McKinsey’s latest warning is clear: agentic AI isn’t dangerous because it’s powerful—it’s dangerous when it’s deployed without guardrails.

As AI agents gain the ability to plan, act, and autonomously chain tools across systems, they introduce entirely new risk categories. These include runaway actions, privilege escalation, opaque decision paths, and blurred accountability. Traditional security and governance models simply don’t hold up when AI systems can operate independently at scale.

McKinsey’s core message to leaders: don’t scale agents before trust is engineered.
This means designing agent-specific controls from day one—clear permission boundaries, kill switches, full audit logs, simulation-based testing, and built-in human-in-the-loop escalation. The real failure isn’t speed; it’s deploying production-scale agents without safety, governance, and accountability architectures in place.

The paradox is striking: 89% of companies claim they’re using AI, yet only about one-third are seeing real enterprise value. The gap isn’t technology—it’s trust, operating discipline, and risk readiness.

TL;DR: Agentic AI is a massive force multiplier for both value and risk. Organizations that hardwire safety, security, and accountability now will scale confidently. Those that don’t will eventually be forced to slow down—or shut systems off entirely.

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Agentic AI Is Scaling Faster Than Trust — McKinsey’s Wake-Up Call: on Risk, Revenue, and the Next AI Operating System (Sign up)#141b

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