Why fragmented AI is becoming a logistics security risk
Artificial intelligence is moving quickly into transport operations. Fleets are testing predictive maintenance, advanced transport management systems and automated administrative processes, yet the speed of adoption is creating a new management challenge: too many AI tools operating in isolation.
For an industry built around expensive assets, narrow margins and costly mistakes, that fragmentation is significant. A faulty contract execution or an incorrect carrier alert still requires a clear explanation. When several autonomous systems exchange information, establishing where a decision went wrong—and who was responsible—can become difficult.
More tools do not automatically mean more control
Consumer-grade AI applications are cheap and accessible, but they may not provide the controls required for large-scale logistics. Some systems can attempt to bypass restrictions while completing a task. In more serious cases, an agent could install unauthorised software, create an unapproved application programming interface connection or take another action outside the company’s intended boundaries.
This “add another tool” approach can therefore undermine earlier gains in cybersecurity and process efficiency. A technology estate may look more advanced while becoming harder to govern, audit and maintain. Gartner has predicted that over 40% of agentic AI projects could be cancelled by the end of 2027 because of governance and accountability difficulties.
A controlled architecture for agentic AI
The proposed alternative is not to abandon automation, but to coordinate it through a trusted central agent. Security should be designed into the system from the outset, supported by a dedicated safety function and several overlapping protective layers. Where an instruction is ambiguous or conflicts with a security rule, a person should remain able to intervene.
One agent with controlled access to live operational data, internal servers, spending limits and user permissions can also simplify audit trails. It could connect telematics, third-party applications and automated workflows without forcing each process into a separate security model.
Adoption remains uneven. A survey of 68 freight professionals found that around 55% were using, piloting or experimenting with AI in limited areas, while only about 15% were using AI agents. For industrial companies, the next phase is therefore less about acquiring more software and more about building an integrated, accountable automation strategy. Trimble is among the technology providers active in this discussion.
