By Summer Okibe

The world is standing at a strange intersection where our biggest challenges and our boldest innovations are meeting in real time. Artificial intelligence is rewriting everything from how we communicate to how we work and energy is no exception.

What excites me about this moment is that AI is collapsing the distance between innovation and impact. For the first time, machines can predict, optimize, and anticipate the rhythm of the grid itself. Think of Google’s DeepMind cutting data center cooling energy use by 40%, or IBM’s Green Horizon forecasting Beijing’s air pollution and guiding cleaner industrial operations.

Now imagine that same precision applied to rural mini-grids in Nigeria or Kenya algorithms predicting solar battery failures and triggering maintenance before a community experiences an outage. That is reliability born of foresight, not luck. But even as I say that, there’s a question that makes me pause: Who owns the intelligence? Who owns the foresight?
I ask myself this every time I upload a photo to an AI platform. The data training most AI systems rely on still comes from the Global North, which means the models often fail to understand the realities of informal economies, tropical climates, or erratic grids that define much of the Global South. If we are not intentional, we risk digitalizing dependency, outsourcing not just our oil, but our algorithms, and with them, our energy sovereignty.

AI’s influence extends far beyond production. On the supply side, smart sensors and predictive analytics are already helping solar and wind operators fine-tune efficiency down to the very gust of wind or degree of sunlight. Researchers are also using AI to accelerate discoveries in next-generation batteries and solar cells.

On the distribution side, we are witnessing the rise of autonomous micro-grids: self-balancing, self-healing systems using machine learning and blockchain to trade surplus electricity peer-to-peer. This is not science fiction, it is reshaping what an energy network even looks like. On the user end, AI-enabled devices are learning from our habits and adjusting power use intuitively whether it’s a Nest thermostat in a Canadian home, or a smart solar cookstove in a Nigerian village. But efficiency without equity is shallow progress. Cleaner systems mean little if they deepen exclusion or prioritize profit zones over low-income communities. The real test is whether AI can deliver not just cleaner energy, but fairer systems.

From my work across energy governance and environmental justice, I believe three shifts are essential.

First, countries must establish energy data sovereignty. Locally generated data whether from household solar panels or community mini-grids cannot be extracted or commercialized without national oversight. Kenya’s 2019 Data Protection Act is a strong starting point, but nations like Nigeria need energy-specific clauses that recognize data as a national resource.

Second, regulators must demand algorithmic transparency in critical infrastructure. If an AI system decides how power is allocated or when to trigger a blackout-prevention protocol, citizens deserve to know why. Canada’s Directive on Automated Decision-Making offers a useful reference, but we need localized versions that reflect our own realities.

Third, inclusion cannot be an afterthought. Governments must hardwire gender, Indigenous, and youth representation into the design and procurement of AI systems. Justice cannot be retrofitted after the code is written. Justice, for me, has never been just about access, it is about agency, affordability, and accountability: the triple A’s. AI can bridge energy gaps when it is designed with context. Okra Solar’s model, which uses AI to cluster rural homes into modular micro-grids that grow organically with community demand, shows what is possible. But technology alone is not justice. Without building local capacity to maintain, interpret, and develop these systems, we risk reproducing old patterns of dependency only this time in code. That is why I advocate for algorithmic affirmative action: a principle that mandates local ownership, training, and benefit-sharing in every AI-energy partnership.

Looking ahead, a just clean energy revolution is one where the algorithm and the altar meet where technology respects human dignity and ecological balance. It is a future where communities in the Niger Delta or Alberta’s oil sands co-own the algorithms guiding their transition to renewables; where Indigenous and rural users earn revenue when their anonymized energy data is used to train smarter systems; where women entrepreneurs use AI-optimized solar dryers, irrigation pumps, and recyclers to power new circular economies.

But justice begins with questions: Who benefits from AI’s efficiency gains? How do we embed Indigenous and local consent into digital governance? And how do we prevent automation from becoming a new architecture of inequality?

AI may be ready. The real question is whether our values are.

Summer Okibe is a climate and energy policy specialist, attorney, and doctoral researcher currently based in Canada. As a voice for inclusive and sustainable development, she combines academic rigor with grassroots impact, having secured over $400,000 in scholarships and disbursed funds to less-privileged children across Nigeria.

She is currently developing the concept of Aderayah Academy, a vision for a tuition-free, solar-powered school in Enugu designed to give underserved children access to quality education. In addition, she recently launched a ₦500,000 annual prize for outstanding female law graduates at Chukwuemeka Odumegwu Ojukwu University (COOU).

Recognized with awards including the Flight 302 Legacy Award and JCI Top 100 Outstanding Young Persons of Nigeria, Summer’s leadership inspires youth across the continent.