SAP: Knowledge graphs and governance are essential for enterprise AI agents
Critical steps for companies transitioning from chatbots to autonomous AI agents.
1Transitioning from chatbots to autonomous agents
Max McPhee, senior solution advisor at SAP, emphasized the importance of companies moving from chatbots to autonomous AI agents during his talk at VB Transform 2026. McPhee stated that these agents need to be grounded in the company's own context rather than general knowledge. This allows agents to behave more like a coworker than an assistant. SAP recommends using knowledge graphs and vector-embedded data to facilitate this transition.
2Building enterprise context with knowledge graphs
McPhee explained that the principles used to onboard new employees also apply to AI agents, with adjustments for how software retrieves information. Knowledge graphs and vector-embedded data make it easier for agents to find and retrieve information. This approach helps companies overcome challenges like internal shorthand, ensuring smoother operations.
3Governance, identity, and security
SAP offers a robust infrastructure for governance and process control in autonomous agents. McPhee highlighted that as a 50-year-old process company, SAP has modernized its governance to handle the flexibility of agents. Machine learning is regaining importance for validating agent behavior, with anomaly detection and ML-based validation acting as guardrails.
4Identity and permission management
SAP's generative AI assistant, Joule, operates based on user access rights. Even if a user has permission to access S/4, Joule must also be provisioned for that access, eliminating the risk of bypassing controls. SAP ensures top-tier security with this model, preventing unauthorized access through agents.
5Balancing standard SAP with customized systems
McPhee stressed the need to bridge SAP's knowledge with customer customizations and non-SAP systems. Many customers report that SAP constitutes only 10% of their landscape. Acquisitions like LeanIX and Signavio help map these non-SAP systems, enabling agents to understand enterprise interconnections.
6Automation investments
SAP acquired Berlin-based automation company n8n, integrating it into Joule Studio, a low-code environment for building agents. McPhee warned that companies must modernize legacy systems to avoid performance issues, likening it to 'driving a Ferrari on a dirt track.' Upgrading infrastructure is essential for leveraging autonomous agents.
7The resurgence of machine learning
McPhee noted that the rise of autonomous agents has brought machine learning back into focus. Anomaly detection and validation processes ensure agents operate securely. SAP has long used this approach for intelligent approval recommendations, enhancing reliability in business processes.
8The future of business processes
SAP predicts that autonomous AI agents will transform business processes. Knowledge graphs, governance, and security measures are foundational to this shift. McPhee warned that without modernizing infrastructure, companies won't fully benefit from these technologies. SAP aims to guide customers through this transformation.