Manufacturers wanting to leverage the latest AI tools with their quality data need to make key decisions and changes NOW in how they collect and store information.

A recent Quality Magazine article by Genevieve Diesing highlighted a key challenge for manufacturers preparing for AI: disconnected and inconsistent data.

As Chris Campbell, President and CEO of AssetSmart shared in the article, “Errors are intrinsic to manual data entry… A wrong value will negatively affect any AI models.”

As manufacturers continue investing in AI and advanced analytics, one thing is becoming clear: AI is only as good as the data behind it.

At AssetSmart, we see this every day. Manufacturers want smarter operations, better quality control, and less waste — but disconnected systems, manual processes, and siloed data often stand in the way.

Preparing for AI doesn’t start with the algorithm. It starts with building reliable, and connected operational data.

That means:
✔️ Capturing accurate data at the source
✔️ Connecting information across systems

✔️ Standardization of data  
✔️ Creating a foundation for scalable analytics and AI

The manufacturers who make these investments now will be the ones best positioned to leverage AI in the years ahead. At AssetSmart, we help manufacturers build the connected, reliable operational data foundation needed to support AI, analytics, and smarter decision-making.

Before AI Can Help, the Data Has to Be Ready

Manufacturers who want their data to support AI in the next several years need to make decisions now about how they collect and store information.

Read the full article:

https://www.qualitymag.com/articles/print/99564-before-ai-can-help-the-data-has-to-be-ready