The shift is already under way. AI systems no longer just surface recommendations for humans to act on; they plan, write code, identify exceptions and execute complex workflows with decreasing human touch points. That capability gain is real, but it arrives with an accountability gap that logistics operators have not yet resolved.
When a human makes a consequential call and it goes wrong, the chain of responsibility is clear enough. When an autonomous system does, it is not. The question of who carries the cost sits uneasily between the operator who deployed the tool, the vendor who built it and the client whose stock, shipment or invoice was affected.
Wajahat Akram, CTO at FLOX, works through that question directly in this Chain Reaction episode. The conversation covers how accountability should be structured as AI takes on more operational weight in multi-party logistics, where the line sits between a system that assists and one that acts and what governance looks like when the decision-maker is not a person.
For UK and EU shippers and logistics providers already trialling AI in exception management, demand sensing or financial reconciliation, these are not theoretical concerns. Getting the accountability structure right before something goes wrong is considerably cheaper than working it out afterwards.
