AI isn't a confusion eliminator—it's a chaos amplifier

Five questions to get AI, strategy, and messaging aligned

I’m a lucky fellow. I sit on both sides of the AI conversation.

Sometimes I’m writing about AI tools—helping teams explain what they’ve built and why it matters. Other times, I’m inside the work itself—designing AI systems, workflows, and interfaces, and deciding what the tool should actually do for the person using it.

From both angles, the same problem shows up again and again. And it’s not new.

Years ago, I worked for Bob Hacker, a marketing legend who liked to tell a story about being interrupted while writing. Someone asked him, “Are you working on copy or strategy?”

His mildly annoyed answer: “What’s the difference?”

That line stuck with me because good copy always reflects strong strategy. And weak copy usually reveals that the strategy underneath it isn’t finished or is flawed.

The same thing is happening with AI.

Teams often treat product definition, AI behavior, and marketing message as separate problems. In practice, they’re the same problem viewed from different perspectives. When teams use AI without alignment, AI doesn’t resolve the confusion—it accelerates it. And I’ve seen it play out in everything from enterprises, to partnerships, to fast-moving product launch teams. No one is immune.

So before you ask AI to generate content, plans, structures, or tools, it’s essential to answer a few grounding questions that inform AI strategy and messaging clarity.

1. Who is the single person this AI helps first, and what job are they hiring it to do?If the answer is “marketing,” “the team,” or “everyone,” alignment hasn’t happened yet. You need to be able to envision specific use cases.

2. What decision or outcome should be meaningfully better after they use it?Don’t mistake velocity for strategy. Speed without clarity just moves confusion faster.

3. What must humans decide before AI can help—and what decisions should never be delegated to it?AI is not a substitute for unresolved strategy—and those who fail to carefully review outputs will pay downstream.

4. What does “good” look like, and who gets to say so?If no one owns quality, AI output will be endlessly regenerated instead of evaluated. Quality is a conversation—not a feature.

5.  What would confuse or disappoint the customer if this worked perfectly?That question often reveals what the product—and its messaging—aren’t ready to promise yet.

See how function and message connect? This is where AI function, product intent, and marketing message collapse into the same problem.

When teams can answer these questions clearly, AI becomes a force multiplier, and content about it can be turbocharged to drive real demand. When they can’t, AI becomes a chaos accelerator capable of pushing through tons of content with strategic holes that—as many companies are finding—can stop progress and force organization-wide repositioning.

That difference has little to do with technology—and everything to do with alignment and preparation.