Mid-Year AI Review: Are You Getting What You Paid For?

If you implemented AI tools in the first half of this year, now is a natural moment to step back and evaluate. Not just whether the tools are running, but whether they’re actually delivering the value you expected.

Questions to Ask

A mid-year AI review doesn’t need to be complicated. Work through these questions:

Is the system still running? This sounds obvious, but AI implementations can quietly break or drift. Check that the automations are firing, the outputs look right, and no one has worked around the system because it stopped working well.

Did the metrics move? Go back to whatever baseline you set at the start. Response time, conversion rate, hours saved, error rate — whatever you were measuring. Has it improved? By how much? Is it enough to justify the ongoing cost?

Are there new workflows to add? You probably started with one or two use cases. Six months in, you understand your business and the AI’s capabilities better. What else should be automated?

Is the team using it? Adoption can erode over time, especially if the system requires any effort. Is your team still using the AI the way it was intended, or have they gone back to old habits?

What to Do With the Answers

If the metrics are moving and the team is using it: document what’s working, expand to a new use case, and set goals for the second half of the year.

If the system has stalled or the results are unclear: diagnose before you add more. The issue is usually one of configuration, adoption, or measurement — and all three are fixable.

If you want a fresh set of eyes on your AI setup, let’s do a review together.