AI pilots stall before production at a predictable rate. The technology works. The architecture doesn't. Specifically, the design for where the AI runs and where the deterministic process takes over.

That line separates a governed deployment from a compliance event.

This session gives you a framework to draw it. You'll learn to map your processes across a stakes-vs-complexity quadrant, identify which of five automation types fits each scenario, and assess which of four agent autonomy levels your regulated environment can actually support.

​​​​​​​We close with a live demonstration of IBM BAW and watsonx Orchestrate on a governed invoice-to-pay workflow.

You'll leave with:

• A seven-dimension decision framework that matches workflow scenarios to the right automation type: deterministic workflow, decision automation, document AI, RAG assistants, or AI agents

• A method to locate your processes on the stakes-vs-complexity quadrant and determine the correct automation posture

• Criteria for evaluating agent autonomy levels against your compliance and operational risk thresholds

• Human-in-the-loop and audit logging patterns that hold up under regulatory scrutiny

• KPIs tied to cycle time, unit cost, capacity, quality, and control strength

• The Agentify Readiness Assessment to determine whether your initiative has what it needs to move from pilot to production 
  

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Originally posted on 2026-05-19 in the IRPA AI Network — Enterprise AI