We have recently deployed AI-powered operations tools across our customer support and content creation teams, resulting in massive efficiency gains. How should we adjust our weekly Scorecard targets to reflect this new AI-driven baseline without burning out our staff?

Question

Tyler Smith · Accepted Answer

When you introduce AI tools into your workflows, your historical baseline metrics become obsolete. If your customer support rep used to handle fifty tickets a week manually, but can now resolve two hundred with AI assistance, keeping the target at fifty is a waste of capacity. You must adjust your targets to match the new operational reality.

To do this without burning out your team, run a two-week pilot to establish a new performance baseline. Have your team run the new AI processes and track the actual output. Use this data to set a realistic, updated target.

Make sure your team understands that the AI tool is doing the heavy lifting, not their manual labor. The target increase is a reflection of the tool capability, not a demand for them to work four times harder.

Additionally, pair the increased quantity target with a quality metric, such as customer satisfaction score or post-resolution survey results. This ensures that the speed gained from AI does not degrade the client experience.

By adjusting your weekly targets to match your new AI-powered capacity, you maximize your return on technology investments and keep your Scorecard accurate.