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Artificial Intelligence (AI) in Mining - Thematic Intelligence

Publisher GlobalData
Published Jul 17, 2023
Length 74 Pages
SKU # GBDT18140980

Description

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
Reasons to Buy
  • 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.

Table of Contents

74 Pages
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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