AI spend keeps rising, but many organizations still cannot produce earnings-call-ready ROI. Deloitte has named the paradox directly: rising investment, elusive returns. The result is a familiar pattern — plenty of activity and headlines, but not enough proof that the economics improved.
Most of the time, the model is not the problem. The gap usually sits between "we built it" and "the business actually runs differently." McKinsey's research lands in the same place: companies capture more value when they redesign workflows and put real governance around deployment.
The most commercially viable AI initiative right now is not another pilot. It is AI value realization anchored in process integration. Pick one outcome. Give it one executive owner. Put a dollar sign on it. Wire the workflow into systems of record. For a CRO, that means win rate, sales cycle time, or discount discipline. For a CFO, it means DSO, invoice exceptions, or cost per transaction.
Gartner's updated figures reinforce the urgency: over 50% of GenAI projects were abandoned after proof of concept by end of 2025 — up from the 30% projected in 2024. The root causes remain the same: unclear business value, data issues, rising costs, and weak risk controls.