AWS proposes a new ROI model for agentic automation
What happened
On 7 October 2026, the AWS Machine Learning Blog published a post proposing the Agentic Value Model for assessing the business value of agentic automation. The post argues that the ROI model common in the RPA era — hours saved × labour cost − build cost — has gaps, omitting dimensions such as exception handling, decision quality, resilience to change and value realisation. The framework cites McKinsey's "1:3:5 pattern": for every $1 invested in agentic technology, $3 must go to process redesign and $5 to capability building and adoption. The framework is still at the methodology stage, and the report gives no specific enterprise deployments or quantitative results.
Written by AI from the reports · updated 8 d ago
Timeline
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- AWS Machine Learning BlogBeyond hours saved: Building the business case for agentic automation
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 first.
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