African mining projects are increasingly incorporating artificial intelligence (AI) to streamline operations and meet ambitious production targets set by governments across the continent. As the mining industry undergoes a digital transformation, the upcoming African Mining Week (AMW) will highlight the pivotal role of AI and other digital tools in optimizing exploration and production processes, with a view to unlocking new mineral reserves, reducing costs, and enhancing worker safety.
Botswana Diversifies Mineral Portfolio
In Botswana, Botswana Diamonds is expanding its mineral portfolio beyond diamonds with an AI-based nationwide exploration campaign launched in August 2024. By March 2025, the company identified potential deposits of besshi, greenstone, Mississippi Valley-type lead and zinc, SEDEX, and platinum group metals (PGMs). To capitalize on these discoveries, Botswana Diamonds has applied for 11 new prospecting licenses. John Teeling, Chairman of Botswana Diamonds, stated: “During the initial analysis of the big database, it became clear that the AI technology could be used to identify other unknown minerals opportunities… Our analysis so far has identified a series of targets in copper cobalt, zinc, and gold.”
KoBold Advances Zambia’s Critical Mineral Market
U.S.-based startup KoBold Metals is applying AI to enhance critical mineral exploration and mine development in Zambia. In January 2025, KoBold raised $537 million in new capital, bringing its total funding to $1 billion. The company is developing one of the world’s largest untapped copper basins in Zambia, with plans to produce 300,000 tons annually by 2030 from its $2 billion Mingomba Project. Additionally, KoBold Metals is exploring the Dumbwa Mine and Konkola West Project, contributing to Zambia’s goal of reaching 3 million tons of annual copper production by 2031.
Kilken Platinum Drives Mine Expansion
In South Africa, Kilken Platinum is utilizing AI to optimize operations at its Thabazimbi processing plant in Limpopo as part of an expansion plan to double PGM production to 83kgs per month. The project has already increased output to 40kgs in its initial phase. Dondo Mogajane, CEO of Kilken Platinum’s parent company Moti Group, emphasized that AI enables real-time tracking of production metrics and ensures strict adherence to safety protocols.
Beyond these projects, Rio Tinto subsidiary Richards Bay Minerals is employing AI for ore body modeling, equipment dispatch management, and blast control at its mines in KwaZulu-Natal, South Africa. In the Democratic Republic of Congo, Glencore is leveraging digital technology to streamline critical mineral exploration as part of its Phase 2 expansion at the KTO copper and cobalt project.
AMW 2025 will feature high-level discussions focused on AI’s impact on industry growth, investment opportunities for technology providers, and the broader economic benefits of digital transformation in mining.
The Telecom Sector Embraces AI
Meanwhile, in the telecom sector, OpenAI recently closed a $40 billion funding round, the most ever raised by a private tech company. Its ability to attract capital in the face of U.S. President Donald Trump’s tariffs is testament to the transformative potential of AI in business. For telecoms companies, the stakes are higher than ever. The future of network operations is no longer about maintaining legacy systems but about embracing the transformative power of AI to stay competitive.
AI is rapidly evolving from a futuristic concept into a business-critical tool, and for telecoms, it’s no longer a luxury – it’s a necessity. The pressure is on, and those who hesitate risk falling behind. AI is a driving force in optimizing network performance and automating operations. For telecom operators, embracing AI is no longer a good-to-have; it is now table stakes to compete in a hyper-competitive, tech-driven landscape.
At the heart of AI’s transformative impact on telecom is the rise of AI agents. These software entities are able to pursue long-term objectives autonomously. They can interact with the environment, processing data from diverse sources including text, images, video, and audio. They can also make complex decisions by breaking them down, prioritizing, and sequencing them efficiently. They also have the ability to create a feedback loop to continuously improve their output.
Though still in its early stages, leading telcos are already exploring this technology in a variety of ways:
- Network optimization: AI agents analyze network traffic and performance data to identify bottlenecks, enabling dynamic resource allocation for sustained optimal performance.
- Predictive maintenance: AI agents continuously monitor network infrastructure, predicting potential failures and proactively scheduling maintenance to minimize downtime and reduce operational costs.
- Resource allocation: AI agents optimize resource distribution, such as bandwidth, to adapt to fluctuating demands and maintain consistent service quality.
At Mobile World Congress 2025 in Barcelona, agentic AI was a major talking point. Deutsche Telekom and Google Cloud announced plans to develop an agentic AI for autonomous networks, while Ericsson is collaborating with Telenor to create a proof-of-concept for a system that cuts the energy consumption of radio access networks. SK Telecom also unveiled AI-powered services, including telco AI agents and infrastructure assistants.
The introduction of AI agents signals the dawn of a new era for telecom operators. As autonomous networks powered by AI agents evolve, they will significantly reshape how telcos deliver services, manage infrastructure, and interact with customers. With telecom networks becoming increasingly complex, traditional rule-based automation will struggle to handle real-time challenges. AI agents will be pivotal in addressing these complexities, reducing latency, and improving service delivery.
However, the journey ahead is not without challenges. Data privacy and security will remain critical concerns, as AI agents process vast amounts of sensitive customer data. Additionally, integrating AI agents with legacy systems poses a challenge, as telcos must ensure seamless compatibility without disrupting service continuity. The shift towards AI-driven decision-making also requires new skills and training for staff to effectively collaborate with AI systems.
Looking ahead, AI agents will evolve from niche tools into central components of telecom operations, driving cost reductions, enhancing efficiencies, and unlocking new service offerings. The north star for operators will be not only to successfully deploy AI agents but also to cultivate an ecosystem that supports continuous innovation. This will help them stay ahead of the competition and deliver faster, more reliable, and personalized services. For telcos that can execute on this opportunity, AI agents will prove to be a game-changer.
