AI Value Realization is the governance discipline that connects AI and automation investment to realized P&L impact, from the original business case through to board-ready proof of return. It requires three components: independent measurement not produced by the vendors being evaluated, the Forecast vs. Realized Loop auditing actual P&L movement against the original business case, and Capacity Released as the metric connecting freed time to financial outcome. Most enterprises can forecast AI value at approval; almost none audit whether it materialized post-deployment – that gap is what AI Value Realization closes.