Every SAP landscape contains custom code that works—but nobody wants to touch it. Technical debt, poor documentation, and legacy design can make even simple changes risky and time-consuming.

In this session, SAP developer and author Paul Hardy puts today's leading AI tools to the test using a deliberately awful ABAP program designed to reflect the realities of many SAP environments. Through a series of hands-on experiments, he explores how AI performs when analysing legacy code, generating tests, identifying refactoring opportunities, and assessing readiness for S/4HANA and SAP S/4HANA Cloud.

Discover where AI genuinely delivers value, where it falls short, and why human expertise remains essential. You'll leave with practical insights into how AI can help reduce technical debt, improve code quality, and accelerate SAP modernisation efforts.

What You'll Learn

• How AI performs when analysing legacy ABAP code
• Ways to accelerate testing and refactoring with AI
• Practical approaches to reducing technical debt
• How AI can support S/4HANA modernisation
• Common pitfalls when relying on AI-generated output