Botswana Diamonds PLC has announced a significant expansion of its mineral exploration strategy, applying for eleven new Prospecting Licences (PLs) in Botswana following an Artificial Intelligence (AI)-driven exploration programme.
The move marks a diversification from the company’s primary focus on diamonds to a broader range of polymetallic resources, including copper, silver, cobalt, gold, nickel, zinc, and platinum group metals (PGMs).
The AI exploration initiative, initially aimed at identifying diamond-rich deposits, has uncovered promising polymetallic targets across 7,322 square kilometers. The newly applied licenses target five distinct mineralisation types:
- Besshi (volcanogenic massive sulfide deposit) – Predominantly copper.
- Greenstone – Copper and nickel.
- Mississippi Valley-Type (MVT) deposits – Lead and zinc.
- Sedimentary Exhalative (Sedex) deposits – Lead, zinc, and silver.
- Ultramafic deposits – Platinum Group Metals (PGMs).
"“Our comprehensive, country-wide AI-driven exploration programme in Botswana initially focused on diamonds. However, it quickly became clear that AI technology could identify previously unknown mineral opportunities. This analysis has led us to secure key targets in copper, cobalt, zinc, and gold,” said John Teeling, Chairman of Botswana Diamonds.
The discovery of polymetallic resources through AI technology underscores the growing role of data-driven exploration in the mining industry. With increasing global demand for copper, cobalt, and PGMs—critical for green technologies—Botswana Diamonds' diversification may attract further investment and partnerships within the sector.
This latest development follows previous efforts by Botswana Diamonds to leverage advanced technologies for mineral exploration. The company’s AI-driven approach is expected to accelerate exploration efficiency and improve resource targeting, positioning Botswana as a key player in the evolving global mining landscape.
As Botswana Diamonds continues its exploration activities, industry analysts will closely watch how AI-driven techniques impact the efficiency of mineral discovery and development in the region.