PUBLISHER: MarketsandMarkets | PRODUCT CODE: 1915209
PUBLISHER: MarketsandMarkets | PRODUCT CODE: 1915209
The AI in mining market is anticipated to grow from USD 2.60 billion in 2025 to USD 9.93 billion by 2032, at a CAGR of 21.1% between 2025 and 2032. The AI in mining market is driven by rapid digital transformation and the increasing deployment of IoT, cloud computing, and 5G connectivity across mining sites.
| Scope of the Report | |
|---|---|
| Years Considered for the Study | 2020-2032 |
| Base Year | 2024 |
| Forecast Period | 2025-2032 |
| Units Considered | Value (USD Billion) |
| Segments | By Offering, Deployment, Technology, Application, Minig Type, Vertical and Region |
| Regions covered | North America, Europe, Asia Pacific , Latin America, Middle East & Africa |
The expanding adoption of autonomous haulage systems, smart drilling, and fleet management platforms accelerates automation and enables remote operations, particularly in complex and inaccessible mining locations.

"Generative AI technology segment is estimated to hold the largest market share in 2030."
The generative AI technology segment is expected to account for the largest share of the AI in mining market in 2030 due to its ability to enhance operational efficiency, decision-making, and predictive capabilities across mining processes. Generative AI can analyze massive volumes of geological, operational, and sensor data to generate actionable insights, simulations, and predictive models, enabling mining companies to optimize exploration, drilling, and extraction strategies. By producing accurate 3D models of ore bodies, predicting equipment failures, and simulating mining scenarios, generative AI reduces operational risks, downtime, and costs. Additionally, it accelerates design and planning workflows, allowing engineers to test multiple approaches virtually before implementation. The technology also supports environmental compliance and safety management by generating predictive alerts for hazardous conditions and tailings management. Its integration with other AI tools, such as computer vision and IoT analytics, further amplifies value across end-to-end mining operations. Given the growing demand for advanced analytics, automation, and smarter resource utilization, generative AI provides a scalable and intelligent solution that addresses both operational and strategic challenges, securing its position as the leading technology segment in the AI in mining market.
"Services segment is estimated to record the highest CAGR during the forecast period."
The services segment is expected to grow at the highest CAGR in the AI in mining market during the forecast period due to the increasing reliance of mining companies on consulting, system integration, training, and managed services to successfully deploy and scale advanced AI solutions. As mining operations become more complex and digitally connected, companies require specialized expertise to integrate AI platforms with existing equipment, IoT devices, enterprise systems, and remote operational centers. Services are crucial in customizing AI use cases, such as predictive maintenance, fleet optimization, geological modeling, and safety monitoring, to meet site-specific challenges and regulatory requirements. Additionally, the shortage of skilled AI and data science professionals within the mining sector pushes operators to depend heavily on third-party service providers for ongoing support, real-time performance monitoring, and continuous model improvements. Managed services and subscription-based deployment models further drive the demand by reducing upfront investment costs and ensuring long-term ROI through outcome-based performance contracts. As AI transitions from pilot projects to full-scale implementation, service providers become essential partners, fueling the segmental growth.
"Asia Pacific is projected to hold the largest share of the AI in mining market in 2030."
Asia Pacific is estimated to hold the largest market share in 2030 due to the massive mining infrastructure expansion, the growing industrial output, and the rising demand for metals, minerals, and coal required for energy production and manufacturing. China, Australia, India, and Indonesia are among the world's largest producers of essential raw materials, including iron ore, copper, gold, lithium, and coal, leading to substantial investment in mining modernization. The increasing need for operational efficiency, cost optimization, and high productivity has accelerated the adoption of advanced AI technologies, such as predictive analytics, autonomous haulage systems, AI-powered drilling optimization, and real-time equipment monitoring. Government initiatives supporting digital transformation and Industry 4.0 integration in mining, along with large-scale public and private funding for automation, further strengthen AI deployment. Additionally, the high availability of skilled engineering talent and rapidly evolving digital infrastructure-5G connectivity and cloud computing platforms-enable seamless integration of AI solutions across remote mining sites. As the region continues to scale mineral extraction to support electronics, EV batteries, and renewable energy industries, it is positioned to lead the AI in mining market by 2030.
The report profiles key players in the AI in mining market with their respective market ranking analysis. Prominent players profiled in this report 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), ABB (Switzerland), Microsoft (US), and SAP SE (Germany), among others.
Apart from this, IBM (US), RPMGLOBAL HOLDINGS LIMITED (Australia), Liebheer (Switzerland), GroundHog (US), Haultrax (Australia), Micromine (Australia), SYMX.AI (Canada), The Tomorrow Companies Inc. (US), VRIFY (US), IntelliSense.io (UK), Orica Limited. (Australia), MineSense Technologies Ltd. (Canada), Exyn Technologies (US), among others, are among the few other companies in the AI in mining market.
This research report categorizes the AI in mining market based on offering, mining type, deployment mode, technology, application, vertical, and region. The report describes the major drivers, restraints, challenges, and opportunities pertaining to the AI in mining market and forecasts the same till 2032. Apart from these, the report also consists of leadership mapping and analysis of all the companies included in the AI in mining market ecosystem.
Key Benefits of Buying the Report
The report will help the market leaders/new entrants in this market with information on the closest approximations of the numbers for the overall AI in mining market and the subsegments. This report will help stakeholders understand the competitive landscape and gain more insights to position their businesses better and plan suitable go-to-market strategies. The report also helps stakeholders understand the pulse of the market and provides them with information on key market drivers, restraints, challenges, and opportunities.