Article
How AI is setting up the next revolution in mineral exploration and investment
September 8, 2025
Recent years have seen a dramatic increase in the amount of data available to support mineral exploration. This is great news for predicting profitable deposits, but the sheer quantity of data is swiftly overwhelming the capacity of geoscientists to analyse, or investment teams to understand (at least in a useful timeframe). However, well trained and dedicated AI can sift through that information in a fraction of the time humans can. For mineral project developers and investors this is a crucial development. It means they can have the answers to where they should or shouldn’t place their effort or money in days, perhaps hours, rather than weeks or even months. But only if you get the right AI in the first place, and you keep geoscientists in the loop…
The public’s perception of mineral exploration is that it’s a mundane and relatively easy pastime. You go somewhere, find a deposit, mine it, and head back home.
As we all know, nothing could be further from the truth. Locating a worthwhile and feasible deposit is a long, complicated job that requires a huge sequence of actions and investment decisions. Success is never guaranteed, and rarely achieved.
But equally the public has a strange view of AI too; that it will somehow ‘do all the work’, which of course it can’t. If you used AI on a farm, you wouldn’t expect it to fix the irrigation or complete a full veterinary exam. Similarly in mining you wouldn’t expect it to dig and drill holes.
What AI can do is bring a level of perception and understanding to complex mining data that eclipses any form of data analysis we’ve witnessed in the past. But it has to be a guided process, with geoscientists closely involved, in order to reach its full potential. Without that, AI will misfire.
Nonetheless, AI’s ability to understand and summarise data, and see through that complexity to the truth below is on the brink of revolutionising not just mining, but also the way investors decide the best potential deposits to invest in, with the least risk, and the greatest reward.
Luck and data don’t mix
Early on at MinersAI, it became clear to us that one of the most painful problems for mineral exploration and investment is the sheer mass of data that needs to be analysed, cleaned and structured. Most of it is super hard to find, super hard to structure and often super hard to use. (People say luck plays a big part in stumbling on the ideal deposit. Unfortunately, luck doesn’t scale…)
Companies can spend a year per project just digitizing their data, and getting it into some kind of shape before they even begin to extract any insights from it. Geologists may be spending 70, 80, even 90% of their working day just crunching numbers and structuring data, as opposed to doing the value-add work of analysing that information and ensuring it contributes to building a better and more profitable business.
When you step back and look at this problem, you realise it’s not just affecting the exploration companies who want to decide where to dig. It’s shared across all the actors in mining, from big mining groups doing feasibility, M&A, and prospectivity studies, to financial institutions carrying out due diligence.
Everyone wants access to data that can help them make decisions faster and more confidently. Everyone wants to shrink it, confine it, and summarise it in a way that generates lightbulb moments, not migraine headaches. It’s a universal need and a universal problem.
Why mineral exploration needs a technological helping hand to meet exceptional demand
Discovering a mineral deposit currently takes, on average, five years or more of work and $25m+ of investment. Yet only around 5% of those exploration possibilities stay the course to become successful enterprises.
In the next 15 years the world will have to vastly increase the amount of quality minerals it mines, not just to hit the net-zero targets of 2040, but, crucially, to achieve the robust energy supply security we all need. While elements such as Cobalt, Lithium and Rare Earths often receive the most publicity, materials such as copper and iron ore are just as critical. (This year’s Global Critical Minerals Outlook by the International Energy Agency was particularly concerned about a predicted 30% shortfall in copper and a decline in ore grades.)
Importantly, easily accessible, near-surface finds are a thing of the past and we need to pursue deeper deposits. To stand any chance of locating them successfully, consistently, reliably and profitably we need a far better way of studying the data that comes from exploration, and extracting the key facts that make fast, confident decisions about drilling and investment possible. That 5% hit rate must improve, so how can AI help that happen?
Perhaps more importantly, how can AI achieve this in the real world, with real pressures, and do it reliably in an industry that may already be growing suspicious of the AI hype?
To discover the solution, check out our next blog ‘When is AI right for you?’ here.