There’s a lot of buzz around AI’s potential to transform supply chain forecasting, especially looking toward 2026. I came across https://www.trinetix.com/insights/logistics-and-supply-chain-trends, which gives a solid overview of how AI-driven demand forecasting is expected to complement traditional methods. Unlike relying solely on historical data and stable patterns, AI can analyze larger and more complex data sets, adapting dynamically as demand fluctuates to reduce forecast errors. The article also highlights advanced data technologies like predictive analytics, digital twins, and control towers that help turn fragmented data into actionable insights for better risk management and more predictable supply chains. Given the frequency of supply chain disruptions due to climate, geopolitical, or health factors, this adaptive and responsive forecasting is becoming essential. Additionally, there’s growing interest in integrating ESG and sustainability goals, which could also inform planning decisions by considering environmental and ethical criteria. Overall, AI seems poised to improve both the accuracy and flexibility of forecasting, helping companies better react to rapid changes and minimize costly supply disruptions.