Where AI is actually worth using
How to tell the difference between an AI feature that helps and a demo that falls apart in real use.
By WSV Consulting
It's never been easier to build an impressive AI demo, and it's never been harder to ship one that holds up once real people use it. The gap between those two is where a lot of budgets quietly disappear.
Tie it to something you already measure
The best place to start is a number you already care about, like how long support tickets take or how many people finish signing up. If you can't name the thing an AI feature is supposed to improve, you're building a demo, not a product.
Plan for it being wrong
AI models are confidently wrong sometimes. Real products plan for that, with a person checking the important stuff, a clear backup when the model fails, and ongoing testing instead of a single check before launch.
The AI worth shipping usually looks boring from the outside. It quietly saves a few minutes on a task that happens thousands of times a day. That adds up.
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