(MENAFN- GlobeNewsWire - Nasdaq) The main market opportunities in AI for mining include expanding predictive maintenance in underserved regions, automating core operations with AI robotics, and enhancing ESG transparency through AI. These developments promise increased efficiency, safety, and sustainability in mining.

Dublin, Oct. 15, 2025 (GLOBE NEWSWIRE) -- The "AI In Mining Market Size, Share & Industry Analysis Report by Type, Deployment, Technology, Regional Outlook and Forecast, 2025-2032" has been added to ResearchAndMarkets's offering.

The Global AI in Mining Market is poised to achieve a substantial growth trajectory, with projections indicating a market size of USD 435.94 billion by 2032, expanding at a CAGR of 40.6% during the forecast period.

Key Highlights:

• The North America market led the global AI in Mining sector in 2024, accounting for a 36.80% revenue share.
• The US market is expected to maintain dominance in North America, reaching USD 91.37 billion by 2032.
• Among type segments, Surface Mining was the frontrunner globally, contributing a revenue share of 54.62% in 2024.
• The Cloud segment dominated deployment categories in 2024 with a 51.71% revenue share, projected to sustain its lead during the forecast period.
• Machine Learning & Deep Learning segment brought in USD 10.74 billion in 2024, asserting its ongoing dominance in technology segments.

AI is revolutionizing the mining industry by enhancing safety, productivity, and technological advancement. Initially deployed with smart fleet management tools like the DISPATCH system, it's now ingrained with applications like real-time ore sorting and autonomous operations. Currently, AI is crucial in exploration, equipped with resources like satellite data, significantly reducing costs and time for deposit identification. Many global governments and companies are proactively incorporating AI through initiatives emphasizing crucial mineral mapping.

The competitive scenario is dynamic, featuring major mining corporations, OEMs, technology entities, and startups. Industry leaders such as BHP, Rio Tinto, Vale, and Glencore lead AI adoption with smart fleet systems and predictive tools, while Komatsu, Caterpillar, and Sandvik focus on AI-enhanced autonomous machinery. Technology providers like IBM, Microsoft, and Google are entering with cloud-based AI solutions. Furthermore, government investments in AI underscore its strategic importance in securing critical minerals and modernizing exploration.

COVID-19 Impact Analysis

The pandemic negatively impacted AI adoption in mining due to restrictions, financial uncertainty, and supply chain crises, leading to postponed investments and halted innovations.

Driving and Restraining Factors Drivers:

• Operational Efficiency and Cost Optimization
• Enhanced Exploration and Resource Estimation
• Increased Demand for Worker Safety
• Sustainability and Environmental Monitoring

Restraints:

• High AI Implementation Costs
• Data Scarcity and Quality Issues
• Regulatory and Ethical Concerns

Opportunities:

• Predictive Maintenance in Underserved Regions
• AI-powered Robotics Automation
• ESG-Driven Optimization and Reporting

Challenges:

• Integration with Legacy Infrastructure
• Data Issues in Subsurface Environments
• Regulatory Ambiguities

Market Share Analysis

Companies are employing diverse strategies to remain competitive, including acquisitions and partnerships to address varied industry demands. The underground mining type recorded a 39% revenue share in 2024, with AI enhancing safety and decision-making through advanced technologies like AI-assisted geospatial mapping. The robotics & automation segment accounted for 27% revenue share, driven by automation of hazardous tasks and optimization of mining processes.

Regional Outlook

AI in mining is advancing rapidly in regions like North America, driven by technology adoption and infrastructure. Europe emphasizes sustainability and law compliance, while Asia-Pacific's industry growth and mineral resources spur AI integration. LAMEA presents growth potential, with AI improving efficiency and safety in challenging environments.

Recent Strategies Deployed in the Market:

• Apr-2025: Datarock Pty Ltd launched a secure database for AI applications, boosting cybersecurity in mining operations.
• Dec-2024: Sandvik AB acquired Universal Field Robots to enhance automation and safety through AI in mining.
• Oct-2024: Komatsu Ltd. acquired Octodots Analytics, advancing AI-driven data integration for mining optimization.
• May-2023: BHP collaborated with Microsoft on AI-driven concentrator optimization at Escondida mine in Chile.
• Apr-2021: IBM acquired myInvenio to enhance AI-driven workflow optimization in mining.

List of Key Companies Profiled:

• IBM Corporation
• Komatsu Ltd.
• Caterpillar, Inc.
• Sandvik AB
• SAP SE
• Microsoft Corporation
• Datarock Pty. Ltd.
• Earth AI Inc.
• BHP Group Limited
• Rio Tinto PLC

Key Topics Covered:

• Chapter 1. Market Scope & Methodology
  • 1.1 Market Definition
  • 1.2 Objectives
  • 1.3 Market Scope
  • 1.4 Segmentation
  • 1.5 Methodology for the Research
• Chapter 2. Market at a Glance
• Chapter 3. Market Overview
  • 3.1 Introduction
  • 3.2 Key Factors Impacting the Market
• Chapter 4. Market Trends - AI In Mining Market
• Chapter 5. State of Competition - AI In Mining Market
• Chapter 6. Product Life Cycle - AI In Mining Market
• Chapter 7. Market Consolidation - AI In Mining Market
• Chapter 8. Competition Analysis - Global
  • 8.1 Market Share Analysis, 2024
  • 8.2 Recent Strategies Deployed in AI In Mining Market
  • 8.3 Porter Five Forces Analysis
• Chapter 9. Value Chain Analysis - AI In Mining Market
• Chapter 10. Key Customer Criteria - AI In Mining Market
• Chapter 11. Global AI In Mining Market by Type
• Chapter 12. Global AI In Mining Market by Deployment
• Chapter 13. Global AI In Mining Market by Technology
• Chapter 14. Global AI In Mining Market by Region
  • 14.1 North America AI In Mining Market
  • 14.2 Europe AI In Mining Market
  • 14.3 Asia Pacific AI In Mining Market
  • 14.4 LAMEA AI In Mining Market
• Chapter 15. Company Profiles
• Chapter 16. Winning Imperatives of AI In Mining Market

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