Author: Greg Kihlström

A growing share of product research and buying now runs through an AI agent rather than a person. The agent reads the request, narrows the field, and hands back a few options ready to buy. The customer picks from a list someone else built.

Most brands are still optimizing for the wrong reader. The work that earns attention from a human shopper — narrative, design, persuasive merchandising — is largely invisible to the system that now determines whether the brand reaches that shopper at all. The Brand Visibility for Agentic Commerce (BVAC) Framework…

This article was written by Greg Kihlström for CMSWire. Since User Experience (UX) has been a discipline, the “user” has been synonymous with a human being for obvious reasons: humans were the consumers of software tools, websites, mobile apps and all the other experiences that fall under this umbrella.…

Are you building an organization of marketers using AI tools, or an organization of AI agents managed by marketers? This question usually earns me a few nervous laughs when I …

This article was written for MarTech by Greg Kihlström. We’re experiencing a conflict between the economic pressure to produce quick and cheap research results and the scientific demand for rigor. Hundreds, if not thousands, of lifelike personas can be generated within minutes by vendors promising strong results. But these…

The CMO’s job in 2026 is to be an AI realist, not an AI enthusiast. This means making hard decisions about where AI creates genuine competitive advantage and where it creates the illusion of progress.

This article was written by Greg Kihlström for CMSWire. In economically uncertain times, it would seem safe to assume the best way to win over customers hinges on this uncertainty. Yet, relying on price as a primary market differentiator is growing increasingly unsustainable for CPG brands. This is no…

The CMOs who will win this race are building data infrastructure, rethinking how they earn (not buy) attention, and putting governance frameworks around agentic AI before they need them, not as they are in the midst of a critical project. The gap between AI ambition and AI execution is…

Have you ever shipped an AI capability that looked great on launch day, then quietly started making your customer experience worse, one “personalized” suggestion at a time? This is the part of the AI story that rarely shows up in vendor demos. A model can be well-designed, thoroughly tested,…

The AI transformation of marketing is no longer a future-state planning exercise, but rather a present-tense organizational redesign challenge.