Artificial Intelligence (AI) in Mining - Thematic Intelligence
Summary
Artificial intelligence (AI) refers to software-based systems that use data inputs to make decisions on their own. Recent progress in machine-learning (ML) algorithms (e.g., OpenAI's GPT-4) and increasing computing power have enabled AI to solve problems in real-time. GlobalData estimates the total AI market will be worth $909 billion in 2030, growing at a compound annual growth rate (CAGR) of 35.2% between 2022 and 2030.
Artificial intelligence (AI) has been disrupting sectors worldwide, with generative AI increasing interest—especially following the release of ChatGPT in November 2022. This can be seen in GlobalData’s market forecast for AI, which will reach $908.7 billion by 2030, with a CAGR of 35.2% between 2022 and 2030.
This theme is extremely prominent in mining, with companies desperate to find new methods to improve productivity and minimize costs, while also finding new sources of minerals. AI is already playing a big role; however, its influence will only grow in the years to come.
It is an expensive investment for mining companies already suffering after the COVID-19 pandemic and the economic downturn that has come with it. The mining companies will be forced to reprioritize funds if they want to explore newer AI technologies.
Scope
- AI enables mining companies to use autonomous machinery and data to improve efficiency and productivity and reduce downtime. These tools can reduce operational costs for mining companies. Autonomous machinery can also reduce the requirement for on-site workers, thereby removing them from potential hazards and improving safety. AI can help companies better understand the environment and terrain where exploitation is to begin. According to Glencore, this can save firms up to 80% of unnecessary costs
- Understand the impact of the AI theme on the mining sector. Understand the impact of generative AI on the mining sector. Access the latest data on the AI theme within the mining sector. Identify the leading digital transformation efforts from mining companies through investment into the AI theme. Access case study insights on leading players within the AI theme.
- Executive Summary
- Players
- Mining Challenges
- The Impact of AI on Mining
- How AI helps tackle the challenge of safety
- How AI helps resolve the challenge of productivity
- How AI helps resolve the challenge of ESG
- How AI helps resolve the challenge of cost control
- How AI helps resolve the challenge of resource development
- Case Studies
- BHP Billiton’s AI drowsiness cap reduces vehicular accidents
- XCMG Machinery is using AI to improve the safety of its products
- Champion mining AI-based drilling system with Caterpillar
- Kobold Metals is using AI to locate minerals in less obvious areas
- Akkio’s generative AI program predicting commodity price fluctuations
- Agnico Eagle’s use of AI for predictive maintenance
- AI Timeline
- Market Size and Growth Forecasts
- Signals
- Mergers and acquisitions
- Patent trends
- Hiring trends
- AI Value Chain
- Hardware
- Semiconductors
- Cameras
- Sensors and lasers
- Servers
- Storage devices
- Networking equipment
- Edge equipment
- Data management
- Data governance and security
- Data storage
- Data processing
- Data aggregation
- Data integration
- Foundational AI
- Data science
- Machine learning
- 3D modeling
- Knowledge representation and reasoning
- Visualization engines
- Advanced AI capabilities
- Human-AI interaction
- Decision-making
- Motion
- Creation (also known as generative AI)
- Sentience
- Delivery
- Hardware appliance
- Licensed software
- Artificial intelligence as a service
- Companies
- Leading AI adopters in mining
- Leading AI vendors
- Specialist AI vendors in mining
- Sector Scorecard
- Mining sector scorecard
- Who’s who
- Thematic screen
- Valuation screen
- Risk screen
- Glossary
- Further Reading
- GlobalData reports
- Our Thematic Research Methodology
- About GlobalData
- Contact Us
- List of Tables
- Table 1: Key challenges facing the mining sector.
- Table 2: Mergers and acquisitions
- Table 3: Leading AI adopters in mining
- Table 4: Leading AI vendors
- Table 5: Specialist AI vendors in mining
- Table 6: Glossary
- Table 7: GlobalData reports
- List of Figures
- Figure 1: Key players in AI
- Figure 2: AI is at the forefront of mining investment over the next two years
- Figure 3: Thematic impact assessment
- Figure 4: BHP is leading in ownership of autonomous trucks
- Figure 5: Champion’s autonomous “drill-to-mill” system
- Figure 6: Unmet demand for critical minerals
- Figure 7: Akkio’s generative AI commodity price forecasting model
- Figure 8: The AI story
- Figure 9: The global AI market will be worth $909 billion by 2030
- Figure 10: AI-related patent publications in the consumer goods sector peaked in 2021
- Figure 11: Underground equipment has the largest number of AI patents
- Figure 12: AI-related jobs continue to increase in the mining sector
- Figure 13: The AI value chain - An overview
- Figure 14: The AI value chain - Hardware - semiconductors
- Figure 15: The AI value chain - Hardware - cameras
- Figure 16: The AI value chain - Hardware – sensors and lasers
- Figure 17: The AI value chain - Hardware – servers
- Figure 18: The AI value chain - Hardware – storage devices
- Figure 19: The AI value chain - Hardware – networking equipment
- Figure 20: The AI value chain - Hardware – edge equipment
- Figure 21: The AI value chain - Data management
- Figure 22: The AI value chain - Foundational AI – data science
- Figure 23: The AI value chain - Foundational AI – machine learning
- Figure 24: The AI value chain - Foundational AI – 3D modeling
- Figure 25: The AI value chain - Foundational AI – knowledge representation and reasoning
- Figure 26: The AI value chain - Foundational AI – visualization engines
- Figure 27: The AI value chain - Advanced AI capabilities– human-AI interaction
- Figure 28: The AI value chain - Advanced AI capabilities– decision-making
- Figure 29: The AI value chain - Advanced AI capabilities– motion
- Figure 30: The AI value chain - Advanced AI capabilities– creation
- Figure 31: The AI value chain - Advanced AI capabilities– sentience
- Figure 32: The AI value chain - Delivery
- Figure 33: Who does what in the mining space?
- Figure 34: Thematic screen
- Figure 35: Valuation screen
- Figure 36: Risk screen
- Figure 37: Our five-step approach for generating a sector scorecard
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