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By combining Generative AI, automated data visualization, and Retrieval Augmented Generation, researchers created an intelligent chatbot that engages directly with procurement data.

Companies can reduce planning delays and improve service levels by using a hybrid metaheuristic approach, achieving near-optimal solutions in minutes instead of hours.

SCM alum Adam Buttgenbach ’20 is powering PepsiCo’s EV revolution! The Wall Street Journal interviewed Adam about his transformative work as PepsiCo’s Director of Fleet Engineering & Sustainability, where he is leading the deployment of more than 1,750 electric vehicles, including over 100 battery-electric semi-trucks from leading OEMs like Volvo, Tesla, and Daimler.

By combining industry expertise with statistical modeling, study offers a consensus-driven definition of the truckload market cycle and tools to predict changes

Many executives at small and medium-sized enterprises (SMEs) associate process automation with expensive robots and assume that it’s within reach only for large enterprises. However, possibilities for reducing the amount of human involvement in tasks extend well beyond robots and include a host of affordable approaches. In our research with SMEs, we have uncovered strategies that can make automation feasible, even for businesses with lean budgets.

AI is revolutionizing supplier negotiations, driven by the need for speed, scalability, and strategic agility in complex supply chains. Initially used for automating low-value tasks, AI can now play a crucial role in a growing number of key procurement decisions. However, adopting AI isn’t straightforward. Companies must navigate hurdles such as data quality, regulations, and matching the right tools to the right situation.

The future of warehouse operations hinges on a delicate balance between human capability and robot autonomy, empowered by AI. While the journey to advanced Human-Robot Collaboration (HRC) may be gradual, the key lies in recognizing the ongoing role of AI in improving every stage of collaboration.

MIT CTL Research Scientists Drs. Inma Borrella and Maria Jesus Saenz, in collaboration with Dr. Elena Revilla, wrote a case study which has been recognized as the top-selling case in Operations Management at Ivey Publishing for 2024/2025.

Data-driven approach improves forecasting, resulting in more effective inventory management.

Research explores the value of an end-to-end early warning system to improve on-time delivery.