Course: Measuring AI ROI Pathway: Business (Paid) Level: Intermediate Estimated Reading Time: 8 minutes
The moment you deploy AI, everyone wants to know: "Is it working?"
That's the right question. The problem is that most organisations measure the wrong things — or measure too many things — and end up with dashboards full of numbers that don't actually tell them whether the investment was worth it.
This lesson is about choosing metrics that matter. The kind your CFO can use in a board paper. The kind that tell you, in plain terms, whether to keep going, adjust course, or stop.
There's a strong temptation to measure everything AI touches. Model accuracy. Response times. Token usage. User satisfaction scores. Employee adoption rates. Cost per query.
Any one of these might matter. All of them together create noise. When you present fifteen metrics to a board, you're not informing them — you're overwhelming them.
The discipline is in choosing the three to five metrics that genuinely reflect whether your AI investment is delivering value. Everything else is operational detail for the project team, not the boardroom.
Every metric should trace back to a business outcome. Not a technical outcome — a business one.
Here's the difference:
This lesson is part of Measuring AI ROI — a paid course (NZ$39.00). Enrol to unlock the full lesson, audio, and completion tracking.
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