Everyone's excited about AI agents right now—and with good reason. They can handle real work, automate the boring stuff, and free up teams in ways we haven't seen before. But like any big tech shift, there's a part of the conversation that doesn't always get enough attention. In this case, it's governance.
Governance isn't flashy. It doesn't make headlines, but it's absolutely critical if you want your AI initiatives to actually succeed. From my years in tech and leadership, I've learned something important: innovation without structure can cause more headaches than it solves. A system that can act on its own deserves clear boundaries and well-defined responsibilities.
Key Questions Every AI Deployment Should Ask
- What decisions can this system make — and what should be off-limits?
- What data does it actually need — and what should never touch it?
- How will we monitor its behavior, accuracy, and outcomes?
- Where and when should humans step in if something feels off?
This isn't about slowing down progress or adding red tape. It's about making sure the AI you bring in actually lifts the business instead of complicating it. When governance is done correctly, it fosters trust — both within your team and with your clients. Governance lets you scale faster with confidence.
Put simply: rules and structure aren't constraints here. They're enablers.
If your team is starting with AI agents and you want a practical, no-nonsense framework to get started, I'd be happy to share what I've been using with leadership teams. Sometimes clarity is the single most valuable starting point.
Question for You
What's the biggest challenge you've seen with AI governance — culture, tools, or ownership?