Liu's CAREER award to support AI-driven wireless network research, education

You bought the AI tool. Nobody used it. $200/month gone, and now you're more skeptical than ever.

That's not a you problem. That's a deployment problem.

Here's what a recent NSF-funded AI research award quietly confirmed: even the most sophisticated AI systems fail when they're built without understanding the real-world environment they'll operate in. Researchers are now designing AI that learns the specific conditions of a network before making decisions — not generic AI dropped in and hoped for the best.

That's exactly what went wrong with your tool. It was built for every business, which means it was optimized for none of yours.

The lesson isn't "AI doesn't work." It's that AI works when it's matched to one specific, repetitive problem in your business — not deployed as a general solution across everything at once.

Pick one bottleneck. One task your team does manually every week that follows a predictable pattern. That's your starting point. One workflow, one tool, thirty days to measure the result.

That's how you get your first real win — without touching what already works.

What's one repetitive task in your business that costs your team the most time each week?

#AIForBusiness #SmallBusinessGrowth #AIStrategy #BusinessOperations

Original Source

Qiang Liu, assistant professor in the School of Computing, stands next to one of. Liz McCue | University Communication and Marketing. Liz McCue | ...