The CASE Framework: A Multi-Disciplinary Control Architecture for Governing Enterprise Agentic AI
Moving beyond DevSecOps to a multi-disciplinary architecture for governing autonomous enterprise AI systems.
Enterprises are deploying autonomous AI agents faster than they can govern them, and prevailing approaches stretch a single discipline, typically DevSecOps built for deterministic automation, across every scale of agency. We argue that agentic AI governance is four problems, not ...
ArXiv CS.AI
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The CASE framework provides a much-needed scientific taxonomy for AI governance that moves beyond generic policy toward rigorous, multi-layered control systems. By identifying the 'Emergence Gap,' it highlights how current enterprise deployments lack the architectural maturity required to safely manage complex, autonomous agent behaviors.
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