The newly appointed mining sector lead at Australia’s Artificial Intelligence Cooperative Research Centre, MaxMine founder Tom Cawley, says miners and their suppliers have work to do to turn investments in AI into significant real-world improvements.
“Despite increasing investments in AI industries such as mining still struggle to move beyond pilot initiatives to achieve large-scale operational outcomes,” Cawley said after being named in the CRC mining role.
“Gartner estimates that 60% of AI projects fail due to a lack of AI-ready data, with 42% of organisations abandoning AI initiatives before they reach production.
“We’ve [MaxMine] demonstrated that Australia has the capability to develop advanced AI tools that work effectively at scale in mining.
“I hope my role at the AI Accelerator CRC will encourage further innovation across the sector and help to strengthen Australia’s competitive edge in the critical minerals market.”
The AI CRC describes itself as Australia’s primary AI model building capability, combining the work of leading universities, private industry and government. Australia’s AI Opportunity Report 2025 found AI could add up to $142 billion to GDP by 2030, including $29 billion from building a sovereign AI industry and export sector. The CRC is expected to cost up to $150 million to run over 10 years and is seeking up to $75 million of further funding for projects from industry partners.
Formed more than 10 years ago in Adelaide, MaxMine has built an international customer base for surface mine operations management software. Cawley says it has deployed a new production-grade machine learning system over the past six months with major mining and metals trading group Glencore and contractors NRW Holdings and Macmahon.
MaxMine claims the system has delivered “significant operational improvements, including reduced workload for site teams by minimising missed or incorrect loads [and] higher accuracy production tracking, particularly in complex and edge-case scenarios”.
“Developed using over 14 million hours of labelled operational data the ML system helps automate load and dump classification, reduce site team workloads and improve production data quality,” the company says.
MaxMine CEO Shaun Mitchell said implementation of the ML system reinforced what had been observed across the industry: “Organisations succeeding in AI are those that have the highest-quality datasets.
“As AI adoption accelerates across mining and other critical industrial sectors, having high-fidelity, ground-truthed data becomes essential for delivering accurate results, improving operational visibility and enabling faster, more informed decision-making,” he said.
Chief Scientist at the Australian Institute of Machine Learning and interim CEO at the AI CRC, professor Anton Van Den Hengel, said models such as MaxMine’s that could be deployed “with such accuracy across such a range of asset and site types” was rare.
