Beyond hours saved: Building the business case for agentic automation
aws ·
This article argues that traditional ROI models, which focus solely on hours saved, are inadequate for justifying agentic automation investments because they miss critical value drivers. The authors propose the Agentic Value Model, which measures four dimensions: time savings, exception handling, decision quality, and change resilience. Unlike rule-based RPA, agents handle complex tasks with judgment and adaptability, requiring a shift from counting labor hours to measuring economic outcomes like reduced error costs and improved decision integrity. The text emphasizes that freed capacity must be redeployed or result in spend reduction to impact the P&L, rather than simply filling existing backlogs. Real-world examples from Kitsa, dLocal, and Genpact illustrate how these dimensions apply to clinical trials, payments compliance, and supply chain risk. To prioritize workflows, the article suggests a matrix based on task complexity and decision risk, guiding organizations to choose between RPA, agentic automation, or human oversight. Finally, it advises presenting automation as a portfolio of projects with clear stop rules and KPIs to secure leadership buy-in and ensure scalable value realization.
aws