Botswana Minerals has reported that an AI-assisted exploration study identified 36 copper anomalies across two of its eight northern Botswana licences, organized into six exploration corridors.
The licences sit in an under-explored geological corridor connecting Namibia’s Damara Belt with Zambia and the Democratic Republic of Congo’s Central African Copperbelt — both key copper regions in Africa. The identified anomalies exhibit geological traits similar to major existing and historic deposits.
The assessment used Planetary AI’s Xplore platform, which combines machine learning with expert geological insight to identify prospective areas from comprehensive datasets including geological mapping, structural and geophysical data, geochemistry and remote sensing. The geological features point to potential for sediment-hosted and structurally controlled mineralization, as well as iron oxide copper gold-style systems, with the targets sharing similarities with major deposits such as Kamoa-Kakula in the DRC and Tsumeb in Namibia.
Botswana Minerals plans to begin initial fieldwork within three months. The company will refine and prioritize the 36 identified target areas, develop field programmes for key corridors and plan the next stage of exploration based on the integrated target inventory. Further announcements are expected in due course.
Botswana Minerals chairman John Teeling said AI is fundamentally changing how mineral targets are identified. “There is no doubt that AI techniques are revolutionising identification of mineral targets. The ongoing analysis of our huge database continues to provide outstanding results,” he said.
“The analysis uses data from copper mines around the world to identify areas with similar geological characteristics, with the next step to rank these anomalies to better focus future fieldwork and any subsequent drilling decisions,” Teeling added. “This involves deeper AI analysis to support targeted fieldwork.”
