Artificial intelligence is beginning to change logistics through a series of measured operational improvements rather than a single technological leap. For transport companies, the most immediate opportunities lie in handling routine information work: processing emails, amending orders, checking delivery windows and comparing planned schedules with actual results.
Ben Glossop, Vice President of Sales at Aptean, points to a customer receiving 70 to 100 daily requests to alter delivery times. An AI agent can read each request, update the plan and calculate the effect on mileage, time and vehicle capacity. Changes inside predefined limits may be accepted automatically; requests carrying substantial cost or requiring another vehicle are passed to a planner.
Controlled automation, not unchecked autonomy
The model keeps operational authority with the customer. Agents can initially ask for approval, learn from repeated decisions and gradually handle familiar cases independently. This approach is particularly relevant in logistics, where industry terminology, service commitments and vehicle restrictions make context more important than generic text-processing capability.
Aptean is also developing natural-language access to transport planning through Ask Paragon. Instead of manually adjusting numerous routing parameters, planners can ask about route performance or the likely impact of changing delivery windows. A broader integration layer, AppCentral, is intended to help users query information across transport, warehouse and other business systems.
Measuring value beyond labour savings
The first reported benefit is time recovered from administrative work, but the potential impact is wider. One developing agent could identify routes forecast to run below 80% utilisation, contact customers about additional orders and alert an account manager where intervention is needed. Better load factors could improve asset use without reducing service flexibility.
Implementation remains critical. A routing deployment once appeared to raise scheduling costs by 20%, but the comparison involved different operating rules: the new system enforced delivery windows, driver hours and vehicle restrictions that planners had not always applied consistently. Cost, compliance and service quality therefore need to be assessed together.
Aptean Ascent extends this principle into an outcome-focused model combining software, process changes, benchmarking and ongoing support. The longer-term objective is not to remove people from logistics, but to shift their time from repetitive administration towards decisions requiring judgement—while proving that gains survive disruptions such as road closures, weather and staff absence.
