Summary A cluster of 2026 research from Iterable, BCG, Grant Thornton, McKinsey, and PwC points to the same underlying issue across marketing organizations: the barrier to using AI more fully isn't the technology, it's ownership. Most teams have the tools to move faster, personalize more precisely, and act on data in real time. What's missing is a clear answer to who's accountable when a decision goes live. Closing that gap, one named owner per decision, is what separates org

A closer look at the structured data, protocols, and payment rails building the two sides of the agentic web, and why both run deeper than a single file or standard. This one runs more technical than most of what I write. That's deliberate. The shift underway here touches how trust and transactions get built into the web itself, and it's still early. Every protocol named below is a draft, a trial, or a first-year rollout. None of this is settled, and the map will keep changin

Marketing teams have solved the visibility problem. Most now agree on which metrics matter. What's still unresolved is what happens the moment a number arrives, because without an agreement made in advance, every result becomes a fresh argument. Two real client engagements, a luxury vacation rental company and a home organization systems company, show what changes when a number has to earn trust before it gets acted on, rather than after.

AI Marketing Infrastructure Isn't Enough. Here's What's Missing. McKinsey just published a piece on AI capabilities reshaping marketing and I read it the way I read most major research, looking for where it confirms what practitioners are already seeing and where it surfaces something worth paying attention to that isn't already in the conversation. This one did both. The confirmation: Ninety percent of CMOs are experimenting with AI across their marketing workflows and fewer