Featured by Matthew Otabe
For decades, Nigeria’s road infrastructure has remained at the centre of the country’s economic and social development challenges.
From highways linking major cities to rural roads connecting farmers to markets, the condition of the nation’s road network affects virtually every aspect of daily life. Poorly maintained roads contribute to traffic congestion, vehicle damage, accidents, delayed movement of goods and people, and increased transportation costs.
With more than 200,000 kilometres of roads spread across the country, the challenge is enormous. But as infrastructure demands continue to grow and resources remain limited, stakeholders in Nigeria’s highway and transportation sector believe the country can no longer depend solely on conventional approaches to road planning and maintenance.
They are turning increasingly to Artificial Intelligence (AI).
The message was emphatic at an international training programme on AI Applications for Road Management, organised in Abuja by the Nigerian Institution of Highway and Transportation Engineers (NIHTE) in partnership with the International Road Federation (IRF).
The programme brought together engineers, policymakers, regulators, government officials, development agencies and private-sector professionals to examine how emerging technologies could transform the way Nigeria plans, constructs, monitors and maintains its roads.
From reactive to predictive maintenance
One of the strongest arguments emerging from the workshop was that Nigeria must move away from a system where roads are repaired largely after they have deteriorated or failed.
Stakeholders argued that AI, combined with reliable data and sensors, could allow authorities to identify potential failures before they become major problems.
Acting National Chairman of NIHTE, Engr. Dr. Bola Mudasiru, said the country’s traditional methods of road management were no longer sufficient to address the increasingly complex challenges facing the sector.
According to him, AI could provide solutions across the entire life cycle of road infrastructure, from planning and construction to maintenance and eventual rehabilitation.
Its applications, he said, include predictive maintenance, traffic-flow optimisation, asset monitoring, road safety and climate resilience.
“AI offers practical solutions across the entire life cycle of road infrastructure — predictive maintenance, traffic flow optimisation, asset management, safety enhancement and climate resilience,” Mudasiru said.
The significance of predictive maintenance is particularly important for Nigeria, where limited resources often mean that authorities must make difficult decisions about which roads receive attention first.
Rather than waiting for roads to deteriorate beyond repair, data-driven systems could help identify those requiring urgent intervention and determine the most appropriate maintenance strategy.
Data could become the new foundation of road management
For Martins Van Gils of the International Road Federation, the future of road maintenance lies in making decisions based on evidence rather than routine.
He advocated a predictive and risk-based approach that would enable road authorities to determine where, when and why maintenance should be carried out.
Van Gils said technology and sensors could help authorities identify emerging risks and potential failure points, allowing maintenance to be undertaken before costly damage occurs.
“With the right technology and sensors, we can make better decisions on what maintenance actually needs to be carried out in a preventative way,” he said.
But his message came with an important warning: AI should not become technology for technology’s sake.
He cautioned authorities against installing sensors everywhere simply because they are available.
Instead, technology should be deployed strategically in locations and on infrastructure assets where the information generated would have the greatest value.
The reason is simple. Sensors themselves can fail, produce inaccurate information or generate false alarms. Without competent professionals to interpret the information, sophisticated technology could create additional problems rather than solve existing ones.
For Van Gils, the objective is therefore not to replace engineers with machines but to give engineers better information with which to make decisions.
AI and the climate challenge
Nigeria’s road infrastructure is also increasingly exposed to the effects of climate change.
Flooding, erosion and extreme weather events have become major threats to roads and bridges in different parts of the country.
Mudasiru said AI-powered models could help engineers predict flooding and erosion patterns and develop adaptive road designs capable of withstanding changing environmental conditions.
This could prove particularly valuable in vulnerable communities where the destruction of roads by flooding can isolate entire populations and disrupt agricultural and commercial activities.
With sufficient historical and real-time data, AI systems could potentially identify areas at high risk of flooding, monitor changes in road conditions and support early intervention.
The technology could therefore shift road management from simply responding to disasters to anticipating them.
A smarter approach to scarce resources
The challenge, however, is that technology cannot eliminate Nigeria’s infrastructure funding constraints.
Rather, stakeholders believe it can help the country obtain greater value from the resources available.
Van Gils said predictive and risk-based maintenance could enable authorities to prioritise interventions and stretch limited budgets across a wider road network.
Instead of spending heavily on roads only after they have suffered significant deterioration, authorities could use data to determine the most cost-effective intervention at the right time.
This, stakeholders argue, could reduce the frequency of major road failures and ultimately lower long-term maintenance costs.
The approach could also improve transparency in infrastructure spending by providing clearer evidence for why particular roads are prioritised over others.
Building Nigeria’s own digital road map
Nigeria is not starting entirely from scratch.
Representing the National Coordinator of the Rural Access and Agricultural Marketing Project (RAAMP), Engr. Bukar Gana disclosed that the agency, working with the World Bank and the French Development Agency, had developed the Nigeria Rural Infrastructure Management System.
The platform has digitised information covering more than 100,000 kilometres of rural roads.
Its database includes information on road conditions, pavement types, roughness indices, bridges and the socio-economic characteristics of communities along the road network.
That information already provides a foundation for data-driven road management.
The next step, Gana suggested, is to determine how AI can make the system even more useful by improving road-condition assessment, maintenance prioritisation and resource allocation.
This could be particularly significant for rural Nigeria, where road access directly affects agriculture, healthcare, education and access to markets.
Human intelligence still matters
While the enthusiasm for AI was evident throughout the programme, speakers repeatedly stressed that the technology must remain under human supervision.
The President of the Council for the Regulation of Engineering in Nigeria (COREN), Engr. Prof. Sadiq Zubair Abubakar, said Nigerian engineers must acquire competence in AI if they are to remain relevant in an increasingly technology-driven infrastructure sector.
He noted that AI could help the profession move from reactive and remedial maintenance towards proactive and predictive interventions.
But he warned against blind dependence on artificial intelligence.
Professional ethics, accountability, public interest and cost-effectiveness, he said, must remain central to engineering decisions.
That position was echoed by Van Gils, who emphasised that human judgement and practical experience would remain indispensable.
The message is clear: AI can analyse enormous quantities of information and identify patterns that humans may miss, but the final engineering decision must still take into account professional experience, local realities and public safety.
Indigenous engineers must not be left behind
The President of the Nigerian Society of Engineers and chairman of the occasion, Engr. Ali Alimasuya Rabiu, described AI as a transformative force already reshaping infrastructure planning and management globally.
He said AI-powered systems were revolutionising predictive maintenance, traffic management, pavement performance monitoring, asset management and transport safety.
But Rabiu also raised another critical issue: the role of Nigerian engineering firms.
He called for greater participation of indigenous professionals and companies in the planning, design, construction, rehabilitation and maintenance of the country’s roads.
According to him, Nigerian engineers have the expertise needed to execute major infrastructure projects, while greater reliance on local professionals would strengthen capacity, create employment and promote technology transfer.
His position underscores an important dimension of the AI debate. The technology will only transform Nigeria’s infrastructure sector if Nigerian professionals possess the skills to develop, operate and adapt it to local conditions.
Government embraces technological transition
Minister of Regional Development, Engr. Abubakar Momoh, said roads remained indispensable to connecting communities with markets, schools, hospitals and agricultural value chains.
He said the Federal Government was investing in roads, bridges and other critical infrastructure across the regions, but stressed that newly constructed assets must be properly monitored and maintained throughout their useful life.
AI, he said, could assist road managers in detecting defects, predicting deterioration, monitoring infrastructure performance and prioritising maintenance.
“This is why this kind of workshop is very important, so that practitioners can continually update themselves on modern realities, because the world is rapidly growing in terms of innovation and technology,” Momoh said.
He urged NIHTE and other professional bodies to extend the knowledge acquired at the programme to government agencies and regional development commissions through additional capacity-building initiatives.
The road ahead
Perhaps the most important lesson from the Abuja training is that adopting AI is not simply about purchasing sophisticated equipment or installing sensors.
It requires a broader transformation in the way Nigeria manages infrastructure.
That transformation includes collecting reliable data, building digital infrastructure, training professionals, establishing appropriate standards, protecting data, ensuring transparency and developing systems capable of turning information into practical decisions.
Mudasiru also stressed the importance of professional ethics, inclusivity, data privacy and sustainability as technology advances.
For a country grappling with a huge maintenance backlog and limited resources, the opportunity is potentially significant.
If properly deployed, AI could help Nigeria understand its roads better, identify problems earlier, prioritise scarce funds, improve road safety and design infrastructure capable of surviving increasingly harsh environmental conditions. But the technology itself will not repair Nigeria’s roads.
Its success will depend on the quality of the data fed into it, the competence of the professionals using it, the integrity of the institutions deploying it and the willingness of government to act on the information generated.
As Nigeria searches for a sustainable solution to its infrastructure deficit, the emerging consensus among highway and transportation experts is that the country must move from repairing roads after failure to predicting and preventing failure before it happens.
That may ultimately be where AI makes its most important contribution—not by replacing the engineer, but by giving the engineer the intelligence needed to build and maintain a smarter, safer and more resilient road network.
