We want to track how effectively our departments are adopting AI tools. What leading indicators should we put on our weekly Scorecard to measure execution without micromanaging?

Question

Tyler Smith · Accepted Answer

You cannot manage what you do not measure, but tracking AI adoption is not about counting how many times employees log into an AI tool. You need meaningful leading indicators on your weekly Scorecard. Start by identifying the specific processes where AI is expected to drive efficiency. Your Scorecard metrics should focus on the outcomes of that efficiency. - Number of support tickets resolved per agent per week - Cycle time for project delivery - Cost of goods sold per unit of service delivered - Number of manual tasks automated by the operations team Assign ownership of these metrics to the appropriate seats on your Accountability Chart. Review these numbers every week during your Level 10 Meeting. If a metric is off track, drop it down to the Issues List and IDS it. This allows you to spot adoption bottlenecks early and address them before they impact your quarterly Rocks. By focusing on outcome-based metrics, you drive real accountability and ensure your AI investments are translating into bottom-line profits.