Artificial intelligence agents are changing how organizations interact with enterprise applications, data repositories and business processes. As adoption accelerates, leaders must determine how agent identities should be governed, what permissions agents require and how those activities can be monitored effectively.
Unlike traditional access models focused exclusively on human users, AI environments often involve a combination of user identities, agent identities, workloads and system accounts. Organizations need practical ways to limit access, monitor activity and reduce the risk of unintended actions.
Join RSM professionals as they discuss how AI agents are transforming enterprise access models and why Model Context Protocol (MCP) is becoming an important mechanism for connecting agents to enterprise systems and data. Through practical implementation examples, governance principles and a live demonstration, attendees will learn how organizations are addressing authorization, access controls and enterprise-data governance in AI-enabled environments.
You'll learn:
- Why AI agents are changing traditional access and governance models
- How MCP enables agents to interact with enterprise systems
- Key differences between user, workload and agent identities
- Read-only versus write-back access considerations
- Practical approaches to MCP authorization
- Agent registration and inventory management
- Permission bounding and least-privilege design
- Monitoring, observability and governance controls
- Enterprise-data considerations, including data boundaries and kill switches
- Governance and implementation lessons learned from real-world use cases
