AI Triggers 2,000 Logistics Job Cuts

The job cuts at WiseTech are heavily concentrated in software development and customer service, with some teams facing a 50% reduction in headcount. CEO Zubin Appoo has stated, "the era of manually writing code as the core act of engineering is over," pointing to a fundamental shift where AI agents will handle the bulk of software creation, with developers moving into oversight roles. This strategy extends to its recent $2.1 billion acquisition, the US-based cloud company e2open, which will also see significant workforce reductions. This move is part of a broader industry trend where logistics and supply chain management are aggressively adopting "Physical AI." Companies like Amazon, which deployed its millionth robot in 2025, and Walmart are using AI for everything from demand forecasting and route optimization to warehouse automation. This integration of AI with robotics is creating highly efficient, semi-autonomous warehouses that can operate with up to 25% fewer workers than manual facilities. The key technologies driving this transformation include Autonomous Mobile Robots (AMRs) and, increasingly, humanoid robots. While AMRs from companies like Locus Robotics are already common for transporting goods, humanoid robots from Agility Robotics and Boston Dynamics are being trialed by logistics giants like GXO and DHL for more complex tasks like picking and packing. These humanoids are designed to work in existing infrastructure built for people, minimizing the need for costly retrofitting. While roles like software development and order fulfillment are seeing automation, new specialized engineering roles are emerging. These include positions like "Robot Manager" or "Physical AI Fleet Orchestrator," which focus on overseeing and optimizing fleets of autonomous robots and drones. There's also a growing demand for AI Compliance Officers and AI Ethics and Governance Directors to ensure the safe and unbiased operation of these complex systems. For embedded systems and robotics engineers, this shift demands a multidisciplinary skillset. Proficiency in Python and C++ remains critical, alongside a deep understanding of the Robot Operating System (ROS) for developing scalable applications. Experience with sensor fusion—integrating data from LiDAR, cameras, and IMUs—is essential for creating the spatial awareness that allows autonomous systems to navigate dynamic warehouse environments. Beyond technical skills, there's a growing emphasis on "agentic AI," where systems act as independent agents to solve multi-step problems. This requires a move from simple rule-based programming to "Context Engineering," where engineers provide the right data and constraints for AI models to make real-time, autonomous decisions. This involves a strong foundation in machine learning, data science, and logical thinking to design, test, and debug these intelligent systems.