Agentic Decision Support: Agents That Prepare Human Decisions

Agentic decision support uses AI agents to prepare decisions that a human remains responsible for making. An agent gathers relevant data, compares options, tests scenarios and summarizes trade-offs. It presents a recommendation together with the evidence behind it. The decision itself stays with the manager or specialist.

This differs from agentic decision-making, in which the agent also carries out the choice. Decision support keeps a person in the loop, which suits situations with high stakes, regulatory requirements or unclear objectives. Methods such as Tree of Thoughts, which lets a model explore several lines of reasoning before settling on one, illustrate how agents can structure this preparation.

For senior leaders, the value lies in speed and breadth of analysis combined with retained accountability. Requirements follow from that: sources must be traceable, reasoning must be inspectable and uncertainty must be stated. Risk management frameworks such as the one published by NIST address these needs for trustworthy AI systems.