The rise of artificial intelligence (AI) and automation is transforming industries worldwide, and the supply chain sector is no exception. As AI technologies evolve, they are increasingly able to carry out tasks that were once reserved for human workers, making processes faster, more efficient, and cost-effective. However, this also brings about the question: which supply chain roles will become obsolete in the face of emerging AI?
While AI promises to improve many aspects of supply chain management, it also means that certain roles may no longer be as relevant as they once were. Let’s take a closer look at which jobs within the supply chain may face obsolescence and why.
1. Data Entry Clerks
Data entry tasks, such as manually inputting shipment information, stock levels, and order statuses, are common in supply chain operations. However, AI-powered systems are now able to process and update data in real time without human intervention. These AI tools can automatically scan barcodes, track shipments, and update inventory databases seamlessly, reducing the need for human data entry clerks.
Impact: With AI taking over routine data input tasks, human involvement in these roles will significantly decline. Organisations will no longer need as many employees to enter or update information, as AI-powered systems can do this instantly and with fewer errors.
2. Inventory Managers (Traditional Role)
Inventory management has traditionally involved tracking stock levels, reordering items, and ensuring warehouses are adequately stocked. While this remains a critical function, AI has revolutionised inventory management by using advanced algorithms to predict demand, optimise stock levels, and automate replenishment. AI tools can predict fluctuations in demand, supply chain disruptions, and stock shortages with impressive accuracy, minimising human intervention in day-to-day inventory decisions.
Impact: Traditional inventory management roles, which rely heavily on manual stock tracking and reordering, will be diminished as AI takes over much of the forecasting and inventory optimisation process. While human oversight may still be needed for strategic decisions, much of the repetitive work can be handled by AI.
3. Warehouse Workers (Basic Tasks)
Warehouse operations have historically required a significant workforce to manage tasks like receiving, storing, and dispatching goods. However, with the development of AI-powered robotics and automation systems, these tasks are becoming increasingly automated. Robots can transport goods, sort inventory, and even pack items without human assistance. Companies like Amazon have already implemented AI-driven robots to handle warehouse duties, reducing the need for human workers.
Impact: Basic warehouse tasks that do not require critical thinking or manual dexterity, such as picking and packing goods, will increasingly be done by robots and automated systems. Warehouse workers will still be required for more complex tasks or to oversee operations, but many traditional roles will see a reduction in demand.
4. Procurement Specialists (Routine Tasks)
Procurement specialists are responsible for sourcing materials and products from suppliers, negotiating prices, and ensuring timely delivery. AI is making strides in this area by analysing supplier data, forecasting demand, and identifying the most cost-effective purchasing options. Machine learning algorithms can assess vast amounts of data to suggest optimal suppliers and pricing strategies, reducing the need for human involvement in many procurement tasks.
Impact: Procurement roles focused solely on administrative tasks, such as price negotiation and order placement, may be replaced by AI-powered procurement platforms. While human procurement professionals will still be needed for complex negotiations or building relationships with suppliers, routine procurement activities are increasingly handled by AI.
5. Transport Planners
Transport planners are responsible for planning the routes and schedules for deliveries, taking into account factors such as cost, time, and distance. AI-powered systems can optimise these processes by analysing traffic data, weather conditions, and real-time vehicle locations. Autonomous vehicles and drones are also becoming more viable for supply chain transportation, reducing the need for human drivers and transport planners.
Impact: With AI’s ability to predict traffic patterns, optimise delivery routes, and even operate autonomous vehicles, traditional transport planning roles will see a reduction in demand. AI can automate the planning process and even carry out deliveries, reducing the need for human transport planners in certain sectors.
6. Customer Service Representatives (Routine Inquiries)
Customer service teams within supply chains are often tasked with answering questions about order status, delivery times, and product availability. AI-powered chatbots and virtual assistants are increasingly able to handle these types of inquiries without human intervention. These AI systems can quickly retrieve information from databases and provide customers with accurate responses, eliminating the need for human representatives in basic customer service functions.
Impact: While human customer service agents will still be required for complex or escalated issues, AI is taking over the more routine aspects of customer service. As a result, many customer service positions focused on simple inquiries or order tracking will likely become obsolete.
7. Supply Chain Analysts (Routine Analysis)
Supply chain analysts are responsible for gathering and interpreting data to identify inefficiencies, trends, and areas for improvement. While human analysts will still be needed for complex decision-making and strategic insights, AI is increasingly able to process vast quantities of data and generate predictive models. Machine learning algorithms can detect patterns in supply chain data and make recommendations, reducing the need for human analysts to spend time on routine analysis.
Impact: Routine data analysis tasks, such as spotting trends and generating reports, will be increasingly automated by AI systems. Human analysts will still be required for higher-level decision-making and strategic guidance, but the need for manual data processing will diminish.
8. Purchasing Assistants
Purchasing assistants are responsible for processing orders, managing vendor communications, and ensuring timely deliveries of materials. AI is now able to manage these tasks through predictive analytics and automated purchasing systems. By evaluating supplier performance, lead times, and market conditions, AI systems can make purchasing decisions, order materials, and track deliveries with little to no human involvement.
Impact: AI’s ability to predict and automate procurement processes means that purchasing assistants will face decreasing demand. Many of the routine tasks they perform, such as placing orders or communicating with vendors, can now be handled more efficiently by AI.
Conclusion
While AI promises to transform the supply chain industry, it’s clear that not all roles will disappear. Instead, many jobs will evolve, with professionals focusing more on strategic decision-making, problem-solving, and leadership while AI handles routine tasks. Roles that involve high levels of human judgement, relationship management, and creative problem-solving are less likely to be replaced, as these are areas where AI is still limited.
The key to thriving in the AI-driven supply chain landscape will be adaptability. Supply chain professionals must embrace new technologies, upskill, and shift towards roles that require a human touch. By doing so, they can ensure that they remain an essential part of the evolving supply chain ecosystem.
As AI continues to revolutionise the sector, those working in supply chain roles should prepare for a future where collaboration with technology will be the norm, and automation will be seen as a tool to enhance productivity and efficiency
