Artificial Intelligence (AI) in Mining Market Set to Surge Significantly During 2021-2030

The rising demand for advanced technologies, artificial intelligence, and machine learning to spot the location, analyze patterns, and optimize resources to reduce waste drives the growth of the market.

In addition, autonomous mining equipment equipped with artificial intelligence is set to increase overall productivity and minimize fatal mistakes. However, limited understanding of the deployment of AI‑related technology and poor testing method to generate insights hamper the artificial intelligence in mining market growth.

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Furthermore, the adoption of the latest AI technology to make faster decisions with more accuracy, boosting efficiency through eliminating errors, and improving health and safety measures are the factors expected to provide lucrative opportunities for artificial intelligence in the mining market.

COVID-19 scenario analysis:

• The COVID-19 virus has affected a lot of industries due to lockdown imposed by the governments of 180+ nations. This led to the downfall of global economy. However, the mining industries were less affected compared to rest of the industries. Mineral extraction has become a crucial step to drive the economy. Some countries have a vast mineral resource, and their economies are totally dependent on it.

• As several industries were shut down due to lockdown and consumption of minerals was also decreased, which gave the opportunity to the mineral extraction companies to extract minerals and keep it as reserve for the future demand. Artificial intelligence helps to keep low operational cost by spotting the exact location of the mineral in deep earth, using historical data, data analytics, and others.

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AI-driven automation enriches digital control systems and programmable logic devices to improve consistency and accuracy at mining sites. It speeds up discovery and exploration phases by predicting target areas and using soil samples for quantification of mineral deposit as well as impurities in the extracted output.

Artificial intelligence also integrates robotic automation and IoT to manage autonomous drilling techniques and carrying fleets. It allows digital mines built with sensor network technologies to take advantage of IoT data for real-time surveillance and operations.

Mining is not referred as environment-friendly method as it is disruptive and causes negative impact on the environment. The implementation of artificial intelligence in this segment is expected to reduce the environmental impact.

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The deployment of cameras and sensors in the mines for constant surveillance of the operations is performed inside and outside mines. These devices are able to monitor extraction and mining activities by reducing the spread of waste and harmful materials in the environment.

Regular vibrations in the surfaces, temperature changes, and other several events can all be identified by machine learning.

Companies covered in this report are Glencore PLC, China Minmetals Corporation, ArcelorMittal SA, POSCO, BHP Group PLC, Rio Tinto Limited, Vale SA, Jiangxi Copper Ord Shs A, Anglo American PLC, and Aluminum Corp. of China Limited.

Key benefits of the report:

• This study presents analytical depiction of the artificial intelligence (AI) in mining market along with the current trends and future estimations to determine the imminent investment pockets.

• The report presents information related to key drivers, restraints, and opportunities along with detailed analysis of the artificial intelligence in mining market share.

• The current artificial intelligence in mining market is quantitatively analyzed from 2021 to 2030 to highlight the market growth scenario.

• Porter's five forces analysis illustrates the potency of buyers & suppliers in the market.

• The report provides a detailed market analysis based on the present and future competitive intensity of artificial intelligence in mining market.

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