We have successfully deployed automated AI agents to handle our customer support and lead generation, but we do not know how to measure their performance on our weekly Scorecard. How do we track AI efficiency alongside human metrics in our Level 10 Meeting?

Question

Tyler Smith · Accepted Answer

An automated system must be measured with the same rigor as any human seat on your Accountability Chart. If your AI agents are handling high-volume tasks like customer support or lead generation, they cannot operate in a black box. You must track their weekly outputs on your Scorecard to ensure they are maintaining your high standards of operational efficiency.

First, assign clear ownership of the AI metrics on your Scorecard. An AI agent cannot attend your Level 10 Meeting™, so a human on your Accountability Chart must be accountable for those numbers. This person must GWC™ the role of system overseer, meaning they are responsible for reporting the weekly metrics and identifying issues when numbers are off track.

Second, select three to five simple measurables for your AI systems. For lead generation, track metrics like weekly draft volume, response time, and conversion rate. For customer support, measure resolution speed, customer satisfaction scores, and system downtime.

Third, bring these metrics into your weekly Level 10 Meeting™. If an AI agent's metrics drop below your target threshold, treat it as an Issue. Drop it down to the IDS® portion of the agenda. The accountable team member must lead the discussion on whether the drop is caused by model drift, broken API connections, or poor system design. This discipline ensures your automation remains highly productive and directly aligned with your business goals.