How to measure the business impact of AI

The panel explores how to measure the business impact of AI, moving beyond experimentation to demonstrate return on investment to leadership. Stacia suggests focusing on culture, system impact (velocity, quality), and customer satisfaction, while Jennifer emphasizes understanding resistance to AI adoption and splitting adoption rates by employee longevity. Vernon argues that AI adoption highlights the need for fundamental engineering practices like CICD and proper metric measurement. The panelists discuss the limitations of traditional engineering metrics, advocating for DORA metrics and the SPACE framework to address developer experience and potential burnout. They also explore how to communicate improvements in developer experience to CFOs and executives by translating engineering metrics into business priorities, such as customer satisfaction and experimentation capacity.