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.
Top Use Cases in Financial Services
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.
Customer Service
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.
Regulatory Compliance
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.
Contract Intelligence
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.
Financial Forecasting
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.