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Enterprises have spent the past several years experimenting with AI agents—as copilots, autonomous assistants, workflow optimizers, and increasingly as independent decision-makers embedded in complex systems. In 2026, this experimentation phase ends. It becomes the year enterprises are forced to confront the operational, security, and architectural realities of agentic AI at scale.
As organizations integrate agents deeper into workflows, they will discover that the promise of productivity arrives with new forms of risk—rooted in human-factor failures, novel attack surfaces, and the need for entirely new governance and infrastructure layers.
This paper: