“We want to use agents!” If your CEO keeps saying that, you're not alone. Many organizations are racing toward AI driven workflows and autonomous agents. But the fastest way to derail an AI transformation is to jump straight to agents and skip the foundations. Just like with traditional automation, you first need to understand the problem, the process, and the controls before you can automate it successfully.

In this session, I'll use a Service Desk case study to demonstrate the four stages of AI evolution:
1. Existing automation
2. AI assisted information retrieval
3. Controlled agent actions
4. Autonomous workflow execution

We'll use an existing PowerShell automation solution to demonstrate how AI capabilities can be layered on top of proven automation rather than replacing it. We'll explore several KPIs like the predictability, automation level, completion time, and auditability while delivering value at every stage.

Most importantly, you'll learn why the goal is not always to reach Stage 4. Each stage solves different problems, carries different risks, and requires different levels of trust and control. By understanding these trade-offs, you can choose the level of AI enablement that delivers the most value for your organization.

Join this session for a practical guide that helps you evolve real business processes with AI, one stage at a time, while keeping control of costs, risk, and operational reliability.