AI in data management - Hype or help?

AI creates value in data management only when it works on trusted source data and governed rules. Web-trained LLMs are not a trusted source, they are reasoning layers that must operate on authoritative inputs.

Key Takeaways 

1. Cut cost, not control 
   AI shifts repetitive data maintenance work from manual teams and standardized routine tasks to governed agents. This lowers operating cost, increases throughput, and frees experts for exceptions and policy decisions.
2. Trusted data, real value
   AI creates business value only when it runs on trusted sources, governed logic, and accountable ownership. Weak data foundations turn AI into a multiplier of defects and downstream cost.
3. Governance decides the outcome
   AI delivers reliable results in clearly governed tasks with explicit boundaries. Uncontrolled AI autonomy turns local data issues into systemic operational and compliance risk.