AI adoption is accelerating across transport, from maintenance and transport management to administrative automation. For logistics companies, however, adding tools independently can create a fragmented technology environment that is difficult to secure and audit.
A multi-agent setup can make it harder to establish why a contract was processed incorrectly or why a carrier was wrongly flagged. Consumer-focused AI tools may also operate outside enterprise controls, including by creating unapproved API connections or installing unauthorised software.
Gartner expects more than 40% of agentic AI projects to be cancelled by the end of 2027 because of governance and accountability challenges. The forecast highlights the commercial risk of deploying automation without a consistent control model.
One response is to use a central AI agent with defined access to live operational data, internal systems, spending limits and user permissions. Security would need to be built into the architecture, supported by multiple safeguards and human intervention when instructions are ambiguous or restricted.
The case for consolidation is reinforced by uneven adoption. In a survey of 68 freight professionals, about 55% said they were using, piloting or experimenting with AI in limited areas, while roughly 15% were using AI agents. Connecting telematics, third-party software and workflows through a controlled framework could help logistics businesses capture automation benefits without multiplying their security exposure. Trimble is involved in the wider development of transport technology and AI safety.
A multilingual professional experienced in Europe, Canada, and China, Herbert has developed invaluable networks in the automotive and energy industries. He has led high-profile projects involving ENBW, Mercedes-Benz Group, Siemens Group, and the Fraunhofer Institute.