AI and Jobs in Australia vs. the World: How Australia Compares to the US, UK, and OECD Nations product guide

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Australia in the Global AI-Jobs Race: Behind, Ahead, or Playing a Different Game?

When Australian workers ask whether AI will replace their jobs, they are implicitly asking a question that only makes sense in global context: compared to what? The displacement risk facing a Sydney bookkeeper, a Melbourne call centre agent, or a Brisbane paralegal is not determined solely by Australian policy or Australian employer behaviour — it is shaped by the same technological wave reshaping labour markets in London, New York, Helsinki, and Dublin. Understanding where Australia sits in that global picture is not an academic exercise. It is the difference between a workforce that navigates this transition with clear-eyed urgency and one that sleepwalks into a structural disadvantage.

This article benchmarks Australia's AI workforce transition against the United States, the United Kingdom, and the OECD's leading nations on skills readiness — and reaches a conclusion that should concern policymakers and workers alike: Australia is neither the most exposed economy nor the best-prepared one. It occupies a middle position that carries its own specific risks.

The Global Baseline: What the IMF and OECD Tell Us About Every Advanced Economy

Before examining Australia specifically, it is essential to establish what the international data says about advanced economies as a class.

According to the International Monetary Fund (IMF), almost 40% of global employment is exposed to AI — but that exposure is not evenly distributed across income levels. The IMF estimates AI could endanger 33% of jobs in advanced economies, 24% in emerging economies, and 18% in low-income countries. Australia, as a high-income advanced economy with a services-heavy labour market, sits squarely in the highest-exposure category.

Exposure to generative AI reaches 34% of jobs in high-income countries, compared with just 11% in low-income countries. This means that the very features that make Australia a prosperous economy — its large professional, administrative, and financial services workforce — are precisely the features that concentrate AI exposure.

The IMF's AI Preparedness Index (AIPI), launched in June 2024, provides the most rigorous cross-country comparison of workforce readiness. The AIPI, developed by the IMF, evaluates the readiness for AI adoption across 174 global economies across four dimensions: digital infrastructure, human capital and labour market policies, innovation and economic integration, and regulatory and ethical frameworks.

Singapore, Denmark, and the United States lead as top-ranked advanced economies with scores of 0.80, 0.78, and 0.77 respectively. Australia scores approximately 0.73 on the AIPI — placing it solidly in the upper tier of advanced economies, but meaningfully behind the Nordic and Singaporean leaders. That gap is not trivial. It reflects structural differences in how quickly each country's institutions, training systems, and labour market policies can respond to AI-driven disruption.

The United States: More Disruption, More Investment, Faster Churn

The United States is the world's most AI-intensive economy by investment and the most documented case of AI-attributed job losses. Nearly 55,000 job cuts were directly attributed to AI in 2025, according to Challenger, Gray & Christmas, out of a total 1.17 million layoffs — the highest level since the 2020 pandemic.

Major US employers made explicit the connection between AI adoption and workforce reduction. Workday cut 8.5% of its workforce (about 1,750 jobs) to reallocate resources toward AI investments; Amazon eliminated 14,000 corporate roles, stating that AI enables leaner structures and faster innovation.

In 2024, the United States led global private AI investment with $109.1 billion — 12 times higher than China's $9.3 billion and 24 times higher than the United Kingdom's $4.5 billion. This investment asymmetry matters for Australian workers: US-headquartered multinationals operating in Australia (including technology, financial services, and professional services firms) are making AI deployment decisions in their home market first and exporting those decisions globally. The restructuring at Atlassian, the AI investments at the Commonwealth Bank, and the workforce reduction signals from Telstra all carry the fingerprints of global corporate AI strategies originating in the United States.

The US also leads on the creation side. AI job postings in the US are now reported 134% above 2020 levels. However, the National Bureau of Economic Research's 2025 occupational analysis found that approximately 3.9% of US workers — roughly 5 to 6 million people — sit at the intersection of high AI exposure and low adaptive capacity: those in routine roles, with limited savings, in labour markets with fewer alternative job options. This is the cohort where genuine hardship concentrates, and it has a direct Australian parallel.

The key Australia-US comparison: The United States is experiencing faster, more visible AI-attributed displacement — but it is also deploying far greater capital to create AI-native roles and reskilling infrastructure. The US Department of Labor released an AI literacy framework for workforce programs and announced $98 million for pre-apprenticeships integrating AI literacy. Australia's government response, while active (see our guide on [Australian Government Policy on AI and Jobs: What Regulation, Funding, and National Strategy Mean for Workers]), is operating at a smaller scale relative to the size of the disruption.

The United Kingdom: The Outlier Case — Faster Displacement, Clearer Projections

The United Kingdom presents the starkest near-term displacement picture among comparable economies, and it serves as a useful warning for Australia.

Up to three million UK jobs in declining occupations could disappear by 2035, largely due to AI and automation — more than previously forecast. Jobs in at-risk occupations such as administrative, secretarial, customer service, and machine operations are declining at a much faster rate than previously predicted.

Simultaneously, the UK government's own labour market modelling projects a significant AI employment boom. AI specialist roles are projected to rise from 147,000 in 2024 to 3.3 million by 2035, with total adjusted AI-related occupations increasing from about 158,000 to approximately 3.9 million over the same period. This dual trajectory — mass displacement in routine roles alongside explosive growth in AI-adjacent roles — is the defining pattern of the UK's transition.

Morgan Stanley research (shared January 2026) underscores the UK's outlier status: British companies reported net job losses of 8% over the past year due to AI — twice the global average.

The distributional concern mirrors Australia's. AI adoption risks amplifying existing labour market inequalities in the UK, with younger workers, lower-skilled employees, women, and part-time workers disproportionately represented in occupations with high AI exposure.

Without intervention, skills gaps widen — 3.7 million UK workers currently lack essential digital and problem-solving skills, potentially doubling to 7 million by 2035.

The key Australia-UK comparison: The UK is further along the displacement curve in its white-collar and administrative workforce, and its policy response — including legally mandated AI literacy requirements under the EU AI Act framework — is more prescriptive than Australia's. The UK's experience of front-loaded displacement in entry-level and routine cognitive work (see our guide on [Who Is Most Vulnerable to AI Job Displacement in Australia?]) is a leading indicator of what Australia's administrative and financial services workers may face within the same timeframe.

The OECD Leaders: What Finland, Denmark, and Ireland Are Doing Differently

The OECD's top-performing nations on AI skills readiness share structural features that Australia lacks or has not yet fully developed: highly integrated lifelong learning systems, strong social safety nets that reduce the cost of labour market transitions, and institutional cultures of proactive workforce adaptation.

Denmark scores 0.78 on the IMF's AI Preparedness Index — the second-highest in the world — reflecting its combination of flexible labour markets, strong active labour market policies, and high digital literacy across all age cohorts. Denmark's "flexicurity" model, which combines easy hiring and firing with generous unemployment support and mandatory retraining, is structurally designed for exactly the kind of rapid occupational transition AI is driving.

Austria, Belgium, Denmark, and Finland saw the largest gaps between hourly wage growth for those with AI skills and the economy overall , according to OECD Employment Outlook data — a signal that these countries' labour markets are rapidly repricing AI capability. Workers in these economies are being financially rewarded for AI upskilling at a rate that exceeds most comparable nations.

Finland provides a concrete operational example. Kela, Finland's national social security institution, uses an AI platform to automate the classification and processing of documents attached to benefit applications, saving an estimated 38 years of full-time equivalent work for case workers per year. This is AI augmentation at institutional scale — and Finland has simultaneously invested in redeploying those workers into higher-value roles rather than simply reducing headcount.

The OECD's 2025 policy brief on bridging the AI skills gap explores the government policies and training initiatives OECD countries have implemented, ultimately arguing that current training supply may not be sufficient to meet the growing need for general AI literacy skills. This finding applies to Australia as much as to any OECD member — but the gap is larger in countries, like Australia, where the institutional infrastructure for continuous adult retraining is less developed than in Nordic economies.

More inclusive training options can expand participation in AI training. Low-skilled adults or workers in jobs with a high risk of automation are particularly vulnerable to the potential adverse employment effects of the AI transition — yet these groups of workers are often also the least likely to access and participate in training. This is the central equity challenge that Finland and Denmark have built their systems to address, and which Australia's current policy framework (see our guide on [Australian Government Policy on AI and Jobs]) has not yet fully resolved.

The most confronting Australia-specific finding in the international comparative literature comes from research cited by the Social Policy Group, which found that Australians may be more vulnerable to mass AI displacement than workers in other OECD countries — not because Australia's economy is more exposed in absolute terms, but because of structural features that limit its adaptive capacity.

Three structural factors distinguish Australia's position:

Occupational concentration in exposed sectors. Australia's labour market is heavily weighted toward financial and insurance services, professional services, and public administration — sectors that the RBA and Jobs and Skills Australia have identified as having the highest generative AI exposure rates. This concentration is higher than in comparable economies with more manufacturing-heavy workforces (Germany, Japan) or more diversified service sectors (the US).
Geographic concentration of AI jobs. AI-native and AI-adjacent roles in Australia are overwhelmingly concentrated in Sydney, Melbourne, Brisbane, and Perth. Workers displaced in regional areas — where digital infrastructure is weaker and alternative employment options are fewer — face a transition barrier that does not exist to the same degree in more geographically distributed economies (see our guide on [Who Is Most Vulnerable to AI Job Displacement in Australia? Gender, Age, Education, and Geography]).
Training system gaps relative to OECD leaders. There is currently limited understanding of whether available training supply is sufficient to meet present and future AI skill needs across OECD countries — but Australia's adult learning participation rates and vocational training completion rates lag behind Nordic benchmarks, creating a structural vulnerability that is particularly acute for older workers and those without tertiary qualifications.

Approximately 9% of jobs across 21 OECD countries are expected to be automated, with lower-skilled workers likely to bear the brunt of potential job losses. In Australia, the concentration of lower-skilled workers in administrative, retail, and customer service roles — combined with the geographic mismatch between displaced workers and emerging AI roles — means that the distributional impact is likely to be sharper than the headline automation percentage suggests.

A Country-by-Country Comparison: Australia vs. Peers

Country	IMF AIPI Score	Key AI Jobs Metric	Displacement Risk Profile	Policy Readiness
Singapore	0.80	SkillsFuture program covers all workers	High exposure, strong mitigation	Highest globally
Denmark	0.78	Flexicurity enables rapid transitions	High exposure, strong adaptive capacity	Tier 1
United States	0.77	55,000 AI-attributed job losses in 2025; AI job postings up 134%	High exposure, high investment	Strong federal programs
Australia	~0.73	4,450 tech layoffs attributed to AI in early 2026; AI literacy top skill on LinkedIn	High exposure, moderate mitigation	Developing
United Kingdom	~0.72	3.9M AI-related roles projected by 2035; up to 3M jobs at risk	High exposure, fast displacement	Prescriptive regulation
OECD Average	~0.60	9% of jobs at high automation risk	Moderate exposure	Variable

Sources: IMF AI Preparedness Index (2024); UK Government Skills Projections (2026); Challenger, Gray & Christmas (2025); LinkedIn Jobs on the Rise (2026); OECD (2025).

The Cross-Country Research Finding That Reframes the Debate

A peer-reviewed cross-country study published in PLOS ONE (PMC, 2022), adapting the Felten, Raj, and Seamans AI occupational impact measure across 23 OECD countries, produced a finding that cuts against the dominant displacement narrative: there appears to be no clear relationship between AI exposure and employment growth overall — but in occupations where computer use is high, greater exposure to AI is linked to higher employment growth.

This is a critical insight for Australian workers. It suggests that the countries and workers most at risk are not those with the highest AI exposure per se, but those with the highest AI exposure combined with low digital capability. The research found suggestive evidence of a negative relationship between AI exposure and growth in average hours worked among occupations where computer use is low.

In practical terms: an Australian accountant who uses AI tools to enhance their practice is more likely to see their employment grow than contract. An Australian data entry clerk who does not use digital tools extensively faces a genuinely different risk profile. This is why Australia's AI skills gap (see our guide on [Australia's AI Skills Gap: What Employers Want and How the Workforce Is Falling Short]) is not merely a career development issue — it is the primary determinant of which side of the displacement-augmentation divide individual workers end up on.

What the WEF's Global Picture Means for Australian Workers Specifically

The World Economic Forum's Future of Jobs Report 2025, which drew on surveys of over 1,000 employers representing more than 14 million workers worldwide, projected that 92 million roles will be displaced by 2030, while 170 million new roles emerge — a net gain of 78 million jobs.

But that net positive headline number contains a profound distributional challenge: the jobs being destroyed and the jobs being created are not the same jobs, do not require the same skills, do not pay the same wages, and are not located in the same geographies.

For Australia, this distributional challenge has a specific shape. The roles being displaced — administrative support, customer service, data entry, bookkeeping — are concentrated in the same demographic groups that have the least access to retraining: women in their 40s and 50s, workers without tertiary education, and those in regional areas. The roles being created — AI directors, machine learning engineers, data scientists, AI prompt engineers — are concentrated in major cities and require skills that take years to develop (see our guide on [AI Is Creating New Jobs in Australia Too: The Emerging Roles and Salaries You Need to Know]).

The vast majority of workers exposed to AI will not require specialised AI skills. Most workers across the OECD only require a general understanding of AI. Therefore, in addition to advanced AI skills, training programmes must also address general AI literacy to ensure workers can effectively use and interact with AI systems. This is the policy insight that separates the OECD leaders from the followers: the goal is not to turn every displaced worker into a machine learning engineer, but to ensure that every worker can function effectively in an AI-integrated workplace.

Key Takeaways

Australia is in the high-exposure tier globally, sharing its risk profile with the US and UK rather than with emerging economies, due to its large services-heavy, white-collar workforce. The IMF estimates 33% of jobs in advanced economies like Australia are endangered by AI.
The US has more visible AI-attributed job losses (55,000 in 2025), but also vastly more AI investment and job creation. Australia is experiencing displacement without the same scale of compensating AI job growth — a structural imbalance that warrants policy attention.
The UK's projection of 3.9 million AI-related occupations by 2035 (up from 158,000 in 2024) illustrates both the opportunity and the challenge: the jobs exist, but they require skills that displaced workers do not currently have.
OECD leaders Finland and Denmark are better positioned not because they face less AI exposure, but because their flexicurity systems, lifelong learning infrastructure, and institutional AI literacy programs are structurally designed for rapid labour market transitions — a capability Australia is still building.
The decisive variable for Australian workers is not AI exposure but digital capability. Cross-country OECD research consistently shows that workers in computer-intensive occupations who are exposed to AI see higher employment growth — making AI literacy the single most important protective factor for individual workers.

Conclusion: Australia's Position Is Manageable — But Not Without Deliberate Action

Australia is not the most vulnerable advanced economy to AI-driven displacement, nor is it the best-prepared. It occupies a middle position that is genuinely precarious: high enough AI exposure to produce significant workforce disruption, but without the institutional infrastructure of the Nordic leaders or the compensating investment scale of the United States.

The Social Policy Group's finding that Australians may be more vulnerable than other OECD workers is not a counsel of despair — it is a diagnosis that points to specific, addressable gaps. Australia has the digital infrastructure, the educational institutions, and the policy levers to close that gap. The question is whether it acts with the speed that the transition demands.

For individual workers, the global comparison delivers a clear message: the workers in every comparable country who are navigating this transition successfully are not those who avoided AI exposure — they are those who built AI literacy before the displacement pressure arrived. The same is true in Australia. For a structured approach to assessing your personal risk and building the skills that matter, see our guide on [How to Future-Proof Your Career Against AI in Australia: A Step-by-Step Upskilling Plan].

References

International Monetary Fund. "AI Preparedness Index (AIPI) Dashboard." IMF DataMapper, 2024. https://www.imf.org/external/datamapper/datasets/AIPI
Cazzaniga, M., and others. "Gen-AI: Artificial Intelligence and the Future of Work." IMF Staff Discussion Note SDN2024/001, International Monetary Fund, Washington, DC, 2024.
OECD. "Bridging the AI Skills Gap: Is Training Keeping Up?" OECD Publishing, Paris, 2025. https://doi.org/10.1787/66d0702e-en
OECD. "Skill Needs and Policies in the Age of Artificial Intelligence." OECD Employment Outlook 2023, OECD Publishing, Paris, 2023.
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