Measuring AI Adoption Success

Learning Objectives Choose the right KPIs to measure AI adoption on your team Build a simple reporting cadence that keeps leadership informed Translate AI usage data into business impact language Why Measurement Matters Without measurement, AI adoption is a feeling, not a fact. "I think the team is using it" is not a business case. "78% of the team uses AI at least 3 times per week, saving an average of 4.2 hours per person per month" is. Measurement serves three purposes: Prove value — justify the investment and earn support for expansion Identify problems — catch declining usage before it becomes abandonment Optimize — find what is working and double down on it The Four Categories of AI Adoption Metrics Usage Metrics (Are People Using It?) Target benchmarks: Week 2 of rollout: 50%+ of team has tried AI Month 1: 60%+ using AI at least once per week Month 3: 70%+ using AI at least 3 times per week Productivity Metrics (Is It Saving Time?) How to measure time savings without making it burdensome: Do not ask people to track every minute. Instead, pick 3 representative tasks and do a timed comparison once per month (2 minutes with AI, 2 minutes without, compare). Use a monthly 2-question survey: "How many hours per week does AI save you?" and "Which task benefits the most?" Quality Metrics (Is the Output Good?) Business Impact Metrics (Does Leadership Care?) This is where you translate AI metrics into language your organization values: The cost-benefit…