AI Tools Change Every Quarter. Re-Test Them.

One of the most expensive mistakes I see teams make with AI is evaluating a tool once and never revisiting the decision.

A team tries an AI tool, it falls short on an important task, and they set it aside. That assessment may have been accurate at the time. But AI products are improving on a timescale of weeks, not years. The tool that failed in the spring may be the best option for that task by summer.

What this looks like in practice

For years, the built-in AI in the database platform I use added little value. Then, within a few weeks of a major update, its connection for outside AI tools became reliable enough that my AI assistants now read and update records directly.

General-purpose assistants that struggled with multi-step tasks a year ago now complete research, drafting and scheduled reporting reliably. And usage limits that regularly interrupted work on leading plans have eased considerably.

In each case, a team that evaluated the tool once and moved on would be working with outdated information.

A simple re-testing habit

Avoid standardizing on a single AI vendor for every job. Instead:

1. Keep two or three real, recurring tasks as benchmarks.
2. Once a quarter, run them through the tools you use and one or two you don't.
3. When a different tool performs better on a task, move that task.

It takes an hour a quarter and keeps your team on the strongest tools available.

For my current recommendations by type of work, see How to Use AI in Your Business. For the broader shift from AI assistants to AI agents, see AI Agents for Business.

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