PLEASE NOTE: This is the first generated blog and each new run of the code will be different. This should not be taken as the ground truth. The mining industry has been globalised for many years, with companies operating in multiple countries to maximise production and profits. However, this has led to a number of challenges, including the need to operate in different regulatory environments, manage different labour forces, and navigate different tax systems. Additionally, the volatility of commodity prices has also led to challenges for the industry. Despite these challenges, the mining industry remains a key driver of globalisation, and offers a number of opportunities for companies looking to expand into new markets.

Mining firms may use artificial intelligence and machine learning to discover minerals to mine.

It was only a few years earlier that Artificial Intelligence (AI) was a brand-new concept that was much too technical for anyone to anticipate how it will affect the world. Things have surely altered by the year 2019. It has changed the game for a variety of sectors, including significant participants in the mining industry. Small increases in yields, pace, and efficiency may have a huge influence on the mining sector, therefore increasing efficiency and productivity is critical for profitability. Now, let's take a look at how the companies which are using AI in the mining sector.

Opportunities for digital technologies implementation, including implementation of artificial intelligence, are being implemented in the mining sector. Technologies help to save money and to solve problems that humans can't solve. McKinseyestimates that by 2035, the use of data analysis and digital technologies will help coal, iron ore, and copper producers save between $290 billion and $390 billion annually. Digital technologies and artificial intelligence enable companies to extract minerals in hard-to-reach places and under extreme weather conditions. This article first appeared in Mining Review Africa Issue 10, 2019 Read the full digimag here or subscribe to receive a print copy here This means that in an environment when mineral resources are becoming increasingly scarce, it is possible to develop deposits that used to be inaccessible, to do it without endangering lives of employees and to minimize human errors that often lead to costly mistakes.

Here is an unavoidable truth. Resource extraction is hard physical work. And perhaps this is the very reason modern investors have wandered away from mining--whether or not it's to their benefit. New AI methods may change that. Just like society, many investors today are overlooking the connection between the products we use and the source of the materials to make them. And yet it's still true that "if you cannot grow it, you have to mine it."

"Graduates at IBM are coming into roles where you provide services to a range of different industries as opposed to just working in one," she says. "From a career perspective, they can move across different industries but they also move across different functions. You retain your core expertise but you also get to do different jobs because of the diversity of our clients." IBM works with dozens of Australia's biggest companies using Watson to drive machine learning and data analysis within business, and has the advantage of being able to supply whole teams of experts as challenges arise. In contrast, even big industry employers often have only a few specialists in key areas.

Accenture has announced plans to launch a new Applied Intelligence Studio for Mining in Johannesburg. The studio will apply the latest in data science and artificial intelligence technologies with new data sources for real-time co-creation of innovative digital solutions that can help mining companies solve some of their hardest analytical problems. It is expected to open in February 2019. "They are increasingly looking to apply advanced analytics to reimagine processes, unlock trapped value, and drive operational excellence in their businesses today and position themselves for growth tomorrow." "Volatile commodity prices, rising input costs and changing global demand for commodities require mining companies to rethink their strategies and business models to remain competitive," said Rachael Bartels, a senior managing director who leads Accenture's mining business globally.

As the thirst for technology increases and the demand for smartphones, electric cars and other complex technological devices grows, the amount of resources, minerals and metals we need will only increase, but can we meet this demand? There are few sectors and industries that have not been impacted by technological advancement. Whether it's improving efficiency, enhancing transparency or transforming the supply chain, big data, machine learning and AI are poised to reshape the mining sector as we know it; and the timing couldn't be any better. At the recent Big Data and AI conference held in Toronto, the topic of mining disruption through technology was front and center. Speaker Denis Laviolette, president and CEO of GoldSpot Discovery, highlighted the need for the mining sector to not only embrace the recent advancements, but to also quickly look for ways to integrate these innovations into its business model.