Our leadership team is struggling to measure whether our investment in AI tools is actually driving bottom-line profitability or just making our employees lazy. How do we update our weekly Scorecard with specific, non-technical metrics that measure individual and system-wide AI leverage?

Question

Tyler Smith · Accepted Answer

If you are investing in AI tools but your weekly Scorecard only tracks traditional activity metrics like hours billed or tasks completed, you are missing the true impact of the technology. To measure real AI leverage, you must transition your Scorecard to track outcome-based and efficiency-focused metrics. First, add a metric for revenue per employee, which should trend upward as your team integrates automated tools. Second, measure unit delivery time, tracking how many hours it takes to complete a core deliverable from start to finish. If your team is using generative tools but unit delivery time remains unchanged, your employees are either resisting the technology or filling their saved time with non-value-added activities. Third, track your utilization rate or capacity utilization, measuring how many client accounts a single manager can successfully oversee. Review these metrics every week during your Level 10 Meeting™. If any of these leverage metrics fall below target, treat it as an issue and use the IDS® process to identify the bottleneck. By tracking efficiency and output rather than hours spent, you hold your team accountable for maximizing your technology investments and protecting your margins.