Decision latency is the time between a request and a clear decision. It is often hidden inside meetings, handoffs, and “waiting for approval” states. The cost is not just time — it is rework, escalation fatigue, and missed opportunities.
AI initiatives often accelerate the front end of a workflow: faster intake, automated summaries, instant recommendations. But if decision rights are unclear, AI adds volume to the backlog. The result is faster inputs and the same bottleneck.
Reducing decision latency requires a clear ladder: who can approve, who can override, and where exceptions go. That ladder is operational, not technical. Once it exists, AI can compress the cycle by routing decisions to the right person with the right evidence.
The payoff is compounding. When decisions happen quickly, you reduce handoffs, shrink backlog, and rebuild trust in the process. AI becomes a force multiplier, not a source of noise.