AI for Impact 
Measuring What Matters
Many AI evaluations focus on efficiency metrics such as time saved, documents processed, or staff hours reduced. This session examines how agencies can move beyond productivity measures to define success in terms of service quality, accuracy, equity, public trust, resident and worker experience, and public outcomes. Participants will learn practical approaches for identifying meaningful measures of public value.
Learning Goals
By the end of this workshop, participants will be able to:
- Distinguish between efficiency metrics and broader measures of AI effectiveness and public value.
- Identify meaningful measures of success across service quality, accuracy, equity, public trust, and resident and worker experience.
- Develop practical measures for evaluating whether AI use is improving public services and contributing to better outcomes.
Principles for Public-Sector AI Evaluation
Try Before and After You Buy
Comparing Humans, AI, and Human-AI Teams