report that their agentic marketing transformation has produced significant, measurable revenue impact, versus 31 percent of B2C CMOs.
B2B marketing organizations are moving, but they are converting that motion into results more slowly, which is precisely where a well-positioned vendor could add value, if it were speaking to the right buyer.
Outlook for Applied-AI Investment Growth
The strategic implication for B2B technology vendors is uncomfortable but clarifying. Most enterprise marketing and sales organizations -- including firms I have advised -- still build content, campaigns, and sales enablement assets aimed at the technical evaluator who influences the vendor shortlist.
That approach assumes the meaningful AI decision lives in the IT organization.
BCG's data says otherwise for an entire category of large enterprise spending.
Marketing now controls its own AI agenda, is investing at scale, with 43 percent of CMOs reporting AI marketing spend above $15 million this year, and is doing so without the internal talent to fully execute.
That combination, budget authority paired with a talent shortfall, is a gap a tech vendor's content and sales motion should be built to close. It requires speaking directly to the CMO and the marketing operating model, not routing every message through a technical champion who has no stake in the business outcome.
Vendors selling AI tooling into marketing organizations need buyer enablement assets, briefings, and even sales engineering conversations calibrated for a business decision-maker building a new operating system for their function, not for an IT buyer comparing feature checklists.
The B2B tech vendors who adjust first have the strategic advantage.
A vendor that shows up with a credible point of view on up-skilling, governance, and operating model design, rather than another AI point solution demo, will be talking to the person who actually decides.
That being said, I believe the question worth asking in every B2B vendor is simple: does your go-to-market content still assume the sale happens through the technical influencer, or does it recognize that the C-suite owns this key infrastructure investment decision?
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