AI, client expectations and talent shortages – the pressure is on for financial services firms in Australia. But what if these challenges are actually opportunities in disguise?
There's no doubt the past few years have tested the resilience of financial services firms across Australia. Persistent inflation, interest rate volatility, evolving regulations and an ongoing war for talent have forced leaders to adapt at pace. At the same time, AI is revolutionising the industry with the promise of unprecedented growth.
A recent study by KPMG, 'Trust in AI Global Insights 2025', reveals that while 50% of surveyed organisations in Australia regularly use AI, only 36% are willing to trust it, and a massive 78% are concerned about negative outcomes from AI. This positions Australia among the lowest globally in terms of AI acceptance, excitement and optimism.
This AI paradox — high usage coupled with low trust — presents a critical challenge for organisations looking to scale their AI initiatives. In a recent discussion with KPMG, I learned more about what this means for financial services firms in Australia, and how you can use these insights to drive sustainable success. Here are a few key takeaways from the session.
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While 72% of organisations surveyed said they have reduced time spent on mundane or repetitive tasks, organisations have largely confined AI adoption to pilots and proof-of-concepts. This risk-averse approach has some benefits, but most often leads to bottlenecks that limit the value realised from AI adoption.
In our discussion, KPMG highlighted that organisations which are successful at scaling their AI programs differentiate themselves in two ways. First, they clearly identify the use cases they want to impact. Second, they proactively move beyond experimentation as soon as they can. As a result, they are seeing genuine breakthroughs.
Local institutions are not only calling for AI regulation but expect strong oversight from government, regulators, and industry.
To leverage these insights, I encourage you to identify genuine problems that can be solved by AI, rather than deploying the technology for its own sake. Leveraging pilots and proof-of-concepts as validation tools, rather than excuses for caution, can significantly accelerate the return on your AI investment.
Australia's heavily regulated financial services sector is proving a significant hurdle to AI investment confidence, according to KPMG's global tech report. Local institutions are not only calling for AI regulation but expect strong oversight from government, regulators, and industry, with a striking 90% advocating for laws to combat AI-generated misinformation.
The emergence of new global frameworks for responsible AI, such as ISO 42001 – the first international standard for AI management systems – as well as the Voluntary AI Safety Standard in Australia and international standards like the EU AI Act, offer a promising path forward. These frameworks are crucial for building trust among employees, customers, partners and industry regulators.
Rather than adopting a cautious 'wait and see' stance, KPMG encourages financial services firms to proactively align with existing standards and principles as AI programs are developed. This allows firms to navigate the balance between innovation and control, positioning them for long-term success as regulations evolve over time.
A glaring statistic from the KPMG study on trust highlights a significant gap in AI education and literacy in Australia compared to overseas.
An AI-literate workforce is better equipped to critically assess AI tools, comprehend their limitations, and adhere to safe operational practices.
Only 24% of Australians have undertaken AI-related training or education, compared to 39% globally. In addition, over 60% of Australians report low knowledge of AI (compared to 48% globally), and under half (48%) believe they have the skills to use AI tools effectively (60% globally).
This deficit in AI literacy is a critical barrier to widespread adoption and responsible use. An AI-literate workforce is better equipped to critically assess AI tools, comprehend their limitations, and adhere to safe operational practices, ultimately fostering greater organisational trust and usage.
To bridge this gap, firms must educate employees on AI's capabilities and constraints, encourage critical thinking on the appropriate use of AI in the organisation, and provide clear guidelines for experimenting with approved AI tools. This will cultivate a learning mindset, empowering employees to become informed and responsible users of this transformative technology.
So how are financial services firms leveraging AI in Australia? During the Workday Elevate Online session, we discussed a number of use cases in Australia and globally, where AI is delivering real value.
In customer service and support, AI is enhancing the ability to serve clients and identify those at risk of hardship, offering much-needed extra support. Within financial crime and fraud prevention, AI is providing robust support for customers targeted by fraud and scams, while also analysing vast transaction data to detect patterns of fraudulent activity.
Another compelling use case is the application in regulatory compliance. A significant number of financial services firms are focusing on AI use cases that strengthen their risk, compliance, and governance functions. The goal is to gain a clearer understanding of compliance obligations and ensure adequate controls and coverage.
There are also examples where banks are using AI to streamline the contract generation, review and management process for custodial agreements — all within the scope of their internal rules, guidelines and processes. This not only helps them avoid creating new contracts and navigating complex approvals each time, but can also help them identify and manage risk exposure.
Forecasting is a popular use case for AI, because it's fairly low risk and allows teams to get comfortable with AI before leaning into larger transformation projects. And the benefits are tangible: many firms are using financial forecasting models to predict demand and support scenario planning, enabling more strategic decision making.
To avoid falling behind the rest of the world, it's vital that firms consider the impact of low trust on the adoption and success of their AI programs.
In the year ahead, there will be a significant focus on using agentic AI to achieve outcomes more autonomously. This will still require human oversight at key points, but with less emphasis on team members having to constantly prompt and direct AI tasks. Ultimately, it's a future where AI isn't just a cost centre, but a way to drive productivity while lifting compliance standards.
It's encouraging to see financial services firms use AI to gain a competitive edge, driving operational efficiency and empowering teams to shift their focus from repetitive tasks to higher-value, strategic work. But to avoid falling behind the rest of the world, it's vital that firms consider the impact of low trust on the adoption and success of their AI programs.
This hinges on the three imperatives discussed. First, firms must build momentum by moving beyond cautious experimentation, actively seeking to scale AI initiatives that demonstrate tangible value. Second, a proactive approach to AI regulation is essential; rather than a 'wait and see' stance, firms should align with emerging standards, fostering strong governance and accountability. Finally, and perhaps most crucially, firms must close the AI literacy gap within their workforce.
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