CEO: “Why aren’t we using AI yet?”
Data team: “We’ve been using it for years.”
Both are right. The problem is they’re picturing completely
different things.
AI isn’t one thing, though it usually plays one of three roles:
1. THE ANALYST: Traditional AI helps you predict, classify and make better decisions
2. THE CREATOR: Generative AI helps you draft, summarize and generate ideas quickly
3. THE WORKER: Agentic AI helps you execute tasks across systems with less manual effort
That distinction sounds basic. But I think it's where a lot
of organizations get stuck. They jump straight into tools before they are clear
on the job. And when that happens, expectations get fuzzy very quickly.
The other reason this matters is maturity. Traditional AI is
largely proven. Generative AI is moving fast. Agentic AI is emerging
powerfully, and still needs tight guardrails.
So the leadership challenge is both understanding what each
type can do and understanding what each type needs:
Clean data. Clear rules. Strong controls. That’s how you move from experimentation to value.
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