Delivering the opening keynote address at the new conference, attended by more than 400 delegates, McIntosh said Rio Tinto and its peers were heading into a very different future for the industry than the one envisaged a decade ago.

"If you'd asked me 10 years ago if I ever thought we'd be hosting a Hackathon, I'd have just said, ‘what on earth is that?'. And perhaps, ‘we're here to do exploration and mining, not play games'.

"And I would have been wrong."

A 2017 hackathon in Sydney set up by the mining giant's Pioneer Lab to address the problem of material ‘carryback' in mine haul trucks - which can cost 5% of fleet haulage capacity at some Rio Tinto sites - produced a range of ideas but it was the type of thinking the exercise generated that struck McIntosh.

"We gathered 22 frighteningly clever, and mostly young, people from universities and from tech start-up firms [and] held them hostage over a weekend, feeding them coffee, burritos, pizza and data, [which] appear to be their chief dietary requirements," he said.

"We divided them into five groups and threw [the carryback] problem at them.

"The first thing to note is that every group came up with an entirely different approach - they asked different questions and used different thought processes. Secondly, they all used algorithms and machine learning software to learn and improve functionality. So the same basic tool kit, but five completely different takes on the problem.

"There is so much we can learn from this simple exercise. Will we do it again? Absolutely.

"Some of the solutions increased the accuracy of predicting carryback from 70% to well above 90."

McIntosh says a proliferation of hackathon-type meetings globally between traditional mining professionals such as geologists, engineers and metallurgists, and non-mining technologists and entrepreneurs, is also presenting the industry differently to prospective employees and leaders.

McIntosh talked through several examples of the current impact of data analytics, cloud computing services and "cost-effective hyper-scale computing power", automation and modern communications on Rio Tinto's current assets and operations, declaring these and other technologies would continue to positively influence productivity, profitability and safety. He indicated technology and innovation were integral to the company's Mine to Market Productivity drive aimed at generating an additional A$5 billion of free cash flow from company assets by the end of 2021.

But they were also already reshaping the industry's future.

"Our Koodaideri project is an iron ore development being studied within our Pilbara business. It is planned to be our most advanced mine yet built," he said.

"Through the use of digital design, advanced data analytics, machine learning, control loop optimisation and automation we will significantly improve how we operate and maintain this new mine.

"Through the use of digital twins, we will better interact and use the data we gather during design and operations. The digital twin will allow us to access real-time data in the field to support our operators and maintainers.

"This will be our first fully paperless mine.

"Ultimately, Koodaideri will run as part of an integrated system, where we can integrate - in real time - the mine, process plant and rail system, including AutoHaul [Rio's new autonomous rail system].

"It will employ some absolutely leading edge technologies and do so in completely novel.

"Again, this is not a case of technology for technology's sake - this intelligent mine will improve safety, optimise performance, and so attract the workforce of the future."

McIntosh said digitisation of Rio Tinto's mining business was now a core focus at different levels of the organisation and leadership.

"Data is the new oil," he said.

"As an industry we have achieved incredible things through scaling and ever refining known technologies.

"The Tech 4.0 digital disruption is now starting to manifest in a significant way upon our industry.

"From cloud computing, to new sensors, to drones, to ever more automation and now the rise of machine learning and AI.

"This is all being fused through data science to generate new insights."