Logistics is shifting from moving goods to moving intelligence. Powered by AI, automation, multimodal networks, and sustainability, the industry is building faster, more visible, and resilient supply chains for a future-ready 2026
In an industry evolving faster than ever, logistics is undergoing a profound shift, from moving goods to moving intelligence. This feature story explores how technology, data, sustainability, and purpose are reshaping every link of the supply chain. The Smart Shift is not just an upgrade; it is a redefinition of how logistics functions, responds, and creates value in an increasingly complex world.
This transformation, which we call The Smart Shift, is not just an upgrade. It is a redefinition of how logistics functions, responds, and creates value in an increasingly complex world. AI, automation, predictive analytics, and real-time orchestration are converging to empower smarter, safer, and greener operations. Reflecting on last year’s breakthroughs and anticipating next year’s transformations, industry leaders reveal how logistics is being redefined through intelligence, sustainability, and collaboration, setting the stage for a more agile and resilient 2026.
Digital forecasting and operational precision
Cargo operations today are no longer managed solely by experience or intuition. Digital tools are enabling predictive, precise, and real-time decision-making. Manish Agnihotri, CEO, Worldwide Flight Services (WFS), emphasises the role of technology in creating operational clarity: “Digital technologies are enabling real-time exchange of shipment and flight-planning data, helping cargo terminal operators and airlines plan resources with greater accuracy and efficiency. AI and machine learning are now central to forecasting and resource deployment, ensuring optimal allocation aligned to expected loads.”
A key enabler, Agnihotri explains, is the Performance Management Platform – Machine Learning Forecast (PMP MLF), which has been trained on ten years of operational data: “PMP MLF delivers accurate forecasts of cargo volumes by flight, truck, and day, supporting warehouses with precise forward-looking insights. This addresses a persistent 10–15 percent gap between staffing and actual workload. Currently, PMP MLF forecasts 9,842 flights and 6,216 truck movements per week across 75 warehouses in 13 countries, providing daily projections for tonnage, ULDs, and piece counts by mode, customer, and location, all integrated into planning tools for more reliable operations.”
Agnihotri also highlights WFS’s sustainability agenda: “In short-haul and regional airfreight, key measures include transitioning fleets to low-emission vehicles, shifting to renewable energy, and reducing plastic use, essential steps toward achieving a 50 percent reduction in Scope 1 and 2 emissions by 2030, as highlighted in the SATS-WFS 2025 Sustainability Report.”
With these tools, cargo operators gain not just visibility but predictability, reducing operational bottlenecks, optimising staffing, and ensuring smoother throughput even during peak periods. The integration of AI and ML into forecasting has become a critical differentiator in global air cargo management, where even small errors can create cascading inefficiencies across multimodal networks.
AI ensures optimal allocation aligned to expected cargo loads
AI and route optimisation
Beyond the skies, road logistics is increasingly shaped by AI and predictive analytics. Hemant Sikka, Managing Director, Mahindra Logistics, observes the radical impact of AI on operational efficiency: “AI has shifted route planning from guesswork to true precision. By analysing traffic, weather, and network conditions in real time, it identifies the smartest route rather than just the shortest one. This reduces empty kilometres, improves fleet utilisation, and enhances delivery consistency.”
Sikka points out the rise of new technologies alongside AI: “Electric trucks are becoming practical and scalable as charging networks expand, reducing emissions and operating costs while maintaining service quality. Autonomous systems, though still maturing, are already contributing to safer operations and greater long-haul efficiency. Real-time telematics offers immediate insight into driving behaviour, fuel patterns, and potential risks. It helps prevent incidents, boosts vehicle efficiency, and keeps dispatch teams aligned through live updates, significantly improving delivery reliability.”
In practical terms, this means fleets can be deployed dynamically, fuel consumption optimised, and empty runs minimised. Combined with electrification and autonomous technologies, AI is not just improving operational efficiency but also reducing the carbon footprint of road logistics. The convergence of digital intelligence with sustainable operations is steadily transforming fleet management into a science of precision and resilience.
AI identifies the smartest route, not just the shortest one
