At a glance
- Mining and energy experts share AI use cases and challenges
- Key insights on prediction, forecasting, and smarter maintenance
- Regulatory, cultural, and workforce barriers highlighted
COSOL, in partnership with IBM, recently brought together leaders from across asset-centric industries to discuss the emergence of AI across the industry. Anthony Cipolla, AI Lead with COSOL revealed organisations across the Australian asset-centric industry landscape like mining exhibit mixed maturity when it comes to their AI journeys.
Cipolla said businesses were keeping the impact on the workforce front of mind when looking to adopt or increase investment in AI. AI is both a disruptor and an enabler, and no doubt there will be tensions and hurdles along the way as businesses reconcile this.
Cultural change, mindset and trust will be key factors that mining organisations in Australia either have faced, are facing or will face along their efforts to modernise with data, AI and automation, and these items were certainly reflected in the prevailing discussion.
AI undoubtedly presents opportunities in asset-management oriented organisations. Applications like computer vision to recognise changes in assets regularly, as well as data interpretation for potential optimisation with sophisticated LLMs, just to offer an example, are often cited as technologies offering great potential in this industry.
However, technology changes aren't small projects, particularly when they affect organisations responsible for high-value infrastructure and equipment where safety decisions matter most.
AI Challenges In The Mining Sector
COSOL's Anthony Cipolla said.
Another challenge acknowledged was resistance to change. While not exclusive to mining, this barrier to transformation can be particularly strong where big, high-value operators with long legacies are laser-focused on their core operations. Mining is, however, expected to experience more transformation as new generations of workers move into the sector
Alinta Energy’s Chris Pratt, General Manager for Energy Supply Technology, pointed out that prediction and forecasting were core pillars of an energy utility’s work to ensure grids functioned properly. This is a space where data is fundamental and AI’s potential is high.
“It all comes down to prediction. What is our demand going to be at five o'clock tomorrow, when everyone comes home? What's the weather forecast going to be at five o'clock. What's the price of the energy market going to be?,” he said.
“We use machine learning in the trading space to understand and determine demand. We can also harvest the data we have available to extract better information, which results in better outcomes for industry.
“There is also technology we are rolling out now where a customer will call up, and AI will be able to identify that customer and what they might be calling about for the call centre operator, providing faster answers to customers.”
Alinta Energy’s Chris Pratt also highlighted regulatory constraints as another challenge when trying to unlock insights through modern AI solutions.
“We have a lot of obligations to our clients, we go through a lot of audits and have a lot of security, there are a lot of regulations around what we can and can’t do. For example, we can't just go and buy an off the shelf AI solution. We have to put a lot of checks and balances and guardrails in place. That can have the effect of slowing a company down with respect to innovating.”
Closing Thoughts On Managing Change
Adopting AI presents many opportunities but also challenges, and demands of mining companies to interrogate their business across a number of areas. Business transformation takes time, communication and understanding across organisations and industries. For asset-centric industries looking to walk then jog then run with AI, this means effective change management must also be one of the most important areas of focus.
This business-first view was shared by Paul Lee, IBM ANZ Senior Technical Specialist for IBM Asset Lifecycle Management.
“In the case of AI, organisations need to always be thinking about what the business problem is that they are trying to solve, or the business benefit they are trying to gain. You can explore those business cases with your technology partners to tease out the right AI implementation.”
For organisations looking to develop their AI roadmap, COSOL brings deep experience as a trusted implementation partner across asset-centric industries, while IBM provides the proven platform foundation with Maximo's integrated AI capabilities.
Together, this partnership approach helps companies navigate their AI maturity journeys with both strategic guidance and reliable technology infrastructure.
Access the insights
To access even more insights on AI from key asset management leaders, click the link below for the whitepaper.
About COSOL
COSOL is built on one belief: in asset-centric industries, reliability is everything. We’re a trusted, data-led asset management partner for organisations around the world who can’t afford to fail. And known for our deep expertise, dependable delivery, and ability to keep critical assets performing at their best.
The company recently celebrated 25 years in business, are Australian owned and operated, and recognised as reliable partners by their clients across the globe.
