Beyond hours saved: Building the business case for agentic automation

What happened

Beyond hours saved: Building the business case for agentic (AI that carries out multi-step tasks rather than answering one question) automation, AWS Machine Learning Blog announced. The RPA-era ROI model misses most of the value agentic automation creates. Agentic automation, software that reasons and adapts to complete tasks, is showing up on AI center of excellence (AI CoE) roadmaps.

But the standard way companies justify automation investments, hours saved times labor cost minus build cost, was designed for rule-based tools like robotic process automation (RPA). That model misses most of the value agents create.

You will learn why the RPA-era ROI model falls short, how to measure the value it misses, and which workflows are worth automating with agents. Why the traditional business case falls short The classic return on investment (ROI) model was built for stable, high-volume, rule-based work: count the transactions, measure the minutes, multiply by a loaded rate, subtract the build cost.