광업용 인공지능(AI) 시장 : 시장 규모, 점유율, 동향 분석(유형별, 배포 모드별, 기술별, 지역별) 전망 및 예측(2025-2032년)

The Global AI In Mining Market size is expected to reach USD 435.94 billion by 2032, rising at a market growth of 40.6% CAGR during the forecast period.

Key Highlights:

• The North America AI In Mining Market dominated the Global Market in 2024, accounting for a 36.80% revenue share in 2024.
• The US AI In Mining Market is expected to continue its dominance in North America region thereby reaching a market size of 91.37 billion by 2032.
• Among the various type segments, the Surface Mining segment dominated the global market, contributing a revenue share of 54.62% in 2024.
• Cloud segment led the deployment segments in 2024, capturing a 51.71% revenue share and is projected to continue its dominance during projected period.
• Among different Technology segments, Machine Learning & Deep Learning segment with a revenue contribution of 10.74 billion in 2024 is projected to continue its dominance.

AI has transformed the mining industry by making it better protected, more productive and tech-savvy. The mining industry used smart fleet management tools such as Modular Mining's DISPATCH system in the 1980s, now the industry is incorporating advanced applications like real-time ore sorting, predictive maintenance, and large-scale autonomous operations. Currently, AI is being used in exploration backed with satellite data, geophysical surveys, and drill logs, decreeing the cost and time in identifying deposits. Government and companies across the globe are adopting AI in mining through public initiatives, such as national plans focused on mapping critical minerals like lithium and rare earths in Rajasthan, India.

The competitive scenario is highly robust, with mining giants, OEMs, tech companies, and all startups are contributing in it. Corporates like BHP, Rio Tinto, Vale, and Glencore are at the forefront of the AI adoption in mining with smart fleet systems and predictive platforms, meanwhile Komatsu, Caterpillar, and Sandvik emphasizes on digital twin technologies and AI-powered autonomous machinery. Technology suppliers like IBM, Microsoft, and Google are penetrating with cloud-based AI solutions, while starts are working on the innovations related to the geological modeling and resource estimation. Furthermore, governments globally are also investing heavily in AI to secure critical minerals and modernize exploration.

COVID 19 Impact Analysis

By interfering with operations through lockdowns, health restrictions, and site access limitations, the COVID-19 pandemic had a detrimental effect on the mining industry's adoption of AI. Due to financial uncertainty, businesses prioritized essential operations over digital innovation, which resulted in the cancellation or delay of numerous AI projects. Automation, predictive maintenance, and data analytics projects were put on hold when it was decided that investing in AI technologies-which require a large amount of infrastructure, software, and trained workers-was not necessary. Deployment and maintenance were further hampered by shortages and delays in vital hardware, including sensors, drones, and computer equipment, brought on by the global supply chain crisis. Progress was also slowed by limitations on training and workforce mobility. All things considered, the pandemic produced an unfavorable climate for integrating AI, which led to a halt in the digital transformation of the mining industry. Thus, the COVID-19 pandemic had a Negative impact on the market.

Type Outlook

Based on type, the AI in mining market is characterized into surface mining, underground mining, and others. The underground mining segment attained 39% revenue share in the market in 2024. This segment benefits from AI-enabled solutions that address the complex challenges of subterranean operations, such as limited visibility, constrained space, and heightened safety risks. Technologies such as intelligent ventilation systems, autonomous drilling machinery, and AI-assisted geospatial mapping have significantly improved operational outcomes in underground mining. Moreover, AI contributes to better decision-making through the analysis of geological data, helping mining companies navigate intricate underground structures while minimizing risks and improving yield efficiency.

Technology Outlook

By technology, the AI in mining market is divided into machine learning & deep learning, robotics & automation, computer vision, NLP, and others. The robotics & automation segment attained 27% revenue share in the market in 2024. These technologies support the automation of repetitive and hazardous tasks, significantly enhancing worker safety and operational precision. Autonomous haulage systems, robotic drilling, and unmanned aerial vehicles are examples of robotics applications that streamline processes, reduce human error, and lower operational costs. Automation technologies also improve ore handling and transport systems, resulting in optimized productivity and reduced energy consumption. As mining sites often operate in remote and high-risk environments, robotics and automation are increasingly being adopted to enable continuous operations with minimal human intervention.

Regional Outlook

Region-wise, the AI in mining market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America segment recorded 37% revenue share in the market in 2024. Strong technology adoption and advanced infrastructure are shaping AI in mining market in North America. Autonomous haulage systems, predictive maintenance platforms, and AI-powered exploration tools are already being used by mining companies in the U.S. and Canada. Digital transformation is mostly about making operations safer, hiring more workers, and boosting productivity in this area. In Europe, strict rules about sustainability and following environmental laws drive the market. European miners are putting money into AI to make their operations more energy-efficient, keep track of emissions, and find robotic mining solutions. The government is also helping them build sustainable mining ecosystems.

AI is being used more in mining in the Asia-Pacific region because of the fast growth of the industry, the availability of mineral resources, and government-backed programs to digitize. Countries like Australia, China, and India are using AI-powered autonomous machines, real-time ore processing, and exploration platforms to improve efficiency and ensure they have enough important minerals. In LAMEA, on the other hand, AI adoption is still in its early stages but has significant potential. In Latin America, AI is being used to make large-scale mining safer and more efficient. In the Middle East and Africa, AI is being used increasingly to improve energy use, resource management, and remote monitoring in difficult mining areas.

Recent Strategies Deployed in the Market

• Apr-2025: Datarock Pty Ltd teamed up with DataArk Systems to launch a quantum-secure, ransomware-proof database tailored for AI and analytics applications. This solution enhances cybersecurity and data integrity for mining operations, supporting safer and more reliable AI-driven decision-making in the mining sector's digital transformation efforts.
• Dec-2024: Sandvik AB announced the acquisition of Universal Field Robots to develop autonomous robotic solutions for mining. This collaboration will enhance productivity and safety through AI-powered automation, marking a strategic step toward advanced, intelligent mining operations that utilize robotics and intelligent field systems.
• Oct-2024: Komatsu Ltd. announced the acquisition of Octodots Analytics, a Chilean provider of mining optimization software, to enhance its AI capabilities. Integrated into Komatsu's Modular ecosystem-which builds on its DISPATCH fleet management platform-the acquisition will advance AI-driven data integration and decision-making across machine, site, and enterprise levels in mining operations.
• May-2023: BHP Group Limited teamed up with Microsoft to deploy Azure Machine Learning and real-time data analytics at its Escondida copper mine in Chile, using AI-driven recommendations to optimise concentrator operations and boost copper recovery. These highlights growing adoption of digital technologies in mining, reinforcing the AI-in-mining market trend.
• Apr-2021: IBM Corporation announced the acquisition of myInvenio, a process mining software provider, to boost AI-driven automation. This acquisition enables businesses, including mining companies, to map, analyze, and optimize workflows using AI for improved efficiency and reduced operational costs.

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 (Rio Tinto International Holdings Limited)

Global AI In Mining Market Report Segmentation

By Type

• Surface Mining
• Underground Mining
• Other Type

By Deployment

• Cloud
• Hybrid
• On-premises

By Technology

• Machine Learning & Deep Learning
• Robotics & Automation
• Computer Vision
• NLP
• Other Technology

By Geography

• North America
  • US
  • Canada
  • Mexico
  • Rest of North America
• Europe
  • Germany
  • UK
  • France
  • Russia
  • Spain
  • Italy
  • Rest of Europe
• Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Malaysia
  • Rest of Asia Pacific
• LAMEA
  • Brazil
  • Argentina
  • UAE
  • Saudi Arabia
  • South Africa
  • Nigeria
  • Rest of LAMEA

Table of Contents

Chapter 1. Market Scope & Methodology

• 1.1 Market Definition
• 1.2 Objectives
• 1.3 Market Scope
• 1.4 Segmentation
  • 1.4.1 Global AI In Mining Market, by Type
  • 1.4.2 Global AI In Mining Market, by Deployment
  • 1.4.3 Global AI In Mining Market, by Technology
  • 1.4.4 Global AI In Mining Market, by Geography
• 1.5 Methodology for the research

Chapter 2. Market at a Glance

• 2.1 Key Highlights

Chapter 3. Market Overview

• 3.1 Introduction
  • 3.1.1 Overview
    • 3.1.1.1 Market Composition and Scenario
• 3.2 Key Factors Impacting the Market
  • 3.2.1 Market Drivers
  • 3.2.2 Market Restraints
  • 3.2.3 Market Opportunities
  • 3.2.4 Market Challenges

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

• 9.1 Technology Development
• 9.2 Data Acquisition and Integration
• 9.3 Infrastructure and Deployment
• 9.4 AI Application Areas
• 9.5 Integration and Services
• 9.6 Output Optimization and Decision-Making
• 9.7 Feedback and Continuous Learning

Chapter 10. Key Customer Criteria - AI In Mining Market

Chapter 11. Global AI In Mining Market by Type

• 11.1 Global Surface Mining Market by Region
• 11.2 Global Underground Mining Market by Region
• 11.3 Global Other Type Market by Region

Chapter 12. Global AI In Mining Market by Deployment

• 12.1 Global Cloud Market by Region
• 12.2 Global Hybrid Market by Region
• 12.3 Global On-premises Market by Region

Chapter 13. Global AI In Mining Market by Technology

• 13.1 Global Machine Learning & Deep Learning Market by Region
• 13.2 Global Robotics & Automation Market by Region
• 13.3 Global Computer Vision Market by Region
• 13.4 Global NLP Market by Region
• 13.5 Global Other Technology Market by Region

Chapter 14. Global AI In Mining Market by Region

• 14.1 North America AI In Mining Market
  • 14.1.1 Key Factors Impacting the Market
    • 14.1.1.1 Market Drivers
    • 14.1.1.2 Market Restraints
    • 14.1.1.3 Market Opportunities
    • 14.1.1.4 Market Challenges
  • 14.1.2 Market Trends - North America AI In Mining Market
  • 14.1.3 State of Competition - North America AI In Mining Market
  • 14.1.4 North America AI In Mining Market by Type
    • 14.1.4.1 North America Surface Mining Market by Country
    • 14.1.4.2 North America Underground Mining Market by Country
    • 14.1.4.3 North America Other Type Market by Country
  • 14.1.5 North America AI In Mining Market by Deployment
    • 14.1.5.1 North America Cloud Market by Country
    • 14.1.5.2 North America Hybrid Market by Country
    • 14.1.5.3 North America On-premises Market by Country
  • 14.1.6 North America AI In Mining Market by Technology
    • 14.1.6.1 North America Machine Learning & Deep Learning Market by Country
    • 14.1.6.2 North America Robotics & Automation Market by Country
    • 14.1.6.3 North America Computer Vision Market by Country
    • 14.1.6.4 North America NLP Market by Country
    • 14.1.6.5 North America Other Technology Market by Country
  • 14.1.7 North America AI In Mining Market by Country
    • 14.1.7.1 US AI In Mining Market
      • 14.1.7.1.1 US AI In Mining Market by Type
      • 14.1.7.1.2 US AI In Mining Market by Deployment
      • 14.1.7.1.3 US AI In Mining Market by Technology
    • 14.1.7.2 Canada AI In Mining Market
      • 14.1.7.2.1 Canada AI In Mining Market by Type
      • 14.1.7.2.2 Canada AI In Mining Market by Deployment
      • 14.1.7.2.3 Canada AI In Mining Market by Technology
    • 14.1.7.3 Mexico AI In Mining Market
      • 14.1.7.3.1 Mexico AI In Mining Market by Type
      • 14.1.7.3.2 Mexico AI In Mining Market by Deployment
      • 14.1.7.3.3 Mexico AI In Mining Market by Technology
    • 14.1.7.4 Rest of North America AI In Mining Market
      • 14.1.7.4.1 Rest of North America AI In Mining Market by Type
      • 14.1.7.4.2 Rest of North America AI In Mining Market by Deployment
      • 14.1.7.4.3 Rest of North America AI In Mining Market by Technology
• 14.2 Europe AI In Mining Market
  • 14.2.1 Key Factors Impacting the Market
    • 14.2.1.1 Market Drivers
    • 14.2.1.2 Market Restraints
    • 14.2.1.3 Market Opportunities
    • 14.2.1.4 Market Challenges
  • 14.2.2 Market Trends - Europe AI In Mining Market
  • 14.2.3 State of Competition - Europe AI In Mining Market
  • 14.2.4 Europe AI In Mining Market by Type
    • 14.2.4.1 Europe Surface Mining Market by Country
    • 14.2.4.2 Europe Underground Mining Market by Country
    • 14.2.4.3 Europe Other Type Market by Country
  • 14.2.5 Europe AI In Mining Market by Deployment
    • 14.2.5.1 Europe Cloud Market by Country
    • 14.2.5.2 Europe Hybrid Market by Country
    • 14.2.5.3 Europe On-premises Market by Country
  • 14.2.6 Europe AI In Mining Market by Technology
    • 14.2.6.1 Europe Machine Learning & Deep Learning Market by Country
    • 14.2.6.2 Europe Robotics & Automation Market by Country
    • 14.2.6.3 Europe Computer Vision Market by Country
    • 14.2.6.4 Europe NLP Market by Country
    • 14.2.6.5 Europe Other Technology Market by Country
  • 14.2.7 Europe AI In Mining Market by Country
    • 14.2.7.1 Germany AI In Mining Market
      • 14.2.7.1.1 Germany AI In Mining Market by Type
      • 14.2.7.1.2 Germany AI In Mining Market by Deployment
      • 14.2.7.1.3 Germany AI In Mining Market by Technology
    • 14.2.7.2 UK AI In Mining Market
      • 14.2.7.2.1 UK AI In Mining Market by Type
      • 14.2.7.2.2 UK AI In Mining Market by Deployment
      • 14.2.7.2.3 UK AI In Mining Market by Technology
    • 14.2.7.3 France AI In Mining Market
      • 14.2.7.3.1 France AI In Mining Market by Type
      • 14.2.7.3.2 France AI In Mining Market by Deployment
      • 14.2.7.3.3 France AI In Mining Market by Technology
    • 14.2.7.4 Russia AI In Mining Market
      • 14.2.7.4.1 Russia AI In Mining Market by Type
      • 14.2.7.4.2 Russia AI In Mining Market by Deployment
      • 14.2.7.4.3 Russia AI In Mining Market by Technology
    • 14.2.7.5 Spain AI In Mining Market
      • 14.2.7.5.1 Spain AI In Mining Market by Type
      • 14.2.7.5.2 Spain AI In Mining Market by Deployment
      • 14.2.7.5.3 Spain AI In Mining Market by Technology
    • 14.2.7.6 Italy AI In Mining Market
      • 14.2.7.6.1 Italy AI In Mining Market by Type
      • 14.2.7.6.2 Italy AI In Mining Market by Deployment
      • 14.2.7.6.3 Italy AI In Mining Market by Technology
    • 14.2.7.7 Rest of Europe AI In Mining Market
      • 14.2.7.7.1 Rest of Europe AI In Mining Market by Type
      • 14.2.7.7.2 Rest of Europe AI In Mining Market by Deployment
      • 14.2.7.7.3 Rest of Europe AI In Mining Market by Technology
• 14.3 Asia Pacific AI In Mining Market
  • 14.3.1 Key Factors Impacting the Market
    • 14.3.1.1 Market Drivers
    • 14.3.1.2 Market Restraints
    • 14.3.1.3 Market Opportunities
    • 14.3.1.4 Market Challenges
  • 14.3.2 Market Trends - Asia Pacific AI In Mining Market
  • 14.3.3 State of Competition - Asia Pacific AI In Mining Market
  • 14.3.4 Asia Pacific AI In Mining Market by Type
    • 14.3.4.1 Asia Pacific Surface Mining Market by Country
    • 14.3.4.2 Asia Pacific Underground Mining Market by Country
    • 14.3.4.3 Asia Pacific Other Type Market by Country
  • 14.3.5 Asia Pacific AI In Mining Market by Deployment
    • 14.3.5.1 Asia Pacific Cloud Market by Country
    • 14.3.5.2 Asia Pacific Hybrid Market by Country
    • 14.3.5.3 Asia Pacific On-premises Market by Country
  • 14.3.6 Asia Pacific AI In Mining Market by Technology
    • 14.3.6.1 Asia Pacific Machine Learning & Deep Learning Market by Country
    • 14.3.6.2 Asia Pacific Robotics & Automation Market by Country
    • 14.3.6.3 Asia Pacific Computer Vision Market by Country
    • 14.3.6.4 Asia Pacific NLP Market by Country
    • 14.3.6.5 Asia Pacific Other Technology Market by Country
  • 14.3.7 Asia Pacific AI In Mining Market by Country
    • 14.3.7.1 China AI In Mining Market
      • 14.3.7.1.1 China AI In Mining Market by Type
      • 14.3.7.1.2 China AI In Mining Market by Deployment
      • 14.3.7.1.3 China AI In Mining Market by Technology
    • 14.3.7.2 Japan AI In Mining Market
      • 14.3.7.2.1 Japan AI In Mining Market by Type
      • 14.3.7.2.2 Japan AI In Mining Market by Deployment
      • 14.3.7.2.3 Japan AI In Mining Market by Technology
    • 14.3.7.3 India AI In Mining Market
      • 14.3.7.3.1 India AI In Mining Market by Type
      • 14.3.7.3.2 India AI In Mining Market by Deployment
      • 14.3.7.3.3 India AI In Mining Market by Technology
    • 14.3.7.4 South Korea AI In Mining Market
      • 14.3.7.4.1 South Korea AI In Mining Market by Type
      • 14.3.7.4.2 South Korea AI In Mining Market by Deployment
      • 14.3.7.4.3 South Korea AI In Mining Market by Technology
    • 14.3.7.5 Australia AI In Mining Market
      • 14.3.7.5.1 Australia AI In Mining Market by Type
      • 14.3.7.5.2 Australia AI In Mining Market by Deployment
      • 14.3.7.5.3 Australia AI In Mining Market by Technology
    • 14.3.7.6 Malaysia AI In Mining Market
      • 14.3.7.6.1 Malaysia AI In Mining Market by Type
      • 14.3.7.6.2 Malaysia AI In Mining Market by Deployment
      • 14.3.7.6.3 Malaysia AI In Mining Market by Technology
    • 14.3.7.7 Rest of Asia Pacific AI In Mining Market
      • 14.3.7.7.1 Rest of Asia Pacific AI In Mining Market by Type
      • 14.3.7.7.2 Rest of Asia Pacific AI In Mining Market by Deployment
      • 14.3.7.7.3 Rest of Asia Pacific AI In Mining Market by Technology
• 14.4 LAMEA AI In Mining Market
  • 14.4.1 Key Factors Impacting the Market
    • 14.4.1.1 Market Drivers
    • 14.4.1.2 Market Restraints
    • 14.4.1.3 Market Opportunities
    • 14.4.1.4 Market Challenges
  • 14.4.2 Market Trends - LAMEA AI In Mining Market
  • 14.4.3 State of Competition - LAMEA AI In Mining Market
  • 14.4.4 LAMEA AI In Mining Market by Type
    • 14.4.4.1 LAMEA Surface Mining Market by Country
    • 14.4.4.2 LAMEA Underground Mining Market by Country
    • 14.4.4.3 LAMEA Other Type Market by Country
  • 14.4.5 LAMEA AI In Mining Market by Deployment
    • 14.4.5.1 LAMEA Cloud Market by Country
    • 14.4.5.2 LAMEA Hybrid Market by Country
    • 14.4.5.3 LAMEA On-premises Market by Country
  • 14.4.6 LAMEA AI In Mining Market by Technology
    • 14.4.6.1 LAMEA Machine Learning & Deep Learning Market by Country
    • 14.4.6.2 LAMEA Robotics & Automation Market by Country
    • 14.4.6.3 LAMEA Computer Vision Market by Country
    • 14.4.6.4 LAMEA NLP Market by Country
    • 14.4.6.5 LAMEA Other Technology Market by Country
  • 14.4.7 LAMEA AI In Mining Market by Country
    • 14.4.7.1 Brazil AI In Mining Market
      • 14.4.7.1.1 Brazil AI In Mining Market by Type
      • 14.4.7.1.2 Brazil AI In Mining Market by Deployment
      • 14.4.7.1.3 Brazil AI In Mining Market by Technology
    • 14.4.7.2 Argentina AI In Mining Market
      • 14.4.7.2.1 Argentina AI In Mining Market by Type
      • 14.4.7.2.2 Argentina AI In Mining Market by Deployment
      • 14.4.7.2.3 Argentina AI In Mining Market by Technology
    • 14.4.7.3 UAE AI In Mining Market
      • 14.4.7.3.1 UAE AI In Mining Market by Type
      • 14.4.7.3.2 UAE AI In Mining Market by Deployment
      • 14.4.7.3.3 UAE AI In Mining Market by Technology
    • 14.4.7.4 Saudi Arabia AI In Mining Market
      • 14.4.7.4.1 Saudi Arabia AI In Mining Market by Type
      • 14.4.7.4.2 Saudi Arabia AI In Mining Market by Deployment
      • 14.4.7.4.3 Saudi Arabia AI In Mining Market by Technology
    • 14.4.7.5 South Africa AI In Mining Market
      • 14.4.7.5.1 South Africa AI In Mining Market by Type
      • 14.4.7.5.2 South Africa AI In Mining Market by Deployment
      • 14.4.7.5.3 South Africa AI In Mining Market by Technology
    • 14.4.7.6 Nigeria AI In Mining Market
      • 14.4.7.6.1 Nigeria AI In Mining Market by Type
      • 14.4.7.6.2 Nigeria AI In Mining Market by Deployment
      • 14.4.7.6.3 Nigeria AI In Mining Market by Technology
    • 14.4.7.7 Rest of LAMEA AI In Mining Market
      • 14.4.7.7.1 Rest of LAMEA AI In Mining Market by Type
      • 14.4.7.7.2 Rest of LAMEA AI In Mining Market by Deployment
      • 14.4.7.7.3 Rest of LAMEA AI In Mining Market by Technology

Chapter 15. Company Profiles

• 15.1 IBM Corporation
  • 15.1.1 Company Overview
  • 15.1.2 Financial Analysis
  • 15.1.3 Regional & Segmental Analysis
  • 15.1.4 Research & Development Expenses
  • 15.1.5 Recent strategies and developments:
    • 15.1.5.1 Acquisition and Mergers:
  • 15.1.6 SWOT Analysis
• 15.2 Komatsu Ltd.
  • 15.2.1 Company Overview
  • 15.2.2 Financial Analysis
  • 15.2.3 Segmental and Regional Analysis
  • 15.2.4 Research & Development Expenses
  • 15.2.5 Recent strategies and developments:
    • 15.2.5.1 Acquisition and Mergers:
  • 15.2.6 SWOT Analysis
• 15.3 Caterpillar, Inc.
  • 15.3.1 Company Overview
  • 15.3.2 Financial Analysis
  • 15.3.3 Segmental and Regional Analysis
  • 15.3.4 Research & Development Expense
  • 15.3.5 SWOT Analysis
• 15.4 Sandvik AB
  • 15.4.1 Company Overview
  • 15.4.2 Financial Analysis
  • 15.4.3 Segmental and Regional Analysis
  • 15.4.4 Research & Development Expenses
  • 15.4.5 Recent strategies and developments:
    • 15.4.5.1 Acquisition and Mergers:
  • 15.4.6 SWOT Analysis
• 15.5 SAP SE
  • 15.5.1 Company Overview
  • 15.5.2 Financial Analysis
  • 15.5.3 Regional Analysis
  • 15.5.4 Research & Development Expense
  • 15.5.5 SWOT Analysis
• 15.6 Microsoft Corporation
  • 15.6.1 Company Overview
  • 15.6.2 Financial Analysis
  • 15.6.3 Segmental and Regional Analysis
  • 15.6.4 Research & Development Expenses
  • 15.6.5 SWOT Analysis
• 15.7 Datarock Pty Ltd
  • 15.7.1 Company Overview
  • 15.7.2 Recent strategies and developments:
    • 15.7.2.1 Partnerships, Collaborations, and Agreements:
• 15.8 Earth AI Inc.
  • 15.8.1 Company Overview
• 15.9 BHP Group Limited
  • 15.9.1 Company Overview
  • 15.9.2 Financial Analysis
  • 15.9.3 Segmental and Regional Analysis
  • 15.9.4 Recent strategies and developments:
    • 15.9.4.1 Partnerships, Collaborations, and Agreements:
  • 15.9.5 SWOT Analysis
• 15.10. Rio Tinto PLC (Rio Tinto International Holdings Limited)
  • 15.10.1 Company Overview
  • 15.10.2 Financial Analysis
  • 15.10.3 Segmental and Regional Analysis
  • 15.10.4 Research & Development Expenses
  • 15.10.5 SWOT Analysis

Chapter 16. Winning Imperatives of AI In Mining Market