Every SAP transformation eventually reaches the point where bad master data becomes impossible to ignore. Years of inconsistent standards, duplicate records and manual workarounds quietly undermine reporting, automation and AI initiatives. Whether you're migrating to SAP S/4HANA, modernising analytics or preparing for enterprise AI, the same question emerges: how do you improve data quality without years of manual effort?

Artificial intelligence promises to change that.

In this session, Leo Brooks shares real-world examples of using AI to analyse, classify and enrich SAP master data at enterprise scale. Drawing on enterprise asset management projects as practical examples, he'll demonstrate how AI can identify patterns, detect duplicates, restructure inconsistent records and accelerate data remediation, while showing why human expertise remains essential to validate and govern the results. You'll see a live demonstration of AI cleaning and enriching SAP data, hear the lessons learned from applying it in complex SAP environments, and leave with practical ideas you can start using in your own organisation, regardless of where you are in your transformation journey.

What You'll Learn

• Why master data has become one of the biggest barriers to successful SAP transformation and AI adoption.
• Practical ways AI can accelerate the identification, classification and enrichment of SAP master data.
• Where human expertise remains essential to validate, govern and approve AI-generated recommendations.
• Lessons learned from applying AI to large, complex SAP datasets in real-world enterprise environments.
• How cleaner, more trusted SAP data creates a stronger foundation for SAP S/4HANA, analytics and enterprise AI.