Executive Summary
Our survey shows who in the industry is
implementing new technologies and what
they have achieved so far
Beth McLoughlin
Our survey received responses from 223 mining
professionals. Of the 129 who answered the question ‘To
date, has your company (or a company you have invested
in) deployed or developed automation technology?’,
nearly two-thirds (60.6%) said their organisation had.
When it comes to those who have used artificial
intelligence (AI) to drive efficiencies in the mining
company they work for or have invested in, just under
two thirds have not deployed this technology yet.
To date, has your company (or a company you have invested in) deployed or developed automation technology?
To date, has your company (or a company you have invested in) deployed or developed AI technology to drive
Digitalisation and automation are clearly being
widely used by miners who want to optimise
operations, but different technologies are advancing
at different speeds.
When we started putting these reports together,
we treated automation and digitalisation separately.
This year, we have decided to bring them together,
for several reasons.
Digitalisation projects very often revolve around
automation, with mining companies increasingly
choosing to automate some of the more dangerous
parts of their operations and move operators away
from heavy machinery, ultimately into remote
operating centres (ROCs) where possible.
There is no way to achieve that without moving
away from manual processes and using sensor and
other data to plan operations – ie, without a full
digitalisation program.
ROCs such as Rio Tinto’s operations centre in Perth,
from where 50 autonomous trucks are operated in
Pilbara nearly 1000 miles away, are only made
possible using the latest technology. For example,
the BHP ROC in Santiago can handle 5.4 terabytes of information every day.
Who we asked
First, a word on the methodology we used to put this
report together. We received 223 responses to our
What kind of company do you work for?
Where is your company HQ?
survey, with 42.2% of these coming from mining
equipment, technology or services (METS) companies.
Mining companies (producing) made up 17.5% of
respondents, while mineral exploration companies
that are not currently producing were 8.1% of the
whole. Investment companies accounted for 4.5%
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Of all respondents, 44% were in senior or middle
management, with 22.9% at the board level or on
the executive committee of the company they work
for, meaning that a significant number can be
described as decision makers.
More than one in 10 (12.1%) of respondents were from companies with market capitalisation of more than US$5 billion, with 10.8% in the $1 billion to $5 billion category, and 29.6% from companies with
market caps of less than $250 million. Almost a
third (29%) were from private companies or chose
not to disclose their company market cap.
Respondents were from across the globe, with 26.5%
in australia, 16.6% from the US, 23.3% from Europe and about a quarter from other parts of the world.
and about a quarter from other parts of the world.
Picking priorities
Even though roughly a third of our respondents had
not yet deployed automation in their operations,
it came out top of the list of priorities when
professionals were asked what would be most
important to miners by 2030.
Next on the list was real-time monitoring and data
collection, which is not a surprise as this is essential
to any kind of automation program. In tough price
environments for many metals and minerals,
collecting data in real time can help drive
efficiencies. Despite becoming a buzzword since the rise of generative AI in many industries,
optimising and improving efficiency through AI was only third on the list
In 2030, which technologies will be mining's top priorities?
AI has been cited as driving improvements in
operations such as ore sorting, with an expert
recently telling Mining Magazine that AI-integrated
solutions can increase mineral yield by 15-20%,
reduce transportation costs by 25-30% and drive
sustainability.
A separate study by researchers at Charles Darwin
University in Australia found that AI algorithms
could predict gas-related incidents in coal mines
30 minutes before they occur. The ability of machine
learning to process information much more quickly
than before means that new use cases are always
being discovered.
It is possible that the true impact of AI on mining is
not yet known. For instance, work by SRK Consulting
found that it could have a huge impact on safety,
simulating 20 years of blasting sequences in just a
few days so that the risks associated with explosives
in surface mining can be radically reduced.
Fourth on the list was sustainable processing.
A survey by Mining Magazine Intelligence conducted
earlier in the year found that processing was the
number one mining operation companies thought
could be transformed by AI.
New technologies, such as direct lithium extraction
(DLE), are already making waves in the industry.
Not only can they reduce the energy required to
process source material, but they often save money
and time
Machine learning can make small adjustments
in processing, identifying any material that will
cause problems further down the line, and altering
parameters such as heat and quantity of reagent
in real time
The next two on the list were load/haul/ore transport
technology and power generation technology, which
scored almost the same number of responses, with
transport slightly higher.
Fully automated trucks, such as the electric T 264
unveiled by Liebherr and Fortescue at the most
recent MINExpo grab headlines and are increasingly
becoming established in mines across the world.
Australia leads the way here, but even in regions
where full automation is not the norm, mine sites are
using aspects of it, such as collision avoidance
systems, to improve safety and optimise operations.
The reason power generation technology comes in so
close to transport is likely that they are very closely
linked. Replacing drills, load haul dump (LHD)
machines and other heavy equipment is also an
opportunity to electrify operations, and that comes
with power challenges.
Another buzzword in recent years, digital twins,
came in as the lowest on the list of technologies our
respondents thought would be top priorities in
mining by 2030, though still significant.
Digital twins can help mining companies with
predictive maintenance and efficiency, and are used
to test out scenarios in the virtual world before they
can have an impact on the real one. However, many
companies have some form of a digital version of
reality already, though they might not consider this
to be a digital twin.
Digital twins are sometimes described as hype,
but they can have an important role to play in asset
management in mining and in avoiding expensive
shutdowns or downtime.
Remaining challenges
The paradox of implementing automation and
digitalisation programs is that their success depends
How big a barrier are the following factors in the uptake of emerging and innovative technologies in mining?
on the humans that deploy and operate them. We
asked our respondents what the biggest barriers were
to the uptake of emerging and innovative technologies
in mining, and the answers were revealing.
Company culture and internal resistance to change
were viewed as a “large barrier” for almost a third of
those we surveyed, and a “moderate barrier” for just
under a third.
About half said lack of evidence of effectiveness
held them back and was considered a moderate
barrier, while this was a large barrier for 23.2% of
those in the survey.
Perhaps unsurprisingly, upfront costs were also a
concern, with almost half citing this as a large
barrier and a little under a third saying it was a
moderate barrier. That picture might look different
for junior miners without the deep pockets of the
majors, but combined with the lack of evidence for
effectiveness, the results suggest that miners are
unwilling to commit large sums of money for
something they cannot be sure will get results.
Technical concerns and drawbacks were viewed by
almost half of respondents as a moderate barrier to
the uptake of emerging technologies.
Other significant barriers included the long lead
times and supply chain constraints, which can mean
it takes time to implement new tech. This was cited
as a moderate barrier to uptake by 40.6% of those
who answered our question on obstacles. Meanwhile,
a shortage of the required skills was seen as a
moderate barrier to uptake for almost half.
Success stories
As we have seen, about two-thirds of survey
respondents have deployed or invested in automation
for a mining company while only about a third have
done so with AI. From 120 responses, covering those
that had implemented automation technology, no one
said it had been unsuccessful. Only eight found it had
been “not very successful” with a majority reporting
moderate success and 46 responding that automation
had been “very successful” for their organisation.
When it comes to AI, there have also been
successes, but our responses suggest this is more of
a mixed bag. While a large number of companies of
different kinds reported that the deployment of AI
had been moderately successful, quite a few of our
How successful has automation technology been overall for your company (or the mining industry)?
70 respondents to this question, those that had
implemented AI, were less enthusiastic.
Of those respondents from mining equipment,
technology or services (METS) companies, 29% said
AI had not been very successful for them. A quarter
of mineral exploration and development companies
said the same, while 24% of producing mining
companies also reported that implementing AI had
not been very successful.
The picture was even bleaker for investment
companies, with 67% saying it had not been very
successful.
How successful has AI been overall for your company (or the mining industry)?
To fully understand why, it might be necessary to
determine exactly what kind of AI these companies
used. Machine learning for ore sorting could bring
different results to using generative AI to summarise
investment meetings, for example.
Looking ahead
2030 was the date we asked survey respondents to
look forward to, partly because so many mining
companies have ambitious sustainability targets
to reach by that time.
Without monitoring current performance
through data or deploying technologies that can
drive efficiencies, meeting these goals looks
tougher to do.
Most thought spending on AI will increase, with the
majority of those in our survey backing an uptick of
50-100% in six years’ time. A little under a third had
more modest expectations of a 10-30% increase by
2030, while a significant number thought that
spending on AI in the mining industry will go up by
more than 100%.
We also asked where the positive impact of emerging
and innovative technologies will be felt in the mining
industry.
Our respondents predicted that these technologies
will have a large impact on production, and a
moderate impact on profitability. Operating costs
were also singled out by a high number of survey
respondents as an area that will be moderately
impacted by innovations.
By 2030, how big a positive impact will emerging and innovative technologies have on:
Sustainability targets and tackling carbon emissions
were also seen as factors that could be positively
affected by new technologies.
While the companies in our survey – and in the
industry more widely – might be at different stages
in their journey, our findings suggest that there is
only one direction of travel when it comes to
digitalisation and automation.
Navigating the technology landscape may not be
easy, but our respondents are clear that there are
significant gains to be had for those that do.
How do you expect spending on AI in the mining industry to change by 2030?
