Combining AI Agents: Multi ‑Agent Systems in Demand Forecasting

This article presents Multi-Agent Systems (MAS) as a practical, modular approach to modernizing demand forecasting with low-cost, easy-to-use LLMs like ChatGPT. Instead of relying on a single monolithic model, MAS distributes intelligence across specialized agents that handle data preparation, signal detection, modeling, overrides, narratives, and scenario analysis. A key component is the LLM Judge Agent, which evaluates each agent’s output for logic, consistency, and business relevance—acting like an always-on senior Planner. For planning teams, MAS offers a flexible path to AI-driven agility and transparency while preserving human judgment at the center of forecasting ...