AI-Driven Security Strategies for SAP Environments is a timely and authoritative guide for integrating artificial intelligence into the cybersecurity framework of SAP systems. As enterprises undergo rapid digital transformation, this book provides both strategic vision and technical depth to help organizations detect threats proactively, automate identity governance, and strengthen their overall security posture.

Starting with the limitations of traditional methods, the book explains how AI enables adaptive, real-time defenses tailored to SAP’s unique architecture. It explores core AI capabilities, architectural models, and how to integrate with external tools like SIEM and EDR for enriched threat context. Readers will learn how to apply AI for real-time anomaly detection, access control automation, and risk-based alert prioritization—backed by SAP system log analytics and predictive modeling. Case studies on role prediction, governance automation, and LLM-powered threat hunting ground these concepts in practical success stories, offering a clear path from strategy to implementation.

You Will:

• Understand core architectural models and AI capabilities required to secure SAP landscapes
• Learn techniques for automating identity governance and intelligent access control
• Learn real-world implementation insights from case studies in SAP role assignment, governance, and predictive security

This book is for: SAP Security and GRC Professionals

Mercedes Barrachina is an SAP security innovation lead at IBM (SAP Center of Competence in Europe). She holds a BSc and MSc in telecommunications engineering from the University of Malaga, developed her master thesis in the German Aerospace Center (DLR) and holds a BSc in economics as well as a PhD. She has completed several SAP training courses, including SAP Process Control, SAP Risk Management, SAP Fraud Management, SAP Access Control, and SAP HANA.

Mohamed Oudoun is a data engineering consultant at IBM (Client Innovation Center, Morocco). He holds a Master of Engineering (MEng) in computer science and specializes in building scalable AI and data platforms. His work focuses on data lakehouse architectures, machine learning systems, and generative AI applications. He has completed multiple technical trainings in cloud, data, and AI technologies, and has contributed to the development of enterprise-grade solutions across various industries.