My Guide to AI Maturity
Let’s be honest: a lot of organizations right now are playing with GenAI like it’s a new espresso machine. Everyone’s excited, no one read the manual, and somehow IT’s getting blamed when someone accidentally emails ChatGPT their quarterly earnings report.
This isn’t a dig. It’s just where we are.
But as the novelty wears off and the stakes get higher, we need to stop asking, “Are we using GenAI?” and start asking, “Are we actually ready for this?”
Because here’s the truth: deploying a chatbot isn’t the same thing as having a GenAI strategy. Copying and pasting prompts from Reddit is not a prompt governance framework. And feeding your proprietary data into a public LLM is… well… a good way to meet your new friends in Legal.
The Real Problem: No One Knows What “Ready” Looks Like
In cybersecurity, we’ve got maturity models. Controls. Tiers. A shared understanding of what “good” looks like. It’s not perfect, but at least it’s something.
In AI? We’ve got vibes. “We’re doing some really interesting stuff with GenAI,” someone says, vaguely. What does that mean? No one knows. But there's definitely a slide deck.
This is why I think it’s time we got serious (and maybe a little structured) about AI and GenAI maturity. Not to ruin anyone’s fun — but to make sure that all this innovation doesn't melt down into risk, rework, or regret.
Here’s a Sanity Check: Six Domains That Actually Matter
If you want to figure out whether your organization is making real progress with GenAI — or just flirting with it over a glass of AI Pinot Noir — these six areas are a good place to start:
Strategy & Leadership Do the people at the top know what GenAI is, what it’s for, and what success looks like? Or are we still at “we should probably be doing something with that AI thing”?
Technology & Platform Readiness Can your systems actually support secure, scalable GenAI usage? If deploying an LLM means emailing an Excel file to an intern, the answer is probably no.
Data Quality & Accessibility Is your data clean, well-labeled, and accessible? Or is it a digital junk drawer where even the AI is like, “I’m not touching that”?
Governance, Risk & Ethics Do you have guardrails? Prompt logging? IP policies? Or is your GenAI policy just “don’t do anything weird”?
Workforce & Organizational Readiness Are employees trained? Do they know a good prompt from a bad one? Or are they quietly hallucinating their way through expense report summaries?
Value Realization Are you measuring actual outcomes? Or just adding “AI-powered” to things that were already working fine?
Maturity ≠ Boring. It Means You’re Taking This Seriously.
This isn’t about slowing down. It’s about growing up.
Mature doesn’t mean bureaucratic. It means you’ve thought things through. It means the right people are involved. It means you can scale what works, fix what doesn’t, and avoid the kind of GenAI incident that ends up as a case study in someone else's webinar.
Because GenAI isn’t just another IT project. It’s a cross-cutting capability that’s going to reshape how your organization thinks, learns, and serves people.
And the winners won’t be the ones who move first. They’ll be the ones who move wisely.