The mining industry is under more pressure than ever to increase efficiencies. This comes as declining ore grades and more disparate and remote deposits create greater challenges in securing new resources, and rising mining costs drive the need for greater productivity at the mine site. At the same time, there is a strong focus on ensuring safety and sustainability within mines. Artificial intelligence (AI) in the mining industry can address many of these challenges and inefficiencies through several key technologies in the value chain, including computer vision, smart robots, data science, and machine learning.

Leading miners in artificial intelligence

Exploration costs can be reduced by using AI to identify the most likely locations of mineral deposits. Predictive maintenance can ensure that equipment defects are solved before they become extremely costly and ensure that equipment downtime is kept to a minimum, increasing productivity. Smart sensors and cameras aid automated equipment while also monitoring the safety of workers in mines.

Leading adopters of AI for mining are Goldcorp , BHP, Rio Tinto , Freeport-McMoRan , Fortescue, Newcrest , Barrick Gold , and Dundee Precious Metals.

Discover the leading artificial intelligence companies in mining

Using its experience in the sector, Mining Technology has listed some of the leading companies providing products and services related to artificial intelligence.

The information provided in the download document is drafted for mining executives and technology leaders involved in AI mining solutions.

The download contains detailed information on suppliers and their product offerings, alongside contact details to aid purchase or hiring decisions.

Amongst the leading artificial intelligence suppliers are Goldspot Discoveries , Earth AI , Minerva Intelligence , DroneDeploy , Hikvision , Imago , Caterpillar , Komatsu and Microsoft.

Future of artificial intelligence in mining

Mining firms will spend $218m on AI platforms worldwide by 2024. This is up from $76m in 2019, representing a compound annual growth rate (CAGR) of 23.4%.

Total spending on AI mining solutions is difficult to estimate. There are two main reasons for this. Firstly, AI is an intrinsic part of many applications and functions, making it almost impossible to identify revenue explicitly generated by AI. Secondly, the range of sub-sets and technologies that make up AI can be challenging to locate and track.

With falling yields and increasingly hostile locations, AI is more important than ever in the mining industry. AI has reached a point where it can effectively impact every section of the mining value chain, from prospecting to extraction, processing, and even marketing.