AI has officially crossed the hype curve. The models are powerful, but enterprise progress is stalling. Security reviews stretch on, governance debates multiply, and promising initiatives lose momentum before they ever reach production.

This friction is not a failure of ambition; it is a failure of auditability.
If your systems can’t explain what data a model saw or why a decision was made, the default response is “no.” You can’t accelerate what you can’t verify.
That’s the Trust Tax: the hidden cost of opaque infrastructure in high-stakes environments. The longer you pay it, the further you fall behind.

This paper outlines how teams are eliminating the “AI Trust Tax” by shifting to event sourcing—capturing every state change as an immutable event. That history becomes the foundation for operational oversight, auditability, and explainable AI.

Instead of reviewing decisions after the fact, these teams design for visibility from the start. Governance is built in, not bolted on. And that changes the equation: from delay to deployment and from caution to control.