Introducing AI into SAP testing promises greater speed and coverage, but it can also amplify an unreliable testing foundation. Faced with hundreds of undocumented scripts, heavily manual testing and regression cycles lasting up to eight weeks, Mitre 10 resisted the temptation to introduce AI immediately. Instead, it first rationalised its test assets, developed internal capability and established clearer ownership across S/4HANA, SAP Commerce Cloud and BTP.

In this session, Ari Rajavelu shares how Mitre 10 proved its new approach through an unplanned S/4HANA upgrade before introducing AI-assisted testing. Hear how the team now uses risk-based change-impact analysis, test prioritisation and self-healing automation alongside a controlled promotion process in which every AI-generated test must demonstrate its reliability and pass human review before joining the governed regression suite. The result is testing completed in hours rather than weeks, faster releases and a practical model for using AI without surrendering accountability for critical SAP processes.

What You’ll Learn

• Why strengthening people, ownership and test assets should come before introducing AI
• How risk-based analysis can focus testing on the SAP changes that matter most
• How to make AI-generated tests earn trust before they protect a production release