In Africa today, more than 600 million people still live without access to electricity. This statistic is as staggering as it is unacceptable. In an age defined by digital connectivity, the absence of something as basic as electricity continues to lock entire communities out of opportunity, restricting education, healthcare, gender equality, economic development, and basic dignity. ALSO READ: 65% Rwandan rural households access electricity – survey Over the past decade, decentralized renewable energy (DRE) solutions have emerged as the most viable and scalable path to universal energy access across Sub-Saharan Africa. Distributed solar, pay-as-you-go (PAYGo) models, mini-grids, and productive-use technologies have already transformed millions of lives. Yet to reach the full scale, hundreds of millions of people, we must disrupt the disruptors. And artificial intelligence (AI) is the tool to do that. ALSO READ: Rwanda needs $1.5bn to achieve universal energy access by 2029 AI has become one of the most overused buzzwords in tech. But for the DRE sector, it isn’t about hype or novelty. It’s about building systems that are faster, cheaper, more responsive, and more equitable. Used wisely, AI can enable a step-change in how we design, deliver, and scale energy access, bringing clean, affordable electricity to every household and business on the continent. Beyond buzzwords are some real opportunities for impact To understand how AI can transform the DRE sector, we must first get specific. AI isn’t one thing; it’s a family of technologies, from machine learning to natural language processing, computer vision, and advanced analytics. In a DRE context, these technologies can help across the entire value chain. ALSO READ: Why Rwanda is updating its energy policy Let’s start with credit scoring - a core challenge for off-grid energy providers. Most customers in deep rural areas are “unbanked.” They lack formal credit histories, fixed income, or access to conventional finance. That makes it difficult to assess risk, structure affordable financing, or expand inclusively. AI changes that. By analyzing alternative data such as mobile money usage, phone metadata, agricultural patterns, and even social behavior, AI can generate real-time, adaptive credit scores tailored to each customer. This allows companies to offer flexible payment plans to more people while managing risk responsibly. At Ignite, we’ve seen how AI-driven credit models can unlock access for previously excluded households, especially women, youth, and first-time borrowers. Then there’s logistics and forecasting, another bottleneck for scale. Delivering solar systems to remote villages isn’t easy. Roads are rough, maps are outdated, and demand is unpredictable. AI-powered supply chain models can optimize routes, predict stock needs, and reduce downtime, cutting costs and improving service delivery across thousands of locations. Customer support is another area primed for disruption. In many rural areas, customers face language barriers, low digital literacy, and long wait times for technical support. AI tools like multilingual chatbots and voice assistants can provide real-time troubleshooting, usage tips, or payment reminders in local languages, 24/7. These tools can improve customer experience while empowering users to get more value from their energy systems. Perhaps the most exciting application of AI is in impact verification. As results-based financing becomes the norm where development partners pay for actual outcomes rather than inputs, energy providers must prove, with precision, where, when, and how their services are being used. AI can ingest usage data, location data, satellite imagery, and remote diagnostics to verify connections, detect fraud, and ensure transparency. This builds trust across the value chain, from governments and funders to communities and customers. From proof to scale The question is no longer whether AI can help, it’s how we harness it ethically, inclusively, and at scale. Across the distributed renewable energy (DRE) sector, digital-first infrastructure is enabling new levels of insight and efficiency. Organizations are beginning to treat data not just as a byproduct of operations, but as a strategic asset. AI is increasingly being used to support every layer of the value chain: from identifying underserved communities to deploying last-mile agents, personalizing customer interactions, and forecasting infrastructure expansion. But its true power lies beyond internal optimization. The most promising applications are those that learn and evolve with the communities they serve. For instance, AI models can predict which households are likely to benefit most from solar irrigation based on patterns in land usage and weather data. Others can identify emerging micro-markets around community hubs like schools and clinics—fostering ecosystems of productivity rather than isolated installations. Challenges we must address Of course, AI is not a silver bullet. Like any tool, it reflects the values and systems of those who design it. If we’re not careful, it can reinforce exclusion instead of dismantling it. We must ask: Whose data is being used? Who benefits from the insights? Are we designing for urban engineers or rural customers? If an algorithm decides someone isn’t creditworthy, what human review is in place? These are not theoretical concerns; they are the front lines of ethical innovation. There are also infrastructure gaps. AI requires data, and in many rural contexts, data is still scarce, fragmented, or unreliable. Connectivity, device access, and digital literacy remain real challenges. That’s why AI can’t be imported wholesale from Silicon Valley, it must be built, tested, and owned locally. And we must build capacity. AI systems are only as good as the people who manage them. That means training African data scientists, engineers, designers, and regulators to shape the future of AI in energy access, not just consume it. A call for AI action We are at a crossroads. The decentralized energy sector has proven that we can deliver affordable, clean electricity beyond the grid. But to go from millions to hundreds of millions, we need new tools, and new mindsets. AI is one of the most powerful tools we have. Not because it’s new, but because it can make old barriers obsolete: the lack of data, the cost of scale, the fragility of trust. If we use it wisely, it can accelerate Africa’s energy future, one that is inclusive, efficient, and locally driven. But this future won’t build itself. It requires a bold investment in digital infrastructure. It requires ethical frameworks and inclusive governance. And above all, it requires collaboration between startups, governments, donors, and the communities we serve. Let us use AI to expand access, drive progress, and unlock the full potential of every household, school, and business on this continent. The lights are coming on in Africa. With the right tools, they’ll never go out again. The author is the CEO of Ignite Energy Access, a leading provider of decentralized solar solutions across Sub-Saharan Africa, working to connect 100 million people to clean electricity by 2030.
