Agentic automation doesn’t ask for permission. That’s exactly what makes it risky without the right testing framework.
Unlike traditional automation, agentic AI makes decisions, triggers downstream actions, and modifies ERP data – autonomously. When it works correctly, the productivity gains are significant. When it doesn’t, the failures are fast, compounding, and difficult to trace.
Most enterprises deploying agentic automation in JD Edwards environments are doing so without testing infrastructure designed for autonomous behaviour. They’re using QE frameworks built for rule-based processes – and discovering the gaps only after something breaks in production.
In this eBook, you’ll learn:
- Why traditional QE models are not designed for agentic AI – and where the gaps appear
- The specific failure modes that autonomous automation introduces in ERP environments
- How to identify whether your current testing approach can handle agentic behaviour
- What a robust QE framework for agentic automation actually looks like – and how ITC builds it
Download this eBook before your agentic automation deployment becomes an enterprise risk event.