Strategic Intelligence: Artificial Intelligence in Mining

Mining companies are investing in AI technologies to enhance productivity, safety, cost efficiency, and mineral discovery. Mining companies are pouring investment into AI initiaves and will continue to do so.

Artificial intelligence (AI) refers to software-based systems that use data inputs to make decisions on their own. AI tools can perform tasks that typically require human intelligence, such as learning from data, recognizing patterns, making decisions, and understanding language or images. AI can boost productivity, enable new insights, and automate routine or dangerous tasks. The analyst estimates the total AI market will be worth $641.8 billion by 2029, up from $131.3 billion in 2024 at a CAGR of 37.4%.

AI is integrated into key solutions across the mining industry, including predictive maintenance, autonomous equipment, fatigue detection, and advanced data analysis for mineral exploration and operational optimization. As a result, The analyst forecasts that mining companies’ spending on AI will grow from $2.7 billion in 2024 to $13.1 billion by 2029.

AI enhances operational efficiency in mining

AI-powered technologies are helping mines boost productivity and reduce costs across extraction, haulage, and processing. Predictive maintenance platforms have prevented major failures and avoided high-cost asset downtime, while automated trucks, shovels, and drills enable 24/7 operations. Advanced analytics and machine learning also optimize haul routes, reduce idle time, improve payloads, and streamline ore milling to raise recovery and cut energy, water, and reagent use.

AI is making mines safer

Mining remains inherently hazardous. While some firms report zero fatalities, industry-wide deaths persist, harming communities, investors, and operations. AI is reducing these risks by removing humans from dangerous tasks: autonomous and tele-remote trucks and drilling systems reduce exposure to hazardous zones and human error, causing significant reductions in incidents and costs.
AI-enabled sensing using light detection and ranging (LiDAR), thermal, gas, and vision systems support pre- and post-blast inspections and search-andrescue missions. Safety-focused AI, such as collision-avoidance and fatiguedetection, further prevents accidents by highlighting and logging unsafe conditions.

Key Highlights

• The report covers how AI overcomes key challenges in the mining industry. These include safety, mineral discovery and exploration, productivity, ore processing, and the environment.
• The 2025 the analyst mine-site technology adoption survey identified the technologies mining companies are investing in. These include mine planning and scheduling software, collision avoidance, predictive maintenance, fatigue detection, drones, wearables, and autonomous vehicles which commonly have integrated AI features, showing how important AI is to the mining industry.

Scope

• This report provides an overview of AI and how it will impact the mining industry.
• The report predicts how AI in mining will evolve, including the key challenges it will solve.
• It includes selected case studies highlighting who is innovating in mining using AI technologies.
• The report also includes a comprehensive data analysis, including market size and growth forecasts for the AI market.

Reasons to Buy

• The analyst’s thematic research ecosystem is a single, integrated global research platform that provides an easy-to-use framework for tracking all themes across all companies in all sectors.
• This report is essential for senior executives at minining companies to understand the critical benefits from integrating AI technology into their operations. Mining companies who fail to implement AI solutions will fall behind.
• In addition, the report identifies the leading AI adopters in mining, as well as specialist tech vendors in this space.