AI can dig deep, faster.
That can be said of AI’s ability to take volumes of information and quickly uncover hidden patterns or chart new courses of action. But in this case, it is more literal. AI is helping African mining companies dig deep, faster.
“The last three years have been really breakneck speed for those who work in the exploration world,” said Mfikeyi Makayi, CEO of California-based KoBold Metals Africa, during a groundbreaking ceremony in Zambia in April. “Most people don’t understand how much time it takes to develop a mine. On average around the world, it’s a 15- to 20-year project.”
The world is racing toward an electric future. Cars, trucks, drones and industrial robots increasingly run on batteries. Solar farms, wind turbines and sprawling data centers powering the AI revolution all require vast amounts of copper, lithium, cobalt and nickel. Yet before those minerals can power a cleaner economy, they first have to be found.
Experts estimate that hundreds of new mines will be needed globally by 2040 to meet growing demand for critical minerals. Traditional mineral exploration remains a costly and uncertain process that can take decades and consume millions of dollars before yielding results.
Makayi believes AI can change that.
As CEO of KoBold Metals Africa, she is helping lead a technological transformation in one of the world’s oldest industries. Rather than relying solely on traditional exploration methods, KoBold uses machine learning algorithms to analyze decades of geological data, satellite imagery, geophysical surveys and drilling records. The technology identifies patterns that human analysts might miss and predicts where valuable mineral deposits are most likely to be found.
The result is a process that can dramatically reduce the time, cost and risk associated with exploration.
If anyone understands both the promise and challenges of mining, it is Makayi. Born in Zambia, she left Africa to study civil and environmental engineering in the United States before earning a master’s degree in mining engineering in the United Kingdom. She later returned home and built her career in mining operations, working for First Quantum Minerals and gaining experience at sites across Africa, Australia and Europe.
Today, she oversees KoBold’s mineral exploration efforts throughout Africa, including projects in Zambia, the Democratic Republic of Congo, Botswana and Namibia.
Her work has attracted international attention. In 2025, Makayi was named to Time magazine’s list of the 100 most influential people in AI, recognition that reflected not only her leadership but also the growing role AI is playing in the global race for critical minerals.
One of KoBold’s most significant successes is the Mingomba copper project in Zambia.
Using AI-driven exploration tools, the company identified what is believed to be one of the largest high-grade copper discoveries made in recent decades. The project progressed from discovery to development in roughly five years, a timeline that would have been nearly unimaginable under conventional exploration models.
The mine is expected to play a significant role in Zambia’s effort to increase national copper production to 3 million metric tons annually by 2031, serving as a proof of concept for how AI can compress the traditional discovery-to-development timeline.
The implications extend far beyond a single mine. Across Africa, governments and mining companies are increasingly embracing AI as a way to unlock untapped mineral wealth. In Burundi, KoBold is working with government officials to digitize geological records and deploy AI tools to accelerate exploration for nickel, copper, cobalt, platinum group metals and scandium.
In the Democratic Republic of Congo, the company is pursuing major investments in the massive Manono lithium project, one of the world’s largest hard-rock lithium deposits. The effort aligns with growing global demand for minerals needed to manufacture batteries for electric vehicles and renewable energy systems.
Other mining companies are following a similar path. In Botswana, AI-powered exploration programs are helping identify potential deposits of diamonds, copper and gold. In South Africa, mining companies are using AI-driven monitoring systems to improve production and safety. Autonomous equipment guided by AI is also beginning to reshape operations in gold mines across West Africa.
The technology’s appeal is straightforward. Mining has always been a business built on uncertainty. Drilling programs can stretch for years with no guarantee of success. AI does not eliminate risk, but it can significantly improve the odds by narrowing the search area and helping geologists make more informed decisions.
For Africa, the stakes are particularly high.
The continent holds an estimated 30% of the world’s critical mineral reserves, making it central to the global energy transition. As nations compete to secure supplies of copper, lithium, cobalt and other battery metals, African countries increasingly see technology as a tool for attracting investment, reducing exploration risk and accelerating development.
Makayi argues that the challenge facing the industry is unlike anything in history.
“If there’s a word for more than exponential, it’s more than exponential,” she told Time. “We’ve got a climate to save at this point.”
That urgency is helping drive one of the most unexpected partnerships of the AI era: advanced machine learning and mineral exploration. For generations, mining companies searched for hidden deposits with maps, hammers and a healthy dose of luck. Today, they are increasingly turning to algorithms.
