Is AIoT actually making industrial operations smarter, or are we just adding more technology?

There’s a lot of discussion around AIoT—the combination of artificial intelligence with connected devices and sensors—but I’m curious how much practical value organizations are actually getting from it.

In theory, the combination makes sense:

IoT collects real-time information from machines, assets, and environments.
AI analyzes that information and identifies patterns or anomalies.
Teams can use those insights to make faster operational decisions.

Industrial applications could include asset tracking, predictive maintenance, inventory visibility, workplace safety, equipment monitoring, and operational optimization.

But there seems to be a major gap between a successful demo and a system that works reliably in a real industrial environment.

For example, collecting thousands of sensor readings doesn't necessarily improve operations if the data isn't reliable or if employees don't have a practical way to act on the insights.

There are also questions around integration, cybersecurity, cost, maintenance, and whether companies can actually measure the ROI after deployment.

So I'm interested in hearing from people who work with industrial AI, IoT, manufacturing, logistics, or automation:

Where do you think AIoT provides the most practical value today?

And equally important: what are the biggest problems or disappointments you've seen with AIoT implementations?