At a glance
- Leaders from transport and logistics share real-world AI applications.
- Insights into smarter maintenance, rostering, and workforce optimisation.
- Challenges highlighted: governance, cultural transformation, and talent.
- COSOL and IBM partnership helps drive AI maturity in asset-centric industries.
Transport industry perspectives on building AI maturity with practical business cases.
COSOL, in partnership with IBM, recently brought together leaders from across asset-centric industries like transport to discuss the emergence of AI across the industry. The conversations painted a picture of the state of AI in these Australian businesses.
Experts discussed the ‘Walk, Jog, Run Framework’, where organisations are encouraged to gradually build their AI capabilities sensibly and safely. This framework sees AI first needing to become trustworthy and repeatable, then later able to deliver real value, before late-stage scaling up into production across the business.
AI's Potential Across Transport and Logistics
Having kept a close eye on how AI is being adopted across asset-centric industries in Australia and Asia Pacific, COSOL’s AI Lead, Anthony Cipolla, said there were many exciting case studies emerging across transport and logistics.
“Some of our customers in transport and logistics are doing some really interesting things at the moment,” he said. "We know technology leaders that are leaning into robotics, automation and AI to manage how equipment, resources and people move around on their sites. They're also looking to use AI to improve workflows and rosters for staff, there's training and career development use cases, and tools to optimise space for greater utility; there's a lot of potential."
For Rolf Samonte, Head of ICT & Cyber Security for Metro Trains Sydney, enabling the AI opportunity for line maintenance has been a focus. The company, which operates and maintains the Sydney Metro M1 Northwest & Bankstown Line, has already taken steps to plan for success.
“I think one of the key enablers for success with AI for us is that we have established the AI steering committee, headed by our CEO. The leadership buy-in is really driving the initiatives to come forward,” he said.
“Where AI could fit for us is around smarter maintenance, whether it's using IoT and bringing that data into our ERP system and then getting the trends out of that so that we can work safer, smarter and more efficiently.”
Fiona Love, General Manager for Workforce Development at the Australasian Railway Association, was bullish about the impact AI would have on asset management. Love sees optimisation potential in rostering and other areas to drive efficiencies on site and, in particular, improve conditions and bolster the workforce.
AI Challenges, Data Governance and Business Transformation
Adopting AI presents many opportunities but also challenges, and demands of companies to interrogate their business across a number of areas. Several of those discussed during COSOL and IBM’s recent event included cultural transformation, security, talent shortages, lack of data expertise and more.
The scale of the change that AI presents to all industries is perhaps comparable to the disruption brought by the internet, mobile technology and cloud computing (though likely more exponential in nature). At the same time, the concept of the Agentic-Web is being developed to determine how AI systems are standardised and communicate with each other.
AI Governance has also become a priority for organisations, though the good news is that it builds on the existing Data Governance work many companies have already undertaken.
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.”
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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.
