What role does AI play in improving Africa’s energy access?

Every day, behind the scenes, artificial intelligence and machine learning are changing how people operate—from communication, navigation, and internet searches to the use of ‘smart’ technology. The effectiveness of these tools and the resulting benefits are heavily reliant on sustainable energy access. In an article by our Data Innovation Lead, the question was raised: could AI be a potent tool in addressing some of the world’s most pressing development challenges? The answer: potentially yes.  

In this blog, we want to look at how this ‘potential yes’ in AI’s ability to bring transformation might address some of the challenges for Africa's energy sector.

The need for sustainable energy

The Sustainable Development Goals (SDG 7) ensures access to affordable, reliable, sustainable, and modern energy for all countries. With its large population, addressing Africa’s energy access challenges is essential and urgent. The energy sector in Africa is currently facing a pressing crisis as countries grapple with several issues, notably limited resources, limited access to electricity, and a heavy reliance on fossil fuels.  

The underlying challenges are complex, including inefficiency, unreliable grids, and insufficient investment in modernisation. The lack of sustainable energy affects multiple sectors, including education, water, sanitation, and health. A quote, “Close your eyes and imagine a hospital without electricity. Doctors delivering babies in the dark. Pregnant women bringing their flashlights or lanterns and buckets of water to the delivery room” from USAID Power Africa Annual Report 2023 about the need to find solutions to powering healthcare creates a vivid image of the scale of the challenge.  

To frame the situation better:

• Every African country has its specific context, needs, and constraints.
• Improving energy access requires resource allocation, international collaboration, innovation, and locally-led solutions.  
• Artificial Intelligence is simply the process of making machines learn from experience, adjust to new inputs, process large amounts of data, and perform human-like tasks.
• Digital technologies, including AI, are not just tools but strategic assets in our transition from traditional power systems to modern, efficient, and low-emission systems.  

AI is more than a buzzword, it is an opportunity

Some African leaders struggle to provide their citizens with electricity to light their homes, refrigerate their food, or keep cool in severe weather conditions exacerbated by climate change. To these leaders, the investments required to reap the benefits of AI could seem daunting. However, therein lies the opportunity to nurture the relationship between the public and private sectors (technology developers and private sector companies, etc.) to collaborate and scale the integration of AI with energy systems.  

For example, some electricity distribution companies struggle with revenue to stay in business. AI can support improvements in revenue collection and reduce technical issues. These companies can use the synergy between AI and ‘smart’ meters to enhance predictive capabilities and optimisation for more reliable forecasting of energy loads and usage, etc. The private sector could collaborate with government agencies on system integration, capacity building, and enabling environment initiatives to deliver a win-win ultimately: the government would provide electricity more reliably to the citizenry, and the private companies would meet their profitability goals.  

Data-driven power

The Virtual Power Plant (VPP) model, powered by AI, is another example of the potential. VPPs create an integrated and interconnected system that can share resources (solar panels, wind turbines, storage systems, etc.) over large geographic areas. In South Africa, some plans are underway to use AI, as described in this article, SA’s fast-growing numbers of virtual power plants to be optimised with AI. While leading a major initiative to support the Nigerian government in reforming its oil and gas sector, we worked on initiatives focusing on how satellite technology could identify and measure gas flares, enhance the ability of regulators to reduce emissions, and support initiatives to use gas for more productive purposes including generating power for the country. It was clear that AI could have a transformative impact on this process in the future and increase the reliability of the data produced.  

In Ethiopia, we worked on identifying the potential for AI to support energy system improvements. In this project, we examined the use of machine learning (AI) to train computers to interpret satellite imagery and identify land under irrigation by diesel pumps and non-diesel pumps. The aim was to identify latent demand for electricity to help planners identify potential grid extensions that would provide the best return on investment.  Using satellite data and machine learning is potentially a lot quicker than carrying out large ground-level physical surveys to get this information.

The key challenges

However, there are challenges. AI relies on the data given, so its decisions would also be incorrect if the data is incorrect. This means there needs to be access to the necessary skilled personnel and computing power to support machine learning and deep learning, which are the building blocks of the effective use of AI. This computing power to run the data centers, etc., is costly to deploy and will likely strain electricity grids further. Another high cost would be installing sufficient sensors and metering devices on the grid's transmission, distribution, and consumer take-off elements to make it ‘smart’ and provide the data points necessary to enable AI for predictive demand management/maintenance.  

Recommendations

While Africa's energy sector faces numerous challenges, adopting AI presents opportunities for transformative change if stakeholders are deliberate. My recommendations are:

• AI is not a silver bullet for energy access, and relevant stakeholders must show commitment backed by a clear strategy, resource allocation, and action plans.  AI could be an enabler to improve access to clean, modern, affordable, and reliable energy.  
• By addressing challenges such as data availability, infrastructure investment, skilled workforce development, and affordability, Africa can harness AI's benefits to improve energy access, efficiency, and sustainability.  
• Responsible use of AI will include robust policy and regulatory frameworks to safeguard data privacy, cybersecurity, and ethical considerations.

This will ensure that AI-driven innovation contributes to Africa's more inclusive and resilient energy future.

Next steps

As we move forward, the fusion of AI and energy solutions in Africa represents not just technological advancement, but a pathway to improved livelihoods, economic growth, and sustainable development. The time to act is now, turning the potential of AI into tangible benefits for millions across the continent. 
 

About the author:

Kenneth Ene is a Senior Technical Advisor with the Energy Resources and Growth Team based in our US office. Ken brings 20 years of experience in managing the technical delivery of adaptive projects focused on energy access and sustainability, good governance, and policy reform. Ken has strong expertise in multi-stakeholder engagement and political economy analysis, and has provided policy advice at the highest levels of government in several countries.