Data governance is the framework of rules, roles and processes that decide how a business's data is collected, stored, accessed, used and retired. It answers who owns each dataset, who can see it, how accurate it must be and how long it is kept.
It typically includes named data owners, an inventory of where data lives (POS, loyalty, rostering, accounting, cameras), access controls, retention periods, and rules for sharing with vendors. Good governance makes data trustworthy and traceable.
For AI, governance decides what an AI tool is allowed to see. An assistant connected to the POS and customer database should only reach the fields it needs. Retailers can start small: list key systems, assign an owner to each, and agree who approves new integrations.
Pitfalls include data spread across spreadsheets and personal devices, duplicate customer records, former staff retaining access, and AI tools connected with broad permissions because it was easier. Review access regularly. A quarterly check of who can see what, and which AI tools are connected to which systems, catches most problems early and costs very little.
It matters because AI is only as good and as safe as the data behind it. Clear governance reduces privacy and security risk and makes reporting and AI results more reliable.