Artificial intelligence (AI) and machine learning are increasingly influencing mineral exploration processes, according to a recent report by Ipsos for VRIFY Technology. The 2025 Mineral Exploration Tech Report indicates that 77 percent of surveyed mineral exploration professionals reported some level of AI tool usage in their operations, signaling a robust momentum in the adoption of these digital technologies.
The report, which surveyed 135 professionals in the mineral exploration sector, serves as a benchmark for companies aiming to understand their current position on technology adoption. “We hope this report acts as a practical benchmark for the mining industry, helping teams understand where they stand today, learn from their peers, and make more confident decisions,” said Steve de Jong, CEO and founder of VRIFY Technology, in an emailed statement to CIM Magazine. He emphasized the growing importance of technology in enhancing project efficiency.
Despite significant interest in AI, the report reveals that actual usage remains inconsistent. While 56 percent of respondents indicated they use AI and machine learning tools occasionally, only 21 percent reported regular use, and 10 percent admitted they do not utilize these technologies at all. Geologists expressed the most skepticism regarding AI applications, followed by field managers and corporate executives. In contrast, functional specialists showed the highest engagement with such tools.
Key barriers to wider adoption include budget constraints, uncertain returns on investment (ROI), and a general distrust in the outputs generated by AI models. The report identifies a challenge in organizational readiness, suggesting that companies must enhance their technical capabilities and internal frameworks to effectively deploy AI technologies. Smaller firms often struggle with financial limitations, while larger organizations face challenges related to skills gaps and integration complexities. Mid-sized companies, the report notes, are typically better positioned to adopt and operationalize AI tools due to their resource availability and flexibility in risk management.
Despite the hurdles, perceptions of AI improve when companies reference credible peer case studies and insights gained from internal pilot projects, bolstered by clearer ROI expectations. Respondents highlighted that faster decision-making and more efficient resource utilization are the primary benefits observed from AI adoption, with 36 percent of participants noting these improvements. However, the report also indicated that 22 percent of respondents saw no observable outcomes since implementing AI and machine learning technologies. The impact of these tools appears closely tied to the maturity of their implementation and the quality of the underlying data.
Looking ahead, optimism prevails within the industry, as 84 percent of respondents believe that AI and machine learning will yield benefits in the near-term. The findings paint a portrait of an industry at the cusp of transformation, characterized by ongoing experimentation with new technologies and a search for reliable practices. The report underscores the need for stronger data foundations, improved technical skills, and greater transparency in sharing outcomes and best practices across organizations to further advance AI adoption in mineral exploration.
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