When we started planning our latest Melbourne Expert Talks event, we didn’t anticipate bulldozers becoming a central AI metaphor. But that’s the beauty of bringing experts together to talk about technology and leadership – you never know where the conversation might lead!

With a recent Gartner poll finding that 55% of organisations globally are already in pilot or production with Generative AI, we wanted to discover if Australia’s finance and superannuation sectors were investing in AI. At  “Beyond Gen AI: Navigating how businesses realise the benefits of AI”  our experts shared insights into how organisations are embracing the potential of AI and the foundational steps that organisations need to maximise their return on investment. As moderator of the panel, I’m delighted to share some of the discussions here. 

Combining Artificial Intelligence with Human Intelligence

Gen AI continues to dominate technology conversations, but more organisations are understanding that its efficacy hinges on human oversight.  Stephen Reilly Chief Operating Officer at HESTA illustrated this with the memorable bulldozer analogy: “No-one is surprised that a bulldozer can lift more dirt than a human with a shovel. But you still need a human to drive the bulldozer and decide where you want the dirt to go. It’s the same with AI. It’s no surprise that AI can do things faster than a human, but you still need a human in the process to get the best results.”

Claire Cornfield, Senior Executive Head of Customer Experience at La Trobe Financial, expanded on the importance of combining artificial intelligence with human intelligence, especially in organisations where trust is vital, such as financial services. ”We need to decide what we want the technology to do, what we want our staff to do and where each can add value. But we’ll still need humans to be involved in highly emotive or sensitive areas, even though these are also the more challenging jobs.”

Our panel also highlighted AI’s potential to improve customer experience and be used to create better outcomes for vulnerable people. For example, within healthcare, we are seeing the potential for AI to use data sets to predict health problems and enable early intervention. Andrea  Lymbouris, Head of Information Services at State Trustees, can see the potential in AI to provide improved personalised customer interactions within her teams. “AI could support our consultants access data about the client they are speaking to, when they last called and why, so the client doesn’t have to repeat all the information and we can give them the help they need quicker.”

Balancing AI’s risks and rewards

The finance and superannuation sectors, bound by regulatory constraints and financial responsibilities, can often be seen as cautious in their approach to new technologies. But even within this sector, each business will have a different appetite for risk, said Michael Collins, former Chief Information Security Officer at Judo Bank.  “Other businesses are going to run harder and run faster with AI –  they won’t have the sensitive data we do so they’re going to be able to take more risks. But within each organisation, it comes down to what your board and your senior management are comfortable with from a risk perspective.”

Stephen noted numerous potential AI applications in the competitive superannuation sector, such as personalised experiences and detecting anomalies in customer behaviour.  “But, as with everything with technology,  we have been very conscious with what we enable, “ he said. “We want to ensure it adds value, optimise our use and ensure we keep it secure.”

Claire also raised concerns about AI’s impact on talent development if it is used to automate some tasks. “A lot of AI-use cases are automating tasks that usually fall to entry-level roles, “ she said. “But these tasks, like dealing with calls in a customer centre, give people the breadth of experience that they can take into their long-term financial services careers.  If we take that work away, how are they going to get that experience?”

No doubt inspired by the Crowdstrike incident in the week before the event,  the panel also stressed the importance of human intervention in AI systems. Michael said: “Good AI needs three things – confidentiality, integrity and security.  But if an AI system went down, you would still rely on humans to be involved to fix it or maintain the service.” 

For Andrea, the biggest challenge is creating a strategy for the business when AI is advancing so rapidly and how businesses decide when to leverage AI capabilities built into the tools they already procure and when to decide to take a wider approach. Andrea added: “I think from a technology perspective we need to rapidly increase our skill set and expand our knowledge of AI.” 

Alongside AI strategies, getting funding for AI projects can also be a challenge, with limited investment models currently available to organisations to use within business cases. Michael said: “You’ve got to be very clear about why you’re asking for money and what you want to do because the business is always making trade-offs. But it’ll again come back to risk appetite and where you can pivot funding from in your current strategy.”

The importance of data quality and security

I’ve worked in digital transformation for a long time and I’ve seen the same questions about risk come up with each new technology – I remember people being horrified when we first introduced APIs in banking for example. But the difference I see with AI is that it is a technology that can be democratised and anyone can access tools like ChatGPT.  During the panel, I asked if it means that tasks we often put on the back burner, such as data cleansing or resolving our internal data permissions, now become consequential. The question of data quality is certainly one we hear from businesses looking to start working with AI, particularly for organisations looking after sensitive information for their customers or clients. 

Andrea said: “I think organisations are right to be thinking about protecting and securing the data. We need to be very mindful of it and put in place some additional risks and controls.” Michael also echoed the data security sentiment, adding: “You need to understand your data, where it is and how you’re going to use it before you start just running to the sexiest thing that’s on the internet and trying to install it and see how it goes.”

But Stephen also cautioned organisations waiting too long for their data to be perfect before embarking on an AI project. “Your data is never going to be perfect, so you have to figure out how to build in the margin for error for imperfect data. You have to drive forward. My encouragement is to test the quality of your data, overlay human intelligence onto your AI and embrace data governance people.”

Conclusion

We’d like to thank everyone who attended the event and our panel members for sharing their expert insights. 

We’re also delighted to announce that will be matching the total amount raised from the event, boosting the final figure to $1,500 donated to the  Aboriginal Investment Group’s Remote Laundry Project. This will power a laundry site for an entire year, giving remote aboriginal communities access to free laundry services to improve health and social outcomes. 

Watch out for details of our next Expert Talks event and If you’re interested in exploring Gen AI in your organisation, contact the Equal Experts Australia team.