Become a TechRadar Insider
Supply chains used to be judged on the average day. Now they’re defined by the worst day.
Volatility has become the operating environment: port congestion, extreme weather, geopolitical disruption, sudden demand spikes, and supplier instability.
Against that backdrop, artificial intelligence and advanced technologies like RPA, IoT, and machine learning are reshaping supply chains from reactive networks into proactive, resilient ecosystems.
VP Marketing for SAP’s Supply Chain solutions.
As a result, we are seeing the job functions shifting from manual execution to strategic oversight, data interpretation, and human-AI collaboration.
Will AI take my job?
When discussing AI, one of the most common questions is “Will AI replace my job?” And my favorite response is that AI will not replace your job, but people leveraging AI will replace those that do not.
As with previous industrial revolutions, some jobs (usually the mundane and repetitive) will be automated. However, many more value-added and higher-skill jobs will be generated. In fact, the World Economic Forum projects AI will create 170 million jobs while displacing 92 million globally by 2030, yielding a net gain.
Automation of Routine Tasks
AI excels at repetitive, data-heavy work, while boosting efficiency. Inventory clerks, data entry specialists, pickers, packers, and basic freight coordinators are among the most impacted, as physical AI, robotics, and automation software handle counting, sorting, and order processing.
Freight dispatchers are seeing transactional duties like load assignments automated, shrinking tasks from 20 minutes to under one, and IoT sensors provide real-time GPS fleet tracking, resulting in visibility and traceability. These changes cut errors, labor costs, and delivery times, but they demand workers adapt beyond routine operations.
Emergence of Strategic Roles - From data entry to supply chain orchestrator
In the future, we will see new, more strategic roles, focused on catering to human ingenuity to make decisions where AI becomes the partner to support that decision. These roles will empower employees with the tools needed to prioritize orchestration over execution. For example, robot fleet managers troubleshoot warehouse bots, predictive logistics operations managers forecast disruptions, and supply chain agent managers supervise AI agents as sales management guides teams.
There may be opportunities for resilience architects, who simulate shocks and rewire business networks for agility, and data stewards, who use AI to analyze supplier data, predict issues, and identify savings. Digital operators will leverage AI for real-time load matching and predictive maintenance, turning logistics into proactive optimization. These roles blend operations, technology, and strategy, creating new career pathways for more diverse backgrounds.
Building trust and embracing AI
As with any new technology shift, organizations have to address the fear, uncertainty, and doubt that comes with it:
Psychological Effect – As AI becomes more embedded in day-to-day work, it can feel threatening to employees. That is something that can only be overcome by showing the value at both the individual and organizational level. For example, how can AI empower employees to do their jobs more efficiently? Warehouse managers, for instance, could use AI-powered inventory systems to predict stockouts and optimize replenishment, reducing waste, and ensuring product availability.
Trust and embrace - Organizations must create an environment where employees feel empowered to experiment with AI. For example, transportation planners can leverage AI-enabled route optimization tools to minimize fuel costs and delivery times, adapting dynamically to traffic or weather conditions.
Transparency – When introducing new business software systems or technologies, it’s critical to bring employees along in the process, engaging them in early and ensuring they understand both the purpose and impact of these changes.
Upskilling existing and new team members
Upskilling is essential, with digital curiosity and strategic agility at the core. Companies that invest in training will see faster adoption and greater long-term value from AI.
Workforce concerns can be addressed through targeted AI training programs that demonstrate how effective AI use can empower employees. For example, human-AI collaboration workshops can help employees interpret AI-generated insights and handle exceptions, fostering greater collaboration between humans and AI agents.
Workers will need to be proficient in AI tools, data analytics, machine learning basics, as well as the ability to collaborate with AI to interpret insights. This can look like demand planners and procurement analysts using predictive models for accurate forecasting, while warehouse leads will manage hybrid human-robot teams.
Challenges and Opportunities Ahead
Although there are transitional risks such as skill gaps and resistance associated with AI, the benefits are clear. AI is proving to be a powerful ally in protecting workers by reducing exposure to hazardous work, while also opening the door for higher-level work.
Supply chain professionals who embrace this shift and recognize the value of working alongside intelligent systems will thrive in the age of AI. The future favors those evolving with technology – that is why predictive visibility and agentic AI demand proactive mindsets, not just execution.
We feature the best online courses and online class sites.
This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.
The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit