Rudi’s View: The AI Promise Is Broadening

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By Rudi Filapek-Vandyck, Editor

The race to become the world’s largest company by market capitalisation is now decided by day-to-day share price fluctuations between Microsoft and Nvidia, two of the leading global beneficiaries of our modern day revolution that is AI.

In Australia, companies with direct exposure to the global infrastructure built to support AI and its further development have equally enjoyed plenty of investor interest. Think Goodman Group ((GMG)), but also NextDC ((NXT)), Infratil ((IFT)), Macquarie Technology ((MAQ)) and DigiCo Infrastructure REIT ((DGT)).

Equally noteworthy: judging from recent company announcements, AI is getting ready to step outside of the realm of infrastructure and machine learning development and into the wider corporate world where operational inefficiencies are waiting to be identified and addressed through new tech tools and applications.

Increasingly, Australian companies are becoming active participators with the term AI starting to appear regularly in corporate briefings with financial analysts and in press releases.

AI Announcements Are Multiplying

CommBank ((CBA)), the world’s largest bank and number one index constituent locally, has employed over 2000 AI models processing 157 billion data points daily to make circa 55 million decisions; all aimed to enhance the customer experience through personalised and responsive banking services.

Financial services provider Insignia Financial ((IFL)) is hoping implementing generative AI in its call centres and elsewhere through its network can assist with the relaunch of the MLC brand as well as reduce costs by 2030.

Australia’s largest telecommunications services provider, Telstra ((TLS)), is equally counting on an improved customer experience and lower costs. Telstra is planning to reduce its workforce by 2030 with AI expected to feature prominently in customer engagement, billing and IT in the broadest sense possible.

Reborn retailer Myer too is expecting to achieve an improved online shopping experience for customers, while the integration of AI should also provide Myer’s teams with better insights into customer behaviour, thus assisting with strategic decision-making.

AI For Miners

The promise of more operational efficiency and improved customer servicing doesn’t stop with service providers and manufacturers; mining and energy companies want their slice of the action too.

Barrick Gold has deployed an AI-powered exploration system at the Reko Diq copper-gold project in Pakistan in partnership with Fleet Space Technologies. The same Fleet Space is also assisting Rio Tinto ((RIO)) with 3-D mapping of the Rincon lithium project in Argentina.

Mid-tier iron ore producer Champion Iron ((CIA)) has teamed up with Caterpillar for the deployment of an AI-based automated drilling system at its Canadian Bloom Lake mine, with electric drills either remotely controlled or fully autonomous, handling the entire process from drilling through to ore hauling and milling.

Closer to home, Fortescue ((FMG)) has taken on the goal of developing the world’s first fully integrated autonomous haulage system for zero-emissions trucks.

The BHP Experience

To get a better feel and deeper insights into the importance for and deployment of AI inside the mining industry, FNArena spoke with BHP ((BHP)) Chief Technical Officer, Johan van Jaarsveld who was quick to explain the Big Australian has been applying AI for a number of years already.

It wasn’t even called AI at that time and mostly referred to as machine learning. Hence, the technology itself is not genuinely new to BHP. What is new is the high performance compute that has now been added, making problem solving a lot quicker.

Van Jaarsveld explains the practical advantage through one of BHP’s mining operations consisting of, say, 60 trucks and five loaders. When one of the loaders breaks down, the question on the ground arises as to where should trucks load instead to achieve the most optimised outcome.

Previously, answering that question would take hours to solve on a standard computer while, ideally, the answer should be known in eight minutes or so. This has now become possible and it is but one example as to why the application of machine learning technologies, now called AI, are becoming more common across the industry.

From an operational perspective, applying AI is now generating more tangible and relevant outcomes.

Escondida Delivering On Promise

Probably the most tangible example, as far as BHP is concerned, is the fact that AI has allowed to extract an additional US$200m of copper annually from the world’s largest copper mine, Escondida, located in Chile’s Atacama Desert.

Mine operator BHP owns 57.5% of Escondida, with other stakeholders Rio Tinto and Jeco, a Japanese consortium, owning respectively 30% and 12.5%.

Escondida consistently produces over one million tonnes of copper earch year, representing circa 5% of global supplies. As Van Jaarsveld explains, the implementation of AI at the concentrator is now allowing for real time optimisations of the control system, resulting in increased copper recovery, and thus in improved output.

Another touted achievement is some three billion litres of water have been saved from the Escondida operation since FY22.

Such tangible outcomes have increased confidence inside BHP there is opportunity through scaling the best of AI applications across the entire, vast value chain of the miner’s global network of assets and operations.

A Dedicated AI Team

The miner’s international workforce includes 6000 engineers spread across the world, of which the technology team makes up about one third. A dedicated digital team has been separated from the latter to concentrate on AI and on advancing its implementations. As this involves a cornucopia in various requirements, the digital team works in close conjunction with the technology team.

There are currently around 200 existing AI applications spread throughout the miner’s businesses and supply chain. According to the Chief Technical Officer, indications are some “really good” results can be achieved, ultimately leading to increased profitability, as has been the outcome at Escondida.

Safety of the workforce remains management’s number one priority, but this does not exclude AI implementations from achieving tangible results. BHP’s operation at Mining Area C has already delivered the evidence behind that statement.

Traditionally, whenever trains are loaded to transport iron ore to the port, people had to walk along the full length of each train to check for spillage on the tracks. These days AI is watching CCTV camera feeds with the ability to stop the loading whenever spillage is detected. This happens within seconds.

Not only is there no longer a need for people checking on the ground, AI has reduced total downtime by an estimated -50%. In practical terms, this means BHP can ship more tonnes. ASX-listed Deterra Royalties ((DRR)) receives quarterly royalty payments calculated as 1.232% of revenues in AUD from specific tenements within Mining Area C.

AI has equally generated benefit by identifying copper deposits where human geologists had failed to detect it. Two discoveries have been made in Australia and the US when machine learning models were scanning old data and found correlations impossible to identify with human eyes. Subsequent drilling confirmed the highly probable deposits were there.

BHP owns plenty of old geological data. Who knows what else might still be discovered that had been missed or overlooked in the past?

A Broad Innovation Drive

Time for a small side-step. From the innovation team comes the so-called muon topography, an approach to use cosmic-ray particles to look deep below the earth’s surface. This technique can be used in combination with AI to map ore bodies faster and more accurately than before.

Van Jaarsveld explains there’s a constant flux of these particles hitting the earth and some can travel deeply below the surface. He compares it with taking an X-ray via measuring what particles hit a detector versus particles that appear on the earth’s surface.

There’s a lot of image analysing and machine learning processing required to extract usable insights from these data, but he thinks it’s “a pretty cool idea”.

BHP is open to work with external expertise in partnerships where it sees complementary capabilities. While the goal is to scale AI relatively quickly throughout the entire organisation, since 2020 it also has its own venture capital unit, BHP Ventures, launched by Van Jaarsveld in his prior role as Chief Development Officer.

BHP Ventures invests in emerging companies and new technologies that might assist mining companies with enhancing sustainability practices and decarbonisation efforts. The portfolio consists of areas including low-carbon steelmaking, carbon capture and removal, as well as water treatment and renewable energy solutions, spread over more than 20 different early-stage companies.

BHP recently announced the establishment of its first industry AI hub in Singapore, where a small team will work together with Enterprise Singapore, and in partnership with AI Singapore, to jointly explore and develop new AI capabilities.

According to AI Singapore, AI Innovation Director Laurence Liew, by strategically deploying AI solutions to enhance decision-making processes, optimise resource allocation, and improve predictive maintenance capabilities, BHP is not just improving operational efficiency – they are fundamentally reshaping how mining operations can be made smarter, safer, and more sustainable.

As a major producer of iron ore, copper and metallurgical coal, and of potash, scheduled to commence in late 2026 at its Jansen project in Canada, and possibly of nickel again too, BHP’s business and outlook will always remain at the mercy of the global economy and fluctuations in the pricing of its products.

While it remains early days, AI is showing the potential for a safer and more efficient business, which should ultimately work to the benefit of shareholders via a relatively higher-valued share price, both in the good and the not so great times.

Insights and experiences to date are but the tip of the proverbial AI iceberg with corporate management teams across the globe today exploring what can possibly be achieved when AI is successfully implemented inside their organisation.

Goes without saying: while the promise looks attractive, success is not guaranteed, but the rewards can be tangible and significant, both for businesses and for investors.

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This section appears from now on every Thursday morning in a separate update on the website. See Rudi’s Views for the archive going back to 2006 (not a typo).

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(This story was written on Monday, 10th June 2025. It was published on the day in the form of an email to paying subscribers, and again on Wednesday as a story on the website).

(Do note that, in line with all my analyses, appearances and presentations, all of the above names and calculations are provided for educational purposes only. Investors should always consult with their licensed investment advisor first, before making any decisions. All views are mine and not by association FNArena’s see disclaimer on the website.

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