Beyond hours saved: Building the business case for agentic automation
RPA's ROI math breaks on agents. AWS gives practitioners a framework to value exception handling, decision quality, and maintenance — not just hours.
Why it matters
Practitioners and AI center of excellence leaders need a new business case model for agentic automation that captures value sources RPA metrics miss: exception handling quality, decision velocity, and ongoing maintenance costs. This AWS guide operationalizes how to size and prioritize agent workflows differently than legacy automation.
The key facts
5 to knowFramework extends ROI model beyond time savings to exception handling, decision quality, maintenance economics
Targets AI center of excellence leaders and workflow prioritization decisions
Published October 7, 2026 — agent deployment maturation phase
AWS-authored guidance, not independent validation
No pricing, deployment data, or measured outcomes provided
Go to the source
AWS Machine Learning Blogaws.amazon.com
Publisher excerpt: The RPA-era ROI model misses most of the value agentic automation creates. This post gives AI center of excellence leaders a framework to size the full value of agents across time savings, exception handling, decision quality, and maintenance economics, and to prioritize which workflows to automate…