AI Is Reshaping What CMOs Need From Their Agency Partners

PMG has long operated on the premise that the biggest constraint on business performance is how organizations act on intelligence, not how much of it they accumulate. In a recent letter to customers and partners, and in a conversation with The Wall Street Journal, PMG CEO and Founder George Popstefanov laid out the argument plainly. Most organizations were built for specialization. Teams optimize within their own lanes, on their own timelines, with their own tools, while insights get produced in one part of the business and never reach the people making decisions in another. AI accelerates the creation of intelligence, but without the organizational infrastructure to move that intelligence into action, the gap between knowing and doing keeps widening. That gap is where competitive advantage is actually won or lost.

A new Forrester report arrives at a similar conclusion from a different angle. CMOs' AI Imperative Demands Change-Agent Agencies, first unveiled at PMG's AI & Tech Sandbox at Cannes 2026, argues that as AI reshapes the economics of marketing execution, CMOs are being asked to do something considerably harder than deploy technology. They're being asked to lead organizational transformation, and most of their agency partners aren't built to support that.

For brands, the question has shifted. Today, adopting AI is largely a given, as the harder work is structuring the organization to turn AI-generated intelligence into coordinated action, and finding partners who understand what that actually requires.

What Brands Actually Need

Organizations are increasingly looking for partners—change agents—who can help them integrate AI into how their businesses operate, not just into how their marketing runs. They need support navigating adoption, governance, and organizational design. Figuring out what AI can do is rarely the challenge anymore. Instead, identifying how the organization should be structured around AI is an enterprise problem, and most agency relationships weren't designed with that scope in mind.

PMG has been building toward this kind of partnership for years, placing engineers directly inside customer organizations as product leaders and automation builders, connecting strategy, activation, and measurement within a single operating model. Popstefanov's argument in the WSJ piece is that when data, people, and technology remain fragmented, AI tends to accelerate existing dysfunction rather than resolve it. Alignment has to be engineered in from the start, and that's a fundamentally different ask than deploying a tool.

Forrester also names the measurement question. For decades, agency value has been tied to labor via hours billed, resources deployed, and team size. As automation reduces the effort required to complete many marketing activities, the basis for that math is changing, and agencies face real pressure to demonstrate value in terms of what the work actually produces. PMG's commercial model has been structured around business performance for years. Customers care most about outcomes, and that's what the relationship should ultimately be accountable to.

The Broader Case

What the Forrester report ultimately validates is something brands should be asking of themselves. The organizations that compound advantage in the AI era will be those where intelligence moves quickly from insight to decision, where shared context replaces siloed reporting, and where technology is embedded in the operating model rather than added on afterward. And those conditions don't emerge from software purchases but must be built.

Agency partners capable of supporting that kind of work will look different from traditional ones—bringing together technology, strategy, data, and engineering as an integrated system. The relationship starts to look less like a vendor arrangement and more like building something truly unique, together.

That's the model the Forrester report points toward, and is also what PMG has been doing since before the report existed to validate it.