Engineering the leap: Why AI could be Ghana and Africa’s next infrastructure advantage in transportation

Once in a while, a development emerges that permanently alters the way society works. The electric light extended productive hours beyond sunset. The computer transformed how information is processed. COVID-19 redefined where and how work happens. Artificial intelligence belongs in that same category and for engineers in Ghana, the timing could not be more significant.

Africa has seen this pattern before. For decades, millions of Ghanaians had no bank account simply because the branch infrastructure did not exist. Then mobile money arrived and changed the equation. Rather than replicating banking systems built elsewhere over generations, Ghana took a different path, and today mobile financial services are woven into everyday life. AI offers transportation engineering the same kind of shortcut. We do not need decades of embedded sensors or costly traffic counters before we can make intelligent decisions about our roads. Smartphone GPS traces, satellite imagery, and low-cost IoT devices already generate what AI models need to optimise traffic flow, predict pavement deterioration, and model freight demand at a fraction of what traditional data collection once cost. AI offers us an opportunity not to catch up but to bypass an entire generation of inefficiency.

For many years, Ghanaian engineers worked within constraints that limited what could be achieved. Sophisticated software came with licensing costs beyond the reach of most organisations. Analytical tools were built for North American or European conditions and specialised analysis often depended on external expertise. Those barriers are rapidly diminishing. AI-assisted development now enables engineers to build customised tools calibrated to local conditions at a fraction of historical costs. The question is no longer whether the technology exists, but rather what challenges we choose to solve and whether we are collecting the right data to solve them effectively. We already possess the technical principles and the practical understanding of local conditions. Therefore, the shift required is not merely technological but rather a mindset that sees innovation as something we create, not something we import.

The applications are neither theoretical nor distant. AI-powered pothole detection systems can analyse motion data from ordinary smartphones mounted in vehicles, allowing agencies to identify deteriorating pavement and prioritise maintenance resources far more effectively than periodic inspections alone. Along Accra’s N1 corridor, machine learning models can analyse traffic volumes, weather conditions, and event patterns to forecast congestion.
Perhaps nowhere is the opportunity more immediate than in Ghana’s trotro network.

This informal minibus system moves hundreds of thousands of people daily yet operates almost entirely on instinct. Drivers choose routes by feel, fares are set by negotiation, and passengers are left with no reliable way to know when the next vehicle will arrive or which route serves them best. This is not a failure of its operators. It is a data problem, and data problems are precisely what AI is built to solve.

GPS-enabled phones in trotros can map real route patterns, identify coverage gaps, and predict demand by corridor and time of day. AI-powered passenger apps, built for low-bandwidth environments and local languages, can provide real-time arrival estimates and reduce the uncertainty that makes the system frustrating for so many commuters. The trotro is not a problem to be replaced. It is an asset to be understood and AI gives us the tools to finally understand it at scale.

Ghana’s engineering profession has always played a central role in building the infrastructure that supports national growth. AI does not replace that responsibility; it expands our capacity to fulfil it. The countries that benefit most will not necessarily be those with the largest budgets, but those whose engineers have the confidence to build solutions for their own realities. We understand the principles. We understand the challenges. Now is the time to build the future we want to see.

About the Author
Yaa Amanua Osafo, PE is a licensed professional engineer with extensive experience in transportation infrastructure, traffic operations, and road safety. After nearly a decade of practice across diverse geographical and economic contexts in the United States, she is returning to Accra bringing with her a wealth of technical expertise.

She serves as President of the Ghana Transportation Professionals Forum and works with InfiniCity Labs, a Ghanaian-owned AI company building smart solutions for Africa’s development. Amanua believes the next chapter of Ghana’s infrastructure story will be written by engineers who know the terrain, own the tools, and have the courage to build for themselves.

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