In many parts of the developing world, traffic congestion, rising freight volumes, and worsening air quality are the inevitable consequences of surging populations, rapid urbanisation, and fragile infrastructure. Growing prosperity in certain regions only adds more vehicles to roads and more goods to supply chains. To confront these challenges, artificial intelligence (AI) is emerging as a transformative tool — one that can open access to underserved communities, attract private investment, and redefine how people and cargo move from point A to point B.
Beyond the Hype of Self-Driving Cars
Autonomous vehicles (AVs) may dominate the headlines, but AI’s role in transport extends far beyond driverless cars. From predictive analytics that anticipate traffic surges to algorithms that optimise delivery routes and shipping schedules, AI technologies are already working behind the scenes to make journeys safer, faster, and cleaner. These solutions are being deployed not only in advanced economies but also in emerging markets where their potential impact is arguably even greater.
Tackling Efficiency Gaps
Developing countries often face disproportionately high logistics costs — sometimes two to three times greater, as a share of GDP, than in wealthier nations. The causes are many: outdated infrastructure, inefficient customs clearance, and fragmented supply chains. AI-powered e-logistics systems offer a way forward by matching shippers and carriers in real time, automating warehouse operations, and predicting demand with impressive accuracy. This tighter coordination not only reduces waste but also improves service reliability for both businesses and consumers.
Reliability as a Competitive Edge
Consistency is a hallmark of high-quality transport systems. In public transit, accurate journey time predictions can make the difference between full buses and empty ones. Ride-hailing platforms have already shown how AI can refine pick-up and drop-off estimates, even in unpredictable traffic. Extending these capabilities to trains, ferries, and bus networks could dramatically improve punctuality — and with it, public trust and ridership.
Reducing the Human Cost of Road Accidents
Inadequate infrastructure and poorly maintained vehicles contribute to alarming accident rates worldwide, yet human error remains a leading factor. Studies suggest that, in high-income countries, widespread adoption of autonomous systems could slash road fatalities by as much as 90% by mid-century. Even partial automation, such as advanced driver-assistance systems, has already demonstrated tangible safety benefits, with early deployments showing significant reductions in collision rates.
Driving Towards Sustainability
Transport accounts for roughly 23% of global CO₂ emissions linked to energy use. Without decisive action, this share could triple by 2050. AI can support environmental goals through route optimisation, fleet management, and fuel efficiency technologies. Innovations such as truck platooning — where vehicles travel in close formation to reduce drag — illustrate how AI can cut both emissions and operating costs simultaneously.
Balancing Innovation with Responsibility
AI’s capacity to reshape transport is vast, but its deployment is not without hurdles. From regulatory frameworks and infrastructure readiness to public acceptance and workforce adaptation, countries must address a host of issues to realise its full potential. When managed well, AI-enabled transport systems could deliver safer roads, more dependable services, and greener mobility — creating economic opportunities while building a more connected, sustainable future for all.
