Australia's approach to innovation has come under renewed scrutiny as government, academic, and industry leaders highlight the nation's struggle to convert research into commercial outcomes, and call for urgent improvement in the adoption of artificial intelligence by businesses.
Innovation concerns
Australia currently invests 1.68% of its GDP in research and development, lagging well behind the OECD average of 2.7%. Historical data show this figure has deteriorated, falling from 2.25% in 2008 even as other countries improved their position.
The country is now ranked 105th out of 135 globally for commercialising its research output.
Speaking in Canberra, Professor Chennupati Jagadish, President of the Australian Academy of Science, underscored the wider stakes for national security and economic prosperity. He described the nation's capability gap in innovation as "a matter of strategic national interest".
Fragmented landscape
The challenge is compounded by fragmentation across the Australian research sector. There are currently 160 research-related programmes administered by 14 different government portfolios at federal level alone.
Minister for Industry and Innovation and Minister for Science Tim Ayres highlighted the need for greater coordination and a more unified approach to boosting science and technology capability.
SME potential
While statistics on national innovation are sobering, business and technology specialists maintain that opportunities remain for progress, particularly among small and medium-sized enterprises.
Professor Cori Stewart, Chief Executive of the ARM Hub, argued that SMEs are well-positioned to move rapidly with AI and automation because they do not face the legacy burdens of larger corporations.
"At this time we have industries starting to understand their troubles, and we have AI that can actually support SMEs as much as global corporations. If we're smart, we can do it. But if we don't, there's no Plan B," said Stewart
Adoption approach
Australian manufacturers have the capacity to adopt artificial intelligence efficiently, but face barriers that are cultural and procedural rather than technological.
Drawing lessons from the introduction of computer-based office systems in previous decades, Professor Stewart said successful technology rollouts depend less on new tools, and more on matching solutions to specific business challenges and investing in the people who operate them.
Research supports a people-centred approach. McKinsey's most recent State of AI report found transformative impact where companies redesign workflows and focus on employees during the adoption process. Boston Consulting Group's analysis indicates that 74% of organisations struggle to scale AI value, often because their attention is on technical aspects rather than people and processes.
Workforce transition
Professor Stewart emphasised that AI presents both risks and opportunities for jobs, making retraining and upskilling central to a successful transition. Models of adoption that focus predominantly on people and process-as much as 70% according to management studies-are now considered a prerequisite.
"The good news is we already know how to do this. The challenge isn't the technology. It's the same people and process work we mastered when we moved from paper-based systems to computers in the 1980s and 90s. When you focus on matching AI to the right business problems and getting your teams ready to use it, adoption becomes straightforward. We can do this. We do do this. We just need to apply what we already know," said Stewart
Demonstrated outcomes
ARM Hub is one of four government-backed AI Adopt Centres tasked with bridging the gap between research and practical business application. Companies such as Nexobot in Melbourne and Microbio in Brisbane are cited as examples of successful AI deployment, using automation and diagnostics to address sector-specific problems.
"The government has invested $17 million in four AI Adopt Centres. Businesses who have engaged with these centres are already finding ways to improve the world of work and service provision," said Ayres
The focus at the centres is on practical implementation.
As Stewart said, "We're not helping companies become AI experts. We're helping them identify high-impact problems, train their teams and deploy solutions that prove ROI within months."
