Patricia Coan

Special Guest Blog Post written by Chris Cunnane with InterSystems   In a world defined by rapid market shifts, volatile supply chains, and unpredictable customer behavior, traditional forecasting methods often fall short. Relying primarily on historical data is no longer enough. To stay competitive, organizations are increasingly turning to demand sensing and forecasting, an approach that blends real-time data, advanced analytics, and AI to anticipate demand more accurately and respond faster to change. This shift is not limited to retail or manufacturing. Demand sensing is transforming how organizations across industries plan operations, allocate resources, and improve service levels. Below, we explore key industry use cases where demand sensing is delivering measurable value, and why businesses should care.   Why Demand Sensing Matters Demand sensing moves beyond static historical trends. It incorporates current, high-velocity data signals such as sales transactions, weather patterns, logistics feeds, economic indicators, and even social sentiment to generate short-term demand forecasts that reflect real-world conditions. The benefit is clear. Organizations gain better visibility and responsiveness across procurement, production, inventory, and distribution. Instead of reacting to outdated forecasts, they can make timely decisions that reduce costs, prevent stockouts, and improve customer satisfaction. FMCG, CPG, Retail, & E-Commerce Fast-moving…

At Manifest 2026, Scott Luton spent time with Josh Gruenstein, Co-Founder and CEO of Tutor Intelligence, to talk about a future that’s no longer theoretical: AI-powered robot workers operating inside America’s warehouses and factories. And this isn’t a science experiment. It’s already happening.   From MIT to the Warehouse Floor Gruenstein and his team came out of MIT’s Computer Science and AI Lab with a bold idea: build AI-powered robot workers that can handle the manual labor people don’t want to do. “We build physical robots,” Gruenstein explained. “We build AI models that enable robots to perceive their environments, and then we deploy those robots into factories and warehouses across the United States to do manual labor that people don’t want to do.” Unlike traditional automation projects that require massive capital outlays, Tutor Intelligence operates on a robots-as-a-service model. Companies can engage a Tutor robot for roughly $14–$18 an hour, creating a flexible, scalable path to automation without multimillion-dollar implementation risk.   Automation Isn’t New. AI Is Changing the Playbook. When asked about dominant supply chain themes, Gruenstein pointed to a constant drumbeat: automation. But 2026 feels different. “Automation is obviously a constant theme,” he said. “What really seems different…