The Agentic AI Readiness Gap: Proving the Agent's Work
TechTarget, Tuesday, August 19th, 2025
Enterprise agentic AI success depends on control systems and governance, not just agent capability.
Agentic AI deployments fail not because models give wrong answers but because the surrounding processes cannot explain or contain agent behavior.
The critical questions involve permission verification, system access tracking, completion validation, reversibility, and exception ownership.
Organizations must implement runtime controls through identity, permissions, workflow state monitoring, and cost tracking rather than relying on static policies.
Tiered autonomy levels should match risk profiles, with high-impact workflows requiring human decision rights. Success requires comprehensive observability to reconstruct action chains, clear escalation procedures, and demonstrable proof that agents operated within defined guardrails.