Australia has spent decades importing much of the technology that runs its digital economy. AI could make that dependence considerably more expensive.
The Albanese government is increasingly arguing that Australia cannot afford to become merely a customer of overseas AI companies. Assistant Minister for Science, Technology and the Digital Economy Andrew Charlton has warned that the country risks becoming a permanent “renter of intelligence” if more of the economic value generated by AI flows offshore.
In a May speech outlining Australia’s AI ambitions, Charlton framed the choice as building a domestic AI industry or becoming increasingly dependent on foreign platforms.
For Australian CIOs, the debate is more practical than patriotic. As AI becomes embedded in workplace software, cloud infrastructure and business processes, organisations will need to decide how much control they are comfortable handing to overseas model providers and where local alternatives are actually viable.
Australia’s AI bill could keep climbing
The economics are beginning to sharpen the argument.
Recent Australian reporting puts current national spending on AI at roughly $5 billion to $8 billion annually, much of it going to overseas providers. That figure could eventually reach $40 billion a year within a decade if Australia remains heavily dependent on imported AI services, according to comments from Charlton reported by News.com.au. The forecast has intensified the government’s push for more Australian-owned models and AI companies.
The concern mirrors a broader technology sovereignty debate already reaching Australian enterprises. As TechRepublic has previously examined, governments around the world are reconsidering who controls critical digital infrastructure and data.
AI raises the stakes because organisations are no longer talking only about where data is stored. They must also consider who provides the models that interpret that data, the compute that runs them, and the platforms that increasingly make automated decisions.
Sovereign AI does not mean building an Australian ChatGPT
Australia is unlikely to challenge the spending power of the US or China by attempting to build frontier foundation models from scratch.
Charlton has instead argued that Australia should choose where it competes across the AI “stack,” which includes energy, chips, data centres, foundation models, software and services. In a speech to the Australian Business Economists Conference, he pointed to opportunities for Australia across areas including energy, data centre infrastructure, software and applied AI.
That distinction matters for Australian technology leaders.
An Australian enterprise may have little reason to reject a leading overseas foundation model simply because it was developed abroad. But it may choose to run an open-weight model locally, keep sensitive workloads inside Australian infrastructure or buy specialised AI from a domestic provider with expertise in areas such as healthcare, mining or financial services.
That option is becoming more realistic as capable open-weight models proliferate. TechRepublic recently examined how open-weight AI could give Australian enterprises more control over models and sensitive data.
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Australia already has some pieces of the AI stack
Australia is not starting from zero.
Charlton has said the country has more than 1,500 AI companies, while government policy is increasingly targeting the infrastructure and investment needed to grow the domestic ecosystem. His February speech on building an Australian AI stack highlighted local AI businesses, research capabilities and data centre operators as potential foundations for that growth.
Infrastructure is receiving particular attention. In March, the government introduced expectations for data centre and AI infrastructure developers covering energy, water, jobs, research capability and national resilience. Those expectations are now feeding into broader Australian AI standards. The government says its proposed framework will require large data centres to underwrite new power supply and pay their share of connection costs.
Foreign investment is also part of the strategy rather than something Canberra is trying to eliminate. In April, the government signed an AI collaboration agreement with Anthropic focused on areas including Australian researchers, workers, startups, skills and the broader AI ecosystem.
Later that month, Canberra signed a separate agreement with Microsoft, alongside the company’s announced $25 billion investment in Australian digital infrastructure, workforce training and cybersecurity. That makes Australia’s emerging version of AI sovereignty less about shutting the door on foreign technology and more about capturing more of the investment, capability, and economic value it creates.
It also builds on an infrastructure trend already visible locally. TechRepublic has previously explored how Australian data centres are positioning themselves for increasingly sovereign AI workloads.
What Australian CIOs should watch
For Australian IT leaders, sovereignty is likely to become another dimension of AI procurement alongside price, performance and security.
Teams evaluating AI platforms may increasingly need to ask where models run, where organisational data travels, whether workloads can move between providers and what happens if pricing or access to an overseas model changes.
That does not mean every workload needs an Australian model or an Australian-owned cloud. It does mean vendor concentration deserves to be treated as an architectural risk rather than simply a procurement convenience.
Australia’s AI challenge, then, is not to recreate Silicon Valley on the shores of Sydney Harbour. It is to decide which parts of the AI economy are important enough to own.
If AI becomes as fundamental to business as cloud computing did over the previous decade, that decision could determine whether Australian companies merely consume the next generation of technology or capture a meaningful share of the value it creates.
Also read: See how AI is already reshaping Australia’s job market, from slower hiring in AI-exposed occupations to changing skill demands for Australian workers.