Overcoming identity and access management risks associated with generative AI

The rapid adoption of generative AI has transformed how businesses operate, offering unprecedented opportunities for automation, efficiency, and innovation. However, alongside these advancements comes a complex set of challenges in identity and access management (IAM). Traditional security models, which were designed for static environments with predictable access patterns, are now being tested by AI-driven systems that generate, interpret, and act upon vast amounts of data in real time.

As generative AI evolves, so too does the attack surface. Organizations now face emerging risks such as AI-driven identity fraud, unauthorized access to AI-generated content, and the challenge of managing machine identities alongside human users. The dynamic nature of AI-driven decision-making complicates conventional IAM approaches, requiring businesses to rethink authentication, authorization, and governance frameworks. Without a proactive strategy, enterprises risk exposure to data breaches, regulatory non-compliance, and the erosion of digital trust.

This paper aims to provide cybersecurity leaders, risk managers, and IAM professionals with insights into navigating this shifting landscape. It explores key IAM risks associated with generative AI, from managing privileged access for AI models to mitigating adversarial attacks that exploit AI-generated content. It also highlights emerging best practices and technologies—such as AI-powered identity verification, adaptive access controls, and zero-trust architectures—that can help organizations maintain security while enabling AI innovation.

As businesses continue integrating AI into their digital ecosystems, IAM strategies must evolve to address these new threats while ensuring operational resilience. By understanding and addressing the risks today, enterprises can build a secure, scalable foundation for AI-driven transformation. This paper serves as a guide for security professionals striving to stay ahead of the curve in an era where identity and access management must be as dynamic as the AI technologies they seek to protect. 

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