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Artificial Intelligence (AI) in Mining - Thematic Intelligence

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    Report

  • 69 Pages
  • July 2023
  • Region: Global
  • GlobalData
  • ID: 5860909
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. The publisher 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 the publisher'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

1. Executive Summary

2. Players

3. Consumer Challenges

4. The Impact of AI on Consumer

5. Case Studies

6. AI Timeline

7. Market Size and Growth Forecasts

8. Signals
8.1. Mergers and acquisitions
8.2. Patent trends
8.3. Company filings trends
8.4. Hiring trends
8.5. Social media trends

9. AI Value Chain
9.1. Hardware
9.2. Data management
9.3. Foundational AI
9.4. Advanced AI capabilities
9.5. Delivery

10. Companies

11. Sector Scorecards

12. Glossary

13. Further Reading

14. Thematic Research Methodology

15. About the Publisher

16. Contact the Publisher

Companies Mentioned (Partial List)

A selection of companies mentioned in this report includes, but is not limited to:

  • ABB
  • Agnico Eagle
  • Akkio
  • Alibaba
  • Alphabet
  • Amazon
  • AMD
  • Apple
  • Baidu
  • BHP
  • Boliden
  • C3.ai
  • Caterpillar
  • Champion
  • DroneDeploy
  • Earth AI
  • EVRAZ
  • Fortescue
  • Freeport McMoRan
  • Goldspot Discoveries
  • Hikvision
  • IBM
  • Imago
  • Kobold Metals
  • Komatsu
  • Minerva Intelligence
  • Newcrest
  • Rio Tinto
  • Sandvik
  • SenseTime
  • Teck Resources
  • Tesla
  • Vale