The tools are deployed. People are using them. The gains have not followed.
This is the most common position after a significant AI deployment: adoption is solid, the dashboard shows activity, and the projected returns have not materialised. The score identifies where the drag actually is.
Six months after a significant AI deployment, the adoption rates are where they were supposed to be. The tools are running. Nobody is avoiding them. The productivity improvements that were modelled before approval have not materialised. In some teams things have got slower.
The usual explanations do not account for the size of the gap. More training has been commissioned. Change management has been reviewed. The tools themselves have not been found defective. The deployment was not wrong. But something upstream of deployment is not working. Nobody can say what it is, because the organisation has been measuring adoption rather than integration.
They are not mutually exclusive, and in most organisations more than one is active. The score shows which combination is driving this organisation's particular reading.
The time freed by automation has been replaced by the time spent managing AI outputs: checking them, re-running them, correcting them, routing work around the failures. Coordination Efficiency goes down rather than up. The net gain is near zero because the hidden overhead never made it onto the deployment plan.
AI tools were deployed where they were easiest to implement, not where they would have the most impact on outcomes. Teams are faster at tasks that were never the bottleneck. The Leverage Trajectory is flat or declining because high-value judgment work remains untouched.
People are relying on AI outputs for work they would previously have done themselves. Output volume looks normal. The underlying capability is contracting below the surface of the metrics, quietly, because the outputs still look fine. Capability Development Velocity reads lower than it did before the deployment.
The Kaivant Score does not diagnose the cause in advance. It reads the current state across nine dimensions and shows where the weight is concentrated. Once the reading is in front of the leadership team, the pattern is usually recognisable. The score gives the room something neutral to read rather than an accusation to defend against.
A two-hour facilitated session with the score as the agenda is typically enough to identify which of the three patterns is driving the gap, agree the specific dimensions to address, and set the smallest first move for each one. The next measurement shows whether it moved.
Score the current state · Diagnose which pattern is creating the drag · Act on two or three specific moves this quarter · Re-measure and compare the delta. Repeat until the reading is where it needs to be.