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Report 25 Sep 2026

AI Security, Secure AI Lifecycle, and Security Automation – Market View

AI security is becoming an integral part of enterprise cybersecurity. As organizations deploy generative and agentic AI, the attack surface expands across models, applications, RAG environments, enterprise data, identities, APIs, tools, and AI infrastructure. Therefore, security needs to span the entire AI lifecycle, from discovery and design to development, testing, deployment, operation, and retirement.

At the same time, AI is transforming security operations. Organizations are moving from AI-assisted search and investigation to agentic orchestration and policy-governed response. This shift increases the importance of identity, authorization, auditability, human oversight, and rollback mechanisms.

Key findings:

  • AI security is shifting from model protection to system-level security, covering data, identities, agents, applications, infrastructure, and connected tools.
  • Agentic AI makes identity and authorization critical controls because security increasingly depends on what an AI agent can access and execute.
  • Security automation will progress toward governed autonomy, but high-risk actions will continue to require stronger controls and oversight.
  • AI security services will expand to assessment, secure AI engineering, red teaming, runtime protection, SOC transformation, and managed AI security.

Recommended advisory: PAC Leadership Session – Cybersecurity Trends

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Wolfgang Schwab

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