AI agents are increasingly embedded within enterprises, prompting questions about their governance. The rise of agentic AI and Model Context Protocol (MCP) frameworks signals a transformative shift in automation and interoperability, enhancing AI’s ability to execute tasks across platforms. Gartner anticipates that by 2028, a third of Generative AI interactions will involve autonomous agents. While these advancements promise significant efficiency benefits, they also introduce governance, security, and confidentiality risks that organizations are ill-prepared to manage.
The current governance gap reveals that traditional identity governance frameworks, designed for human oversight, struggle to accommodate non-human identities (NHIs) like AI agents. To mitigate risks, organizations must establish robust governance frameworks tailored for AI. Implementing lifecycle management, enforcing least-privilege access, and monitoring cross-platform interactions are vital steps. A modern Identity Governance and Administration (IGA) approach ensures organizations securely manage AI agent identities, enabling them to harness the benefits without compromising security.
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