Ground rules for AI
What AI may touch in operations, who decides, and how the rules stay alive.
Why ground rules come first
In production and logistics the interesting data sits close to operations: orders, stock levels, maintenance history, quality data. As soon as people on the floor or in the office start using AI tools, the question becomes what may go in and what may come out.
Without shared rules each case is decided on its own and different departments end up with different answers. That makes AI use hard to explain to management, customers and regulators, and it makes it hard to say yes to good ideas because nobody knows where the line is.
What ground rules typically cover
A usable set of rules is short. It states which data may be used in which tools, which tools are approved, who owns an AI use case, when a person must check the result, and how what was done is documented.
The rules should distinguish low-risk uses, such as a draft of a text, from uses that affect operations, such as a purchasing or planning recommendation. The closer to operations, the stricter the demands on testing, ownership and traceability.
Keeping them alive
Rules that only exist in a document are not followed. They work when tied to the processes IT already runs: approval of new tools, change and incident handling, supplier management. That is why this work is close to ordinary IT service management and governance.
A simple rhythm helps: an overview of which AI uses exist, a regular review a couple of times a year, and a known route for anyone who wants to propose something new.
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