AI in Mining Market worth USD 9.93 billion by 2032

The report "AI in Mining Industry by Offering (Software, Services), Mining Type (Surface, Underground), Deployment Mode (On-Premises, Cloud, Hybrid), Technology (Generative AI, Machine Learning, NLP), Application, Vertical, and Region - Global Forecast to 2032", is expected to reach USD 9.93 billion by 2032 from USD 2.60 billion in 2025, registering a CAGR of 21.1% during the forecast period.

The AI in mining market is driven by stringent safety regulations and the growing emphasis on reducing workplace accidents and fatalities. The demand for autonomous monitoring, hazard detection, and worker-tracking systems is rising, supported by strong investments in advanced surveillance, environmental monitoring, and risk prediction technologies that create safer mining environments. Additionally, the increasing push for productivity optimization and operational cost reduction boosts the adoption of AI-powered automation across global mining operations.

The safety, security & environmental segment is expected to grow at the highest CAGR in the AI in mining market from 2025 to 2032. This is due to rising pressure to create safer working environments, prevent accidents, and comply with increasingly stringent global safety and sustainability regulations. Mining remains one of the most hazardous industries, with risks related to ground instability, equipment collisions, gas leaks, ventilation failures, and tailings dam breaches. As a result, mining companies are rapidly adopting AI-powered video analytics, real-time worker tracking, predictive hazard detection, and autonomous emergency response systems to mitigate operational risks and protect workers. At the same time, the growing ESG expectations and environmental compliance requirements fuel the demand for AI solutions that monitor emissions, optimize water usage, control dust and noise, and track waste and land rehabilitation. Governments, investors, and communities demand greater transparency and responsible mining operations, accelerating investments in AI-enabled monitoring and reporting tools. With advancements in sensor technologies, IoT connectivity, and cloud-based analytics, the adoption of AI for safety and environmental intelligence for pilot deployments to large-scale implementation increases, driving the segmental growth.

“Metal mining segment captured the largest share of AI in mining market in 2024.”

Metal mining holds the largest market share in the AI in Mining market in 2024 due to the surging global demand for critical minerals required for electric vehicles, renewable energy storage, consumer electronics, and low-carbon industrial technologies. Metals such as copper, lithium, nickel, cobalt, and rare earth elements are essential for battery manufacturing, power transmission, electric motors, and clean energy infrastructure. As countries accelerate energy transition goals and strengthen supply chains for strategic minerals, metal mining companies are significantly increasing production capacities and operational efficiency, driving strong adoption of AI-enabled automation and digital optimization. Metal mining operations involve highly complex processes—from ore body modeling and exploration to drilling, blasting, grinding, and material movement—requiring precise planning and real-time decision intelligence. AI supports these functions through predictive analytics, advanced mineral processing optimization, fleet management, and autonomous equipment control, enabling cost reduction and higher yield recovery. Leading metal mining firms are also early adopters of digital twins, autonomous haulage, and sensor-based ore sorting, reinforcing their leadership in technological transformation and supporting the segment’s dominant market share in 2024.

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“Asia Pacific accounted for the largest share of the AI in mining market in 2024.”

Asia Pacific held the largest market share in 2024 due to its dominant mining production volume and early large-scale adoption of digital mining initiatives. China and Australia alone account for a substantial portion of global mining output, supported by strong investments from mining giants, such as BHP, Rio Tinto, Coal India, and China Shenhua. These companies have integrated AI-based automation, fleet management solutions, autonomous trucks, and intelligent safety monitoring systems across surface and underground operations. The region faces frequent operational hazards, workforce shortages, and increasing regulatory pressure related to worker safety and environmental sustainability, pushing faster implementation of AI for real-time hazard detection, emissions management, tailings control, and predictive maintenance. The strong government support for sustainable mining practices, reduction of operational emissions, and adoption of smart mining technologies have contributed to rapid digital transformation across mining operations. Additionally, heavy demand for coal and critical minerals essential for power generation and industrial manufacturing further drives AI integration, allowing the region to command the largest share of the global market in 2024.

Key Players

Key companies operating in the AI in mining market are Caterpillar (US), Komatsu Ltd. (Japan), Sandvik AB (Sweden), Epiroc AB (Sweden), Hitachi Construction Machinery Co., Ltd. (Japan), Hexagon AB (Sweden), Rockwell Automation (US), Siemens (Germany), Trimble Inc. (US), and ABB (Switzerland), among others.