Tech-savvy mining chief financial officers embrace artificial intelligence to understand ‘truckloads’ of data – enabling them to lower costs and lock away deals ahead of competitors.
‘Mining companies literally have “truckloads” of data, and those that embrace artificial intelligence (AI) to organise and strategically review that information are more likely to prosper in future,’ says Jeff Robson, Managing Director of Access Analytic in Perth. As a consultant specialising in AI, data analytics, and upskilling chief financial officers (CFOs), he works with many of Australia’s – and the world’s – largest miners and energy multinationals.
‘Today’s CFO is expected to be a strategic adviser, a technology champion and a commercial leader, all while maintaining control, measuring performance, and providing financial discipline,’ says Robson. ‘The role of finance is not just to report on the past; it is to help shape the future. This depends on a new ability to embrace data, technology and change.
‘Compared to other industries, data in mining tends to be extensive and well organised because so many industry leaders are engineers. But the uptake of AI tools to produce insights and improve efficiencies varies widely from company to company. Some of the larger and most successful miners are slow to adopt new technology.’
Robson says that while miners are not necessarily competing for markets, they are all aiming to reduce costs. The more information available to improve operations and decision-making, the better. Falling costs lead to rising profits and shareholder returns.
‘Not all mining companies make a lot of money,’ says Robson. ‘Some have tight margins, so every opportunity to reduce costs matters.
‘Many mining companies are directly competing to develop a limited number of viable mineral projects, secure investors to unlock capital and hire capable staff from a relatively small pool of talent. Fast, innovative miners can optimise mining operations and access groundbreaking new prospects faster than ever before. If they are using AI well, some mine developers could be at the finish line while others, using old systems, may not have even made it onto the field.
‘Timely and well-communicated investor relations’ news and information are also critical in the resources sector,’ he says. ‘AI can play a big role in helping companies be more transparent with current or potential investors and in uncovering opportunities. It’s clear that AI is already directly impacting deal-making in metals trading, project analysis and project acquisition.
‘In terms of human resources, if a company gives its people access to a positive, technology-focused environment where people feel they can continuously learn, then that is going to be a more attractive place to work,’ he says.
Access Analytic recently released its 2025 CFO AI & Technology Insights Survey.
The report contains data collated from more than 60 companies, some of which had revenues of more than $1 billion. The majority of those surveyed were mining companies from Western Australia, and it revealed that the use of AI in the finance divisions of the mining and energy sectors has been significantly lower than in large Western Australian businesses overall. In the report, 28 per cent of all respondents said they have no plans to implement AI, while 67 per cent of mining companies in Western Australia said they have no plans in this area. The research also uncovered numerous other important insights into how the financial leaders of some of Australia’s largest companies are utilising AI and technology. Information for the report was collated in July and August 2025.
Robson says that with the assistance of AI, mining innovators can evaluate the profitability of potential mining projects globally.
Financial models can include shifts in commodity prices or geopolitical changes. ‘For example, imagine if your company holds lithium mining projects around the world,’ Robson explains. ‘They could be in Asia, Africa, South America and Australia. You already have the data prepared in an in-house large language model (LLM). The price is included, but other variables – such as diesel rates, development capital costs, royalty rates and more – are embedded, as well. There is an announcement about an invention using lithium, and the lithium price rises 20 per cent in a day.
‘With AI assisting your financial modelling, you know immediately that two of the lithium mines under consideration for acquisition are now potentially viable. But there are other complexities. In this hypothetical scenario, lithium has also just been placed on a critical minerals list, and several jurisdictions where you want to mine lithium have banned the sale of lithium to various target market countries. Going a step further, one of the countries has an election coming up, and two main political parties have different policies on lithium mining and exports. Using AI, in seconds, mining company leaders can evaluate which incoming government could likely influence the mine’s profitability.
‘AI-enabled data applied to real situations around the world right now is radically disrupting operational models and money flow in the mining sector,’ Robson says.
The research report found that leaders who aren’t using AI are mainly concerned with privacy and a lack of skilled personnel to implement changes.
‘These concerns are unfounded as there are very simple solutions to address both of these issues,’ says Robson. ‘They can use in-house LLMs or off-the-shelf solutions, and train staff or hire consultants. With AI support handling the heavy lifting, CFOs spend less time on data collation and more time on strategic issues, and adding value to the AI analysis. This leads to better decisions.’
