The shift toward AI-driven decision frameworks is not simply a technological trend but a fundamental necessity for life ...

For each AI system making operational decisions in your organization, what does it know about the world outside your own data ...

For most of a decade, I have led replacement-demand planning for low-voltage automotive batteries, where this failure mode is ...

Time series forecasting is central to modern supply chain management, enabling organisations to anticipate future demand, optimise inventory levels and streamline logistics. Classical statistical ...

For years, supply chain organizations approached demand forecasting by looking backward, with historical sales trends, seasonal cycles and prior purchasing behavior forming the foundation for most ...

From new tariffs and trade uncertainty to geopolitical tension and extreme weather events, external forces have upended traditional demand forecasting approaches. Among those most impacted are the CPG ...

Editor’s note: This article first appeared on the University of Tennessee, Knoxville’s Global Supply Chain Institute’s blog. It is being reprinted with permission. You can read the original post here.

Google DeepMind and Google Research today announced WeatherNext 2 as its “most advanced and efficient forecasting model.” Notably, it’s helping power forecasts in Google’s consumer apps, including ...

The 2025 hurricane season was a coming-of-age story for AI weather models, which have been around in some capacity since around 2022. Last hurricane season, AI models not only proved they could ...