From Cloud to Copilot: What we must remember as we enter the Age of AI Agents

We’ve seen this before. A shift that looked like a tech upgrade.. but turned out to be a complete rethinking of how we work. A decade ago, we moved to the cloud. We thought we were just relocating files. But we ended up redesigning everything. We had to rethink governance. We had to redefine roles. We had to retrain people. We had to rebuild trust in systems we no longer physically controlled.

Many of us underestimated it.

We assumed it was about infrastructure. But it was about transformation. And now, we’re standing at the edge of an even bigger shift. This time, it’s not about where work happens. It’s about how work happens.. and who is doing it.

AI Agents are not just smarter assistants. They don’t wait for instructions. They don’t just suggest. They reason. They act. They execute.

You give them an outcome.. they figure out the path. They write your summary, analyze your KPIs, schedule the prep meeting, and draft the deck. And they do it while governed by enterprise policies, provisioned with Entra ID, and embedded in your workflows like a digital team member.

Let’s be clear: We’re not just enabling automation. We’re hiring autonomous digital workers. And just like with the cloud, the real impact is not in the tool.. it’s in the operating model.

What the Cloud Taught Us.. and Why It Matters Now

We learned the hard way that change always looks smaller than it is. Remember when “just use SharePoint” turned into 18 months of change management? When IT rolled out tools, but no one knew how to use them? When we realized that transformation doesn’t come from technology.. it comes from design?

Those lessons are more relevant than ever.

1. You can’t adopt what you don’t understand. In the early cloud days, lack of training slowed everything down. Now, if we don’t explain what agents do, what they shouldn’t do, and why they matter.. we risk losing control of the narrative and the results.

2. Structure beats intention. Tools don’t create transformation. Design does. If you want impact from AI, define where agents live, who governs them, how decisions are made, and how success is measured.

3. Autonomy needs accountability. AI agents don’t just store or suggest.. they act. And actions need oversight. Who owns the outcome? Who defines the limits? Who audits the trail?

This isn’t just about “securing AI.” It’s about building accountability by design.. observable, responsible, and aligned with your strategy.

4. It’s not about tools. It’s about trust. Transformation only happens when people believe in it. Just like we once asked: “Can I trust the cloud?” We now ask: “Can I trust this agent to act on my behalf?”

That trust must be earned.. through transparency, clarity, and communication.

Strategy: Now or Never

This shift won’t wait. And AI won’t politely ask for permission to change how work is done. Leaders have a choice: Experiment in silos.. or redesign their business intentionally. That means revisiting role design, workflow architecture, agent responsibilities, governance models, and cross-functional collaboration.

This is not an IT topic. This is a boardroom topic. This is your future workforce.

And the strategy you build today will define your competitive edge tomorrow. We are not just integrating AI. We are re-architecting work. That calls for agents provisioned like employees, governed with enterprise policies, embedded in real workflows, and continuously learning to deliver business value.

It’s not about adopting fast. It’s about building right.

Final Thought: Lead the Shift, Don’t Wait for It

The shift to cloud showed us: Those who wait fall behind.

The shift to AI? It’s faster. It’s bigger. And it’s even more defining.

So don’t just ask what AI can do. Ask what you want it to do. And design the future accordingly.

Because the biggest risk right now? Acting like nothing is changing.

Femke