Times are changing across Africa, with commercial interest shifting from traditional minerals such as gold and diamonds to rare and critical minerals that are becoming central to artificial intelligence, global energy, technology and defence industries.
How AI could unlock Africa’s critical minerals and save miners up to $390 billion a year
- The Atlantic Council recommends creating a $300 million smart mining fund to support African tech firms, reduce risks, and accelerate AI-driven mining across the continent.
- Africa possesses around 30% of global critical mineral reserves, but receives just 10% of the world’s mineral exploration budget and often relies on outdated geological surveys.
- Artificial intelligence has the potential to help Africa discover significant mineral deposits, reduce mining costs, and shift away from its traditional role as a raw-material exporter.
- AI applications, such as data analysis and digital twins, can dramatically improve exploration efficiency, cut timelines, and increase mineral recovery, with successful projects already seen in Zambia, Angola, Botswana, <a href="https://absafricatv.com/south-africa-and-namibia-strengthen-ties-with-seven-new-agreements/" title="South Africa and Namibia strengthen ties with seven new agreements”>South Africa, and Mali.
According to an Atlantic Council report titled Artificial intelligence and the future of African mining, data and AI-driven mining could save producers worldwide between $290 billion and $390 billion annually by 2035.
However, the technology remains at a nascent stage in Africa, despite the continent holding an estimated 30 per cent of the world’s critical mineral reserves and receiving only 10 per cent of global mineral exploration spending.
Many African countries also continue to rely on geological surveys compiled during the colonial era, leaving large parts of the continent underexplored despite major deposits of cobalt, manganese, graphite, bauxite, copper, chromium and platinum-group metals.
Africa holds nearly 85 per cent of known platinum-group metal reserves, about 51 per cent of cobalt and almost 37 per cent of manganese.
DON’T MISS:Africa holds a quarter of the world’s critical minerals powering AI and clean energy, but less than 10% of mining projects are moving ahead
Globally, only about five in every 1,000 early-stage mineral prospects become commercially take more than a decade
However,AI can analyse geological, geochemical, drilling and satellite data to identify promising deposits, reduce unnecessary drilling and shorten exploration timelines.
In Zambia, US-based KoBold Metals used machine learning and three-dimensional geological modelling at the Mingomba copper project to reassess historical drilling data and design a more efficient drilling sequence.
Simulations cited by the Atlantic Councilsuggest such models could cut exploration drilling time by up to 75 per cent.
Elsewhere in Zambia, Fleet Space Technologies is deploying its satellite-enabled ExoSphere platform at Konkola Copper Mines in partnership with CopperTech Metals and Axiom Group.
The system combines predictive AI, geophysical surveys and subsurface data to improve drilling targets and accelerate copper exploration.
Meanwhile, Zambia has partnered with Xcalibur Smart Mapping on nationwide geological mapping, with the full commercial release of the data expected in 2027.
In Angola, Xcalibur conducted aerial magnetic and radiometric surveys under the National Geology Plan between 2015 and 2021.
The programme identified geological structures that helped attract Rio Tinto, Anglo American and Ivanhoe Mines beyond the country’s traditional oil and diamond industries.
Similarly, Tsodilo Rena Institute for Technology Research and Innovation and the Botswana Geoscience Institute at Botswana’s Gcwihaba critical minerals and rare earth elements project
The research will combine advanced mineral analysis with legacy drilling data to identify geological indicators and strengthen AI-driven exploration models.
DON’T MISS:Congo begins first-ever lithium exports to China, unlocking the world’s largest undeveloped hard-rock reserves
Africa possesses around 30% of global critical mineral reserves, but receives just 10% of the world’s mineral exploration budget and often relies on outdated geological surveys.Business Insider Africa
AI adoption is most advanced in Southern Africa, although projects are also emerging elsewhere.
In South Africa, mining companies use computer vision to monitor workers near heavy machinery and detect rockfall risks.
Siemens estimates that up to 40 per cent of South African mines could use digital twins by 2040.
Digital twins create virtual models of mines, allowing operators to test production plans, identify hazards and predict equipment failures.
At Kilken Platinum’s Thabazimbi tailings retreatment plant, AI monitoring is being used to increase monthly platinum-group metal production from 40 kilogrammes to 83 kilogrammes.
Similarly, Anglo American’s Mogalakwena mine uses data models to improve platinum recovery and reduce water consumption.
In Mali, Resolute Mining’s Syama gold mine has become one of Africa’s leading examples of automation and remote mining operations.
DON’T MISS:Africa’s biggest bauxite producer reverses mining crackdown with Australian miner permit renewal
Artificial intelligence has the potential to help Africa discover significant mineral deposits, reduce mining costs, and shift away from its traditional role as a raw-material exporter.Business Insider Africa
The Democratic Republic of Congo is estimated to hold about $24 trillion in largely untapped mineral re
However, the country is still seeking fuller access to millions of colonial-era geological records held at Belgium’s Royal Museum for Central Africa.
The archive contains maps, mineral surveys, drill logs and exploration reports compiled during Belgian colonial rule.
Belgium and the DRC have agreed to digitise the records and transfer copies to Congolese authorities.
Access to the data could help researchers identify deposits of copper, cobalt, lithium and other critical minerals.
Meanwhile, Ivanhoe Mines’ Kamoa-Kakula copper complex used data analytics to target a recovery rate of 95 per cent.
The operation produced about 400,000 tonnes of copper in 2025 and established an on-site smelter that also produces sulphuric acid.
Despite the progress, AI adoption remains fragmented and concentrated in Southern Africa.
West and Central African mining hubs still face unreliable electricity, poor roads, limited railways, weak digital infrastructure, few processing plants and shortages of skilled graduates make it difficult to operate AI systems, collect geological data and deploy automated equipment.
Insecurity in Mali,Burkina Faso, Niger, northern Nigeria and eastern DRC also raises costs and discourages investment in technology-led exploration.
Meanwhile, higher state ownership requirements, changing mining laws and export restrictions in countries such as Mali, Burkina Faso, Kenya, Nigeria and Zimbabwe can delay projects and reduce the capital available for AI and digitalisation.
The Atlantic Council has therefore proposed a $300 million public-private smart mining fund to support African technology companies, reduce investment risks and finance AI-driven exploration, processing and mine operations.
