The AWS Machine Learning Blog argues that the return-on-investment models used during the robotic process automation (RPA) era fail to capture most of the value that agentic automation can generate. The post offers AI center of excellence leaders a framework for assessing the full value of agents.
According to the description, the framework measures value across four dimensions: time savings, exception handling, decision quality, and maintenance economics. It also provides guidance on prioritizing which workflows to automate first.
Why it matters
As organizations adopt AI agents, relying on legacy ROI calculations may undervalue their impact. A structured framework could help leaders justify investments and set priorities more accurately.
Who should care
The post is explicitly aimed at AI center of excellence leaders responsible for building the business case for agentic automation within their organizations.