Agentic AI is beginning to take over parts of the routine decision-making that planners and warehouse supervisors have traditionally handled. Systems can reroute shipments, adjust transport capacity, anticipate inventory shortages and reorganise picking sequences without waiting for a person to approve every step.
That shift does not remove the need for logistics expertise. It changes where expertise is applied. Staff must be able to judge whether an automated instruction makes operational sense, recognise when the system is outside its limits and use a fallback process if the technology is stopped.
Oversight is a workplace capability
The EU AI Act says people assigned to oversight should understand an AI system’s capabilities and limitations, avoid relying on its output automatically, interpret recommendations correctly and intervene when necessary. In practice, that means training tied to the job rather than a generic online course.
A shift manager may need to know which data feeds the agent, where errors commonly occur and who has authority to switch it off. A warehouse operative or driver needs a clear route for reporting an instruction that appears unsafe or implausible. Planners also need enough time and manageable workloads to review recommendations properly; a queue of hundreds of approvals can turn supervision into a rubber stamp.
Work allocation demands extra care
Systems that allocate tasks or evaluate performance using behaviour, personal characteristics or productivity can enter the high-risk area of European AI regulation. Employers therefore need to understand how automated tools affect privacy, performance management and career prospects, alongside their existing employment obligations.
Companies should identify the owner of each automated decision, document which actions require approval, measure review volumes and practise operating manually. These steps build transferable skills: critical judgement, exception handling, process knowledge and confidence in challenging a machine recommendation. The logistics workforce of the agentic era will not simply operate software; it will supervise an increasingly active digital colleague.