Evaluating agentic AI for demand forecasting
· Source: techtarget.com
In short
The article explains how agentic AI can overcome the limitations of traditional statistical demand forecasting models when demand is unstable, unreliable or disrupted by climate, geopolitical and economic factors. It defines agentic AI for forecasting through autonomy, goal-driven reasoning and environmental awareness, then lays out four evaluation dimensions CIOs must prioritize: data readiness, human-in-the-loop governance, integration with legacy systems, and total cost of ownership. A three-phase adoption roadmap (contained pilot, supervised deployment, scaled rollout) is proposed to manage risk and prove business value.
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In the issue of week 40, 2026: Supply Chain AI Advances, but Data, Governance and Capacity Set the Pace
Tags: forecasting, agentic AI, supply chain, inventory, governance, ERP