The driver shortage and AI: what it does solve in planning, administration and recruitment, and what it does not

Why the shortage is a structural problem, and why AI does not add a driver

The driver shortage is not a temporary spike but a structural feature of the labour market: the outflow caused by an ageing workforce is large, and the intake of new drivers with a category C or CE driving licence and the accompanying code 95 (the professional driver qualification) is not keeping up. That is the central point to keep clearly in view with every story about AI: no algorithm drives an extra truck, and no model puts a driver on the payroll who is not there.

That does not mean that AI does nothing here. It means that the gain lies elsewhere: wasting less of your scarce drivers' and planners' time on work that can be done another way, and deploying and retaining the people you do have more effectively. Anyone who judges AI on 'does it solve the shortage' will be disappointed. Anyone who judges it on 'are we making better use of our drivers and hours' can get real value from it.

Planning: more trips from the same drivers

The most direct way in which AI eases the shortage is through planning. If you have fewer drivers than you would like, every trip that can be made more efficient counts, as does every empty kilometre you do not drive. AI-assisted planning software, such as route optimisation, can help make better use of the available driver hours, and above all help you replan faster when someone drops out.

An important point here: the European rules on driving and rest times in Regulation (EC) No 561/2006 still take full precedence. A plan that deploys a driver beyond what the law allows is not a gain but an infringement. Good software includes those rules as a hard constraint, rather than leaving the planner to check the plan against them afterwards.

• Faster replanning when someone reports sick or drops out, so that the trips still get done with fewer drivers.
• Better use of available driving time and fewer empty kilometres, so that the same drivers complete more useful trips.
• Flagging conflicts with the statutory driving and rest times before a driver sets off.
• Putting scenarios side by side at busy times, so that the planner takes a well-founded decision sooner.

Administration: giving hours back to the road and to planning

Every trip comes with administration: trip records, timesheets, consignment notes and CMR, loading and unloading slips, tachograph data and invoicing. Drivers do part of it themselves, and part is done by the planning department or the back office. Every hour that goes into it is an hour that does not go to driving or to real planning, and that weighs heavily when people are scarce.

AI can help here by reading documents and transferring data that is now retyped by hand, with a human checking the exceptions. That is exactly the kind of administrative work that, according to research by CBS, Statistics Netherlands (AI-monitor 2024), is one of the most common AI applications, after marketing and sales. The gain is not a spectacular innovation but time regained, and when staffing is tight that is valuable enough.

Do be critical of savings claims. How much time you actually regain depends on how your administration runs today and how clean your data and documents are. Ask a vendor for a trial on your own slips and forms, not for a general percentage from a sales pitch.

Recruitment and rostering: find people faster, keep them longer

With a structural shortage, recruitment is not an occasional job but an ongoing process, and retaining the people you already have matters just as much as new intake. AI can make the recruitment process faster and more consistent, and help to draw up rosters that match drivers' preferences. That last point bears directly on retention: irregular or unpredictable rosters are a well-known reason why drivers leave.

The support lies mainly in saving time and keeping track, not in taking over the decision on whom you hire or how you roster someone. Examples are drafting job adverts faster, organising responses, or working through roster options within the driving and rest times.

Note one limit that is especially important in recruitment: AI that assesses or selects candidates may fall under the stricter rules of the EU AI Act, and must not, in any event, lead to unfounded or unverifiable rejections. Choosing a person remains human work, with AI at most as an aid in preparation.

• Drafting job adverts and advertising copy faster and more consistently.
• Organising and pre-sorting incoming responses, with the selection left to a human.
• Working through roster options that fit both the demand for trips and drivers' preferences.
• Flagging patterns in absence or staff turnover early, so that you can take action on retention.

What AI does not solve

The honest answer remains: AI does not add a driver. It does not solve the problem of licences and intake, it does not take over the physical trip, and it does not reduce the structural shortage. What it does is find the slack in your existing staffing: more efficient planning, less administrative waste, and more targeted recruitment and rostering.

That is valuable, but it is not a miracle cure and certainly no substitute for good employment practices, training and an intake policy. Expect AI to ease the load on your people and make better use of your hours, not to solve the shortage. Anyone who starts with that expectation chooses the right applications and avoids disappointment over promises that cannot be kept.

The human decides and signs

At AIBA, our starting point is that the human decides and signs. For transport, that means in practice that the planner remains responsible for the plan, even if a system proposes it, and the haulier remains liable for compliance with the driving time legislation. The same applies to recruitment and rostering: the system prepares, the human decides.

Moreover, Article 4 of the EU AI Act (Regulation (EU) 2024/1689) has applied since 2 February 2025. Since the amendment by Regulation (EU) 2026/1744, in force from 27 July 2026, it has asked organisations to take measures that support the AI literacy of employees who work with AI systems. They do not have to guarantee a specific level. For planners, back-office staff and HR, what matters in practice is that they understand what a planning, administration or recruitment tool can and cannot do, where the assumptions and limitations lie, and when a proposal must be adjusted manually. That is not a formality but the basis for working responsibly with these tools; in our AI training for logistics (in Dutch), the team practises that on its own planning.

Start small and make it measurable. Choose one process where the shortage bites hardest, for example replanning after an absence or trip administration, and record how it works now before you introduce anything new. Only then can you judge whether AI support really frees up time or driver hours there.