Change Management When Implementing AI in Traditional Industries
Getting buy-in from skeptical teams and what actually drives adoption
Expert mode marketing technology, AI, and customer experience articles for marketers and other professionals from The Agile Brand Guide®.
Getting buy-in from skeptical teams and what actually drives adoption
The ground is shifting from a world where consumers browse a list of ten blue links to one where they receive a single, synthesized answer. This transition to what some call “Answer Engine Optimization” (AEO) isn’t just an incremental update; it’s a fundamental rewiring of product discovery. As Kimberly Shenk, a career data scientist and CEO of Novi, points out, this new paradigm demands a complete overhaul of how we think about brand visibility, data integrity, and competitive advantage. The question is no longer simply “How do we rank?” but “How do we become the definitive, trusted answer an AI agent selects on a consumer’s behalf?”
If you don’t own evaluation, you don’t own outcomes. You own activity,
which looks great right up until it doesn’t. Vendor dashboards and “model
quality” metrics are not the same thing as operational performance across
real workflows.
Carrier price hikes are quietly squeezing margins, and small e-commerce businesses can’t afford to ignore the impact.
As we enter 2026, we find that, while traditional gifting remains important, how we shop for love has changed, and it says as much about our emotional intelligence as it does our need for convenience.
For many enterprise marketing leaders, the reality on the ground feels less like a revolution and more like a series of expensive science fairs. Ambitious projects, meant to redefine the customer experience, often stall out in the pilot phase, never to see the light of day. The graveyard of promising AI proofs-of-concept is getting crowded, and the return on investment remains stubbornly elusive.
In a digital-first world where speed and efficiency often take center stage, the real opportunity for brand loyalty isn’t in making things faster. It’s in making them feel different. That’s where small, unexpected moments come in—the kind of gestures that aren’t scripted, but still say, “We see you.”
The more profound, and frankly more interesting, shift is not in using AI to make ads, but in learning how to advertise within AI itself—specifically, within the conversational interfaces that are rapidly becoming the new front door to the internet for millions. This is uncharted territory, a frontier where the old rules of interruption and impression-based value simply do not apply.
AI can generate and optimize ads at scale, but human strategy, brand guidance, and emotional insight remain essential to ensure campaigns connect and perform.
Personalization is what you infer. Customization is what customers choose. If you want durable engagement, treat preferences as a first-class product surface, not a settings page nobody trusts.