In hospital exam rooms and factory floors, AI agents streamline operations by managing electronic health records and conducting rapid quality control inspections. Despite their productivity capabilities, these AI agents create a challenge for traditional identity management systems, which were designed primarily for human users and cannot keep pace with the speed and scale of agent activities. Cisco executives highlight a trust gap in enterprise adoption: while many companies are piloting AI agents, very few have moved to production due to concerns about identity governance, accountability, and security risks. Experts emphasize that trust must be integrated from the start, with secure delegation, comprehensive network visibility, and policy enforcement mechanisms to manage AI agents effectively. They advocate for cross-functional alignment, enhanced identity and access management, platform-based networking, hybrid AI architectures, and robust trust measures for early agent deployments. These steps are critical to unlocking the full benefits of AI while minimizing vulnerabilities and ensuring that AI integration is both safe and scalable.
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