The Australian government sees the value of generative AI in local, state and federal governments. However, unusually long spending restrictions and concerns about automation disasters are slowing AI adoption, at least in terms of citizen-facing solutions.
According to a Gartner survey of APAC government CIOs (with Australia right in the middle of the trend), AI/machine learning and generative AI are the two biggest priorities to be implemented by 2026 (Figure A). And yet other pressures are making government agencies hesitant to adopt AI in areas the Australian government considers critically important.
For example, while Gartner research shows that 84% of CIOs consider investing in excelling in the citizen experience a top priority (Figure B), less than 25% of government organizations will have AI-based citizen-facing generative services by 2027.
The Australian Government's disconnect between the desire to implement AI and the ability to deliver
As Dean Lacheca, vice president and analyst at Gartner, said in an interview with TechRepublic, there is public skepticism around large public learning models, and concerns about privacy, security, and data preparation affect the speed of adoption. of AI. This is a particularly sensitive issue in Australia, where automation, including AI, within government services has caused material damage. Consequently, there is an inherent distrust of any application that is seen as automating interactions with citizens across government.
Most notably, although it was not an application of AI, the “Robodebt” scandal that affected Australians so significantly led to a Royal Commission following a change of government. The automation that was at the center of that controversy has made many government agencies hesitant to announce to the public that they are exploring the use of AI.
“That association with automation is not expressed openly, but the underlying sentiment is that government agencies are aware that there is a lot of risk to their reputation if they get it wrong,” Lacheca said. “There is some frustration at the executive level about why they can't move faster in the AI space, but there is validity in the conservative first-step approach and thinking fully through the use cases.”
Tight budgets also impact Australian government adoption of AI
This conservatism is further compounded by prolonged austerity in government IT spending, which Lacheca says is impacting the types of projects that are getting the green light. The need for investment is understood, she said, but leaders who greenlight projects are focused entirely on productivity, efficiency and a quick return on investment.
Given that AI is a new area for many CIOs and their teams in government, and that AI requires transformation and new approaches to technology, finding and then articulating the right projects that can be delivered quickly can be a challenge.
“Because project objectives tend to be relatively modest, in pursuit of a quick return on investment, there is also an educational portion that IT teams must do with the executive,” Lacheca said. “We often hear elements of frustration like 'my teenager is at home using ChatGPT, why are you making things more complicated for us?'
“Therefore, managing expectations of what can be achieved with the technology, given the focus on immediate objectives, and overcoming doubts around citizen-facing services is part of the process with government adoption of AI in this moment”.
Gartner's Solution: Focus on Delivering Internal Applications First
According to Gartner, the solution to these challenges with AI adoption is to start by delivering applications that are not citizen-facing but can support productivity gains within the internal organization. The “morning” fruit enables government agencies and departments to avoid the perceived risks associated with AI in citizen-facing services, while developing the critical knowledge and skills needed to develop more ambitious AI strategies.
Agencies should also build trust and mitigate associated risks by establishing transparent AI governance and assurance frameworks for internally developed and acquired AI capabilities, Gartner's guidance adds.
“There is a lot that government organizations need to do to take steps toward AI,” Lacheca said. “For one use case, for example, an agency might want to summarize a set of data, but that data contains personal information and may not have the correct metadata tags. Maybe you want to analyze that.
“Others are looking for cloud solutions where the data never leaves their world, and others are looking for the 'stained glass' approach that will ensure a level of data obfuscation on the way out as a strategy to protect privacy. “There is a lot of architectural maturity in the way AI strategies are implemented, so organizations should look to develop these capabilities before applying them to public deployments,” he added.
How partners should look to engage the Australian government on AI
These internal tensions will also affect Australian government agency partners. There is an appetite for AI, but making a decisive move and helping to implement solutions means understanding that austerity in government budgets is unusually prolonged and that conservatism about the possible consequences is more sensitive than might be the case in other sectors.
“The next steps that the government could take will probably be much slower than some of its commercial counterparts, because its risk appetite has to be different,” Lacheca said.
For IT professionals working in and in partnership with government agencies, Gartner's recommendations for how to take a step forward with AI boil down to being able to demonstrate a rapid return on investment with minimal risk to public data and interactions. . Partners that can achieve this will be in a strong position when the government begins to accelerate adoption to meet its long-term ambitions.
