The financial services industry stands to reap billions of dollars in productivity, efficiency and quality gains from the rollout of Generative Artificial Intelligence (GAI) technologies, a new report by industry peak body the Tech Council of Australia and Microsoft reveals.

The report, Australia’s Generative AI Opportunity, argues that the professional services and financial services sectors could realise between $5 billion and $13 billion in growth with the introduction of responsible GAI technologies – among the biggest winners of the four industries assessed.

Across the entire Australian economy, adoption of GAI could, with “slow adoption”, contribute between $45 billion and, with “fast-paced adoption”, upwards of $115 billion by 2030, the report revealed. This would be achieved either by enhancements and efficiencies made within existing industries or through the creation of new products and services.

On average, around one-fifth (22 per cent) of an individual’s task hours were recognised to have a high potential for GAI-backed automation. These tasks, “characterised by their routine nature and well-defined parameters” might include the synthesis of documents and large text-based sources, data reconciliation, or transcription.

An additional 22 per cent of tasks could be augmented through GAI, including product quality control, checks on data accuracy, explanations of policies and procedures, preparation of technical documents, or staff training.

GAI is defined as a subset of artificial intelligence, utilising machine learning techniques to generate human-like and “potentially unseen or unimagined” content.

The professional and financial services industries were among four key sectors of the Australian economy – alongside healthcare, manufacturing and retail sectors – assessed in the report. Each was selected due to their being among the most likely to benefit from the progressive development of GAI technologies.

Professional services, including FSIs, could, the report said, “leverage GAI to automate routine tasks, freeing up a highly educated workforce to focus on higher-value activities”.

In the risk space, for instance, a GAI bot could scan financial data and generate alerts of anomalies in risk metrics (capturing data on delinquencies, liquidity and markets), summarise and share root causes, and run simulations to finalise an action plan.

More generally, the technology can be used to automate the analyses of unstructured datasets and synthesise information from multiple sources, including video KYC, underwriting algorithms, and application forms, to form a clearer more holistic view of customers.

The report also warns of the need to manage a number of key risks in order to fully realise the economic opportunity from Gen AI: the capacity to transition workers to other tasks and roles, as GAI could make many positions redundant; to ensure equitable access to GAI technologies for businesses and individuals; and the ability to manage AI responsibly, with the report flagging concerns around potential data biases and unethical outputs, as well as loss of privacy.

“Industry and government need to establish regulations that promote transparency, accountability, and responsible practices,” the report said. “This includes guidelines for transparency and accountability in decision-making, to ensure GAI systems are inclusive and do not obscure the context-specific needs of priority cohorts.

“Furthermore, ensuring data security is particularly critical if GAI is to drive benefits in highly sensitive industries like healthcare or law.”

NAB’s Howard Silby, executive, innovation and partnerships, noted that despite being “around for a while”, GAI technologies have today reached an “inflexion point”.

“Whilst we’ve been using AI tools for some time in areas including digital customer service, cybersecurity and financial crime, the opportunities for Gen AI to move our organisation – and our industry – forward are significant.”

“As a bank, it’s critical that we use AI for the benefit of our customers, and protecting their data has to be our first priority. That’s a key foundation for all the development around Gen AI that we put in place.”