As organizations rush to build AI agents and automate decision-making, one critical question is often overlooked:

👉 Are the underlying processes ready for AI?

Agentic AI systems don’t just execute tasks; they interpret, decide, and act based on the structure of your processes, data, and rules. When those foundations are unclear or inconsistent, AI doesn’t fix the problem; it scales it.

This session introduces Process Maturity Assessment (PMA) as a foundational step for successful Agentic AI implementations. Instead of starting with models, tools, or frameworks, we focus on what must be true before AI can deliver value.

Through practical examples, we will explore how PMA helps:

1. Identify gaps in process logic, exception handling, and decision-making
2. Align stakeholders on how work actually flows (not how it is assumed)
3. Structure data and rules for reliable AI-driven outcomes
4. Define what should, and should not, be automated

You’ll see how process maturity directly impacts the effectiveness, reliability, and scalability of AI agents across use cases.

This session is designed for builders, architects, and decision-makers who want to move beyond experimentation and ensure their AI initiatives are grounded in operational reality.

Key takeaways:

1. Why Agentic AI fails on immature processes
2. What “AI-ready processes” actually look like
3. How to apply PMA before building AI solutions
4. Practical ways to de-risk AI implementations