Poorly structured asset master data is a source of quiet friction. It rarely stops work outright, but it shows up everywhere: in time wasted searching for assets, in trends missed from poor analysis, and opportunities lost from not trusting your data. Poor master data becomes part of the operating environment: familiar, frustrating, and easier to work around than to fix.

Enter AI, a tool with no shortage of marketing hype. Fortunately, master data cleanup happens to demand exactly what AI does best: pattern recognition, scale, and tolerance for tedium. But AI can’t do it alone. Great AI usage doesn’t replace us; our role shifts from data creation to data validation.

In this session, industry expert Leo Brooks shares multiple real-world successes of using AI to analyze, restructure, and enrich master data across hundreds of thousands of assets. He will explore the opportunities AI creates, common pitfalls, and the role human expertise still plays in turning messy records into structured information teams can trust. And of course, the session will feature a live demo of AI cleaning up SAP data.

Key Takeaways:

• How to start using AI to clean your data right now
• Where human expertise remains essential in reviewing, correcting, and approving AI-processed master data
• What clean, structured asset data enables for maintenance planning, reporting, and reliability analysis