Agentic AI projects often look promising in a small demonstration because the workflow is still informal and the risk is contained. The challenge begins when the agent touches real decisions, systems, customers, or operational hand-offs.
Failures usually come from weak workflow design rather than weak technology. Permissions, escalation points, monitoring, human review, and exception handling need to be designed before an agent is trusted with meaningful work.
DDAI focuses on the operating model around the agent: what it can do, what it cannot do, who supervises it, and what evidence proves the organisation remained in control.