Consulting giant McKinsey & Company in bid to convince wary Australian miners on AI

Consulting juggernaut McKinsey & Company has preached to Australian miners they need to be digging “dirt and data” to lift productivity and should learn to love artificial intelligence.

A partner at the firm’s Australian operations, Milan Korbel, says there is some scepticism among mining companies about how AI will benefit them.

“The main reason is because it’s difficult,” said Mr Korbel, who also works in its AI division QuantumBlack. “They’ve tried different ways, different partners, different vendors.”

But he argued that the resistance was not always justified, and that there are cost and time-savers available by trusting AI to run processing operations. Computers can also be trusted to help run mobile fleets and mines more efficiently, he says.

Mr Korbel described AI as “like a big brother across the refinery and helping operators and engineers”.

Australia’s labour productivity growth been slowing since 2014, and McKinsey is betting that artificial intelligence — especially for the mining industry — will be key to lifting it again.

Richard Sellschop, who is a partner with the firm in the US and leads its global mining services division, said productivity gains were one of the biggest imperatives for the mining sector in order for it to keep growing.

“I think that this is probably the most difficult industry in the world to raise productivity, because it’s not like building a widget or a car inside the factory where you’ve got a controlled environment. Here . . . you’re exposed to the elements, grade issues, mines only get deeper.”

“We’ve sometimes used the term that miners of the near future will need to dig dirt and data.”

He said being able to digest and use the data is critical.

“You don’t want Google Maps to be telling you how it’s figuring out what the optimal route from A to B is and why it’s just rerouted you. But it’s really quite useful when it does tell you ‘we recommend you save 10 minutes in your journey by taking a left here instead of carrying out straight’,”

“So getting to that point requires a lot of work, but we believe that the value will become clearer and clearer.”