Artificial intelligence and road freight transport: what practical applications for carriers?
Artificial intelligence is no longer limited to technology showcases or consumer tools. In road freight transport, it is gradually being integrated into business software and management systems to automate time-consuming tasks and improve operational performance. But where does adoption really stand today? What benefits does it bring to carriers? And what developments can be expected in the coming years?
Artificial intelligence and road transport: a decision-support tool rather than a replacement
Hervé Rébillon: Today, artificial intelligence is present in many aspects of daily and professional life. Can we now say that it has become part of the road transport toolkit?
Arthur Awaki (Dashdoc): Absolutely. Although generative AI has received significant media attention in recent years, AI has been present in transport for much longer. The first route optimisation algorithms emerged in the 2000s and already contribute to improving logistics operations.
Today, large language models (LLMs) are opening up new possibilities by automating an increasing number of administrative and operational tasks.
Hervé Rébillon: Should artificial intelligence be viewed as a new actor within the company or simply as a tool?
Arthur Awaki (Dashdoc): AI will not replace people. In transport, driver management, operations management and customer relationships remain at the core of the business. However, it can automate repetitive and time-consuming tasks such as data entry, checks and administrative verifications.
The primary objective is to free up time so that teams can focus on higher value-added activities.
Hervé Rébillon: Are transport companies still cautious about AI?
Arthur Awaki (Dashdoc): Concerns still exist, but they are diminishing as practical applications become more widespread. Adoption is not based on belief, but on tangible results. When a carrier sees that a tool saves time or improves productivity, the value becomes obvious.
Some concerns remain regarding loss of control or the reliability of automated decisions. This is why current solutions still incorporate human validation to ensure trust in the process.
How AI automates administrative tasks in road freight transport
Hervé Rébillon: In practical terms, how can artificial intelligence help transport companies on a daily basis?
Arthur Awaki (Dashdoc): One of the most widespread use cases is the automated creation of transport orders from documents received by email.
Using OCR technologies and AI models, a system can automatically analyse a transport document, identify the customer, the goods, pickup and delivery locations, as well as operational constraints. All this information is then pre-filled into the TMS.
The user only needs to carry out a quick verification before validation, significantly reducing data-entry time.
Hervé Rébillon: How have these solutions been received?
Arthur Awaki (Dashdoc): The response has been very positive. Professionals generally consider manual data re-entry to be a low-value task. Automating it saves considerable time while reducing the risk of errors.
Success rates now regularly exceed 90 per cent, which is a major factor in the widespread adoption of these tools.
Hervé Rébillon: Can AI support other processes as well?
Arthur Awaki (Dashdoc): Yes, the possibilities are extensive. We are notably working on the automated verification of subcontractor invoices. AI compares invoiced amounts with the data recorded in the TMS in order to identify any discrepancies.
Beyond time savings, this helps protect margins and prevent invoicing errors that can directly impact profitability.
AI agents: what opportunities lie ahead for carriers?
Hervé Rébillon: We hear more and more about AI agents. How do they differ from traditional artificial intelligence?
Arthur Awaki (Dashdoc): Traditional AI generally performs a specific task for which it has been designed. An AI agent has greater autonomy in carrying out its missions.
For example, it can receive a request such as 'Which transports were completed yesterday?' and then independently perform the necessary steps to retrieve information, analyse data and provide a relevant summary.
Hervé Rébillon: What developments can we expect next?
Arthur Awaki (Dashdoc): Over the coming years, increasingly autonomous agents should emerge, capable of performing checks, searches and analyses with minimal human intervention.
The main limitation today remains the lack of turnkey solutions specifically designed for road transport. However, technology is evolving rapidly and practical applications are expected to multiply in the years ahead.
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While artificial intelligence will not replace the women and men who keep the road freight industry moving, it is gradually becoming a powerful performance driver for businesses. Administrative task automation, margin protection, process optimisation and the development of AI agents are creating new opportunities across the sector.
These topics will be at the heart of discussions during SOLUTRANS 2027 and the Rencontres de la Filière, where road freight transport stakeholders will share their experience and work together to build the solutions of tomorrow.