What is the difference between decision support and decision automation?
Decision support keeps the person in the chair: the model forecasts demand, scores the lead, or drafts the plan, and a human approves it. Decision automation removes the approval for cases inside agreed bounds: repricing within a band, reordering stock, routing a claim. The question is never whether AI can decide, but which decisions are cheap to get wrong and easy to reverse. That boundary is exactly what human-in-the-loop design makes explicit.
Which business decisions is AI actually making today?
The repeatable, data-rich ones. Demand forecasting that blends sales history, weather and local events. Credit and fraud scoring. Dynamic pricing. Supply chain exceptions, where operations leaders are comfortable letting agents handle narrow, well-defined cases long before end-to-end execution, as in AI in supply chain. The pattern is consistent: automation starts at the exceptions a person finds tedious, not at the judgment calls a person finds hard.
How does a company govern AI decisions?
Three requirements, set before the first automated decision. Written criteria for what the system optimizes, so success is checkable. AI explainability proportional to the stakes, because a declined customer and a regulator both ask why. And a measured override rate: how often people correct the system. Autonomy is earned by a falling override rate, never granted by a launch date. Expanding an AI’s decision authority should be a review decision backed by numbers, the same way a new hire earns wider sign-off, a progression agent autonomy describes in levels.
Where does AI decision making pay back first?
Where decisions are frequent, measurable and currently inconsistent. The business case is usually consistency, not brilliance: the same criteria applied to every case, every day, with people moved to the exceptions. Build the AI business case on decision volume, current error cost and reversal cost, and pilot on one decision type with its own baseline before scaling to the next.