Issues and Insights Article, 48th Parliament

Potential impact of Artificial Intelligence (AI) on the Australian workforce

International research reveals several potential benefits and risks to the economy in adopting AI. While higher educated professionals and managers are most likely to be exposed to AI, the overall impact of such exposure on employment and wages remains uncertain.

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Key issues

Artificial intelligence (AI) has the potential to provide several benefits, risks and challenges for the future Australian workforce. These include:

greater productivity and quality of work for individual workers and workplaces
higher productivity across the economy more generally (but the gains may be restricted if the development and use of AI is predominantly concentrated within a few large corporations)
likelihood of unequal impacts across occupations, with possible future job loss and creation, and changes in tasks within occupations
widening economic inequality if workers in some occupations benefit more than others.

Introduction

The Australian labour market has changed significantly over the past century. New occupations have emerged, disappeared and changed, particularly in response to technological developments. For example, the introduction of computers has required new skills within existing and newly created occupations. Greater mechanisation, robot technology and computerisation has seen the decline or disappearance of occupations such as switchboard operators, cashiers, factory workers, and data-entry clerks.

The emergence and diffusion of artificial intelligence (AI) across the Australian economy is the latest technological phenomenon to challenge the way we work and interact. Its impact raises several questions about what Australia’s future labour market could look like. Will AI impact some jobs and occupations more than others? Will it create new occupations and new jobs? And will it benefit some workers more than others, further accentuating income and wealth inequality?

What is AI?

There is no universally accepted definition of AI, but it is commonly understood to be machine-based systems (AI systems) that autonomously and adaptively make decisions or generate textual, visual or audio content based on user inputs. In the workplace, AI systems assist in routine work such as scheduling, resource management, document drafting and filing, data analysis and decision-making.

Potential benefits

The OECD has predicted that the introduction of AI should deliver greater productivity growth across various industries and deliver new types of jobs. However, measuring the extent of productivity gains from previous technological development has proven difficult. Specifically, there is a lack of consensus regarding productivity dividends from digitisation (such as increased personal computer and digital platform use). Accordingly, the magnitude of AI’s potential productivity benefits is difficult to quantify. Some economists predict substantial gains, while others are less optimistic.

Oxford Economics found the uptake of AI could spur new waves of innovation, lifting the rate of productivity growth over the long run. It estimates that by 2032, the US, as a leading generator of AI technology, could experience GDP growth of 1.8%–4%, depending on how quickly AI is adopted. Conversely, as more of a user (rather than generator) of AI technology, it is estimated Australia will reap around 0.17% higher GDP by the mid-2030s.

Employee surveys undertaken for the OECD have highlighted AI’s economic and non-economic benefits. These include improved job performance, greater enjoyment and positive physical and mental health outcomes resulting from replacing or reducing menial and tedious tasks. Employees in managerial and professional occupations in industries such as finance and insurance were more likely to report greater satisfaction from working with AI and these occupations were more likely to be filled by men. Employers cite improving productivity, lowering costs and improving worker health and safety as prime motivators for implementing AI.

Labour economist David Autor has stated that AI has the potential to benefit workers more broadly than other information and communications technology (ICT) breakthroughs, which have disproportionately benefited professionals and managers. Autor postulates that, with appropriate training, AI could enable a larger share of the workforce to perform ‘higher-stakes decision-making tasks’ currently performed by elite experts, such as doctors, lawyers, software engineers and college professors. This could help restore the ‘middle-skill, middle-class heart of the U.S. labour market’ most heavily impacted by job loss through automation and globalisation (known as job polarisation). However, this hypothesis is not based on empirical research and differs from the OECD’s findings that it will be highly qualified professionals in more AI-exposed occupations who will most likely be impacted.

Potential risks associated with AI

The OECD has also highlighted several risks associated with AI’s introduction and diffusion. These include the dangers of market concentration and potential widening of inequality and poverty within and between countries.

If AI is controlled by a few large firms through market concentration, there is a danger that the benefits of AI may not translate into higher productivity across the broader economy or deliver lower prices for consumers. This concentration could also limit the adoption of AI by smaller and medium-sized firms and organisations that lack the necessary resources to adopt it. From a geopolitical perspective, countries such as the US and China with more substantial AI investment, may reap more benefits than other less-resourced countries.

AI could also worsen income and wealth inequality through accelerating job loss already experienced due to automation. The more highly educated and qualified workers achieving AI-generated productivity gains could receive higher wage increases, increasing the potential for income and wealth inequality.

A 2023 report by McKinsey found generative AI could undertake tasks that currently account for 30% of hours worked in the US economy. Within this model, low-paid workers (such as clerical, retail and administrative staff) were around 14 times more likely to lose their job due to AI than higher paid workers. The report notes that the transitioning of workers to new occupations and different skill sets due to job loss resulting from AI may be difficult and would disproportionately impact women.

In January 2025, the House of Representatives Committee Inquiry into the Digital Transformation of Workplaces released its Future of work report, which recommended Australian governments develop campaigns to inform people about how AI works, outline its associated opportunities and challenges, and encourage training and upskilling in industries most exposed to AI.

The Australian Council of Trade Unions recognises the benefits of adopting AI in the modern workforce, but has also raised concerns. These primarily include the potential erosion of worker’s rights, conditions, and job security in the absence of adequate regulation and meaningful consultation.

Industry sectors most likely to be affected

The OECD has identified AI’s potential impact on various industry sectors, including:

transport (such as self-driving or autonomous vehicles)
agriculture (to optimise harvesting timing and monitor conditions needed to maximise crop yields)
financial services (to facilitate assessing credit worthiness of potential customers and risk of default); financial technology lending (to enable consumers to apply for and obtain loans online); reducing regulatory compliance costs (by enabling better fraud detection); and facilitating algorithmic market trading
marketing and advertising (to enable customer preferences for consumer goods to be better matched)
science (convergence of AI and robotics facilitates faster scientific discoveries, reduced costs of experimentation and improved knowledge-sharing)
health (earlier detection of health conditions, delivery of preventative services, optimal clinical decision-making and new treatment and medication discovery).

Occupations and demographic groups most/least likely affected by AI

The OECD analysed occupational and demographic groups across 22 OECD countries (excluding Australia) to understand AI exposure levels. The average exposure ratios shown in Table 1 measure how closely an occupation’s required technical skills corresponded or overlapped with AI’s technical capabilities. The higher the ratio score, the more exposed occupations were to AI.

Managers and professional occupations recorded the highest AI exposure scores. A strong positive relationship existed between AI exposure and workers’ educational attainment. However, this does not predict whether such exposure will have a positive or negative effect. AI may simply change the nature of tasks within occupations without significant job loss or impact on wages.

The OECD found that from 2012–22 employment growth was strongest in occupations with higher exposure to AI. It also saw no evidence of widening wage inequality within occupations resulting from greater exposure to AI. The OECD found the relationship between AI exposure and gender was much weaker, with males and females facing similar occupational exposure to AI.

Table 1 Occupational exposure to AI (%) (average for 22 OECD countries), 2022

Occupation categories	Average AI exposure	Tertiary educated	Male	30–54 years
Five most exposed occupations
Science & engineering professionals	0.84	87	69	67
Chief executives	0.85	72	68	62
Managers	0.86	76	59	73
Business professionals	0.87	82	45	69
IT technology professionals	0.88	79	81	70
Five least exposed occupations
Cleaners, helpers	0.25	9	18	56
Agriculture forestry & fishery labourers	0.34	8	65	46
Food preparation assistants	0.39	7	31	47
Labourers	0.42	8	72	54
Refuse workers & other elementary workers	0.43	10	72	49
All occupations	0.65	37	57	60

Source: Marguerita Lane, Who Will be the Workers Most Affected by AI?: A Closer Look at the Impact of AI on Women, Low-skilled Workers and Other Groups, OECD Artificial Intelligence Papers, Working paper no. 26, (OECD Publishing, October 2024).

ABS Census of Population and Housing data for 2021 and Australian and New Zealand Standard Classification of Occupations categories allow similar analysis for Australia (see Table 2). The data shows people employed in occupations most exposed to AI (such as science, engineering and ICT professionals) were more likely to be male and aged 30–54 years. However, males also accounted for larger shares of occupations that were least exposed to AI such as farm, forestry and garden workers and other labouring occupations.

Younger people aged 15–29 years accounted for much higher shares of less-skilled occupations least exposed to AI. However, many young people may be engaged in these occupations relatively briefly. This is primarily due to them combining study with part-time jobs in occupations such as cleaning, food preparation or labouring.

Table 2 Demographic profile (%) of occupations with most and least exposure to AI, Australia, 2021

Occupation categories	Tertiary educated	Male	15–29 years	30–54 years	55 years plus
Five most exposed occupations
Design, engineering, science & transport professionals	87	67	23	62	16
Chief executives, general managers & legislators	69	71	3	65	32
Other managers	56	59	11	65	24
Business, human resource & marketing professionals	80	48	19	65	16
ICT professionals	83	79	16	73	11
Four least exposed occupations
Cleaners & laundry workers	22	40	22	49	30
Farm, forestry & garden workers	15	72	34	43	23
Food preparation assistants	15	52	66	23	11
Other labourers	15	77	33	14	20
All occupations	47	52	25	55	20

Source: Australian Bureau of Statistics, Census of Population and Housing, 2021 (TableBuilder)

Assuming greater exposure to AI contributes to higher wage growth, men’s higher representation in such occupations may exacerbate measures of inequality, such as the gender wage gap. However, if AI can be diffused into industries with higher female representation, such as education and training and healthcare and social assistance, this may narrow gender inequities.

Prevalence of workers with AI skills

OECD analysis of LinkedIn members has gauged the prevalence of workers with AI skills by gender and country from 2015 to 2023. Calculating the ratio between a country’s proportion of workers with AI skills relative to the average for all OECD countries canvassed, results in an AI skills penetration factor (see Figure 1).

Australia recorded an AI skills penetration factor ratio of 0.98, just below the OECD average (of 1.0). This ranked Australia 15th out of 36 OECD countries in 2023, an improvement from 19th in 2022, but slightly worse than 14th in 2021.

Only India and the US recorded AI penetration ratios for women above the OECD average of 1.0 (at 1.65 and 1.23 respectively). Australian women recorded an AI penetration ratio of 0.37 which ranked them 18th out of 30 OECD countries (where estimates were available). Australian men had a reported AI skills penetration ratio of 0.92, which ranked them 20th for males out of the 30 OECD countries surveyed.

Australia’s relatively poor AI penetration rate, compared with other OECD countries, indicates there may be scope for greater investment in AI-related skills and training for Australian workers in industries more likely to use AI.

Figure 1 AI skills penetration factor – average for 2015 to 2023

Note: A country needed at least 100,000 LinkedIn members to be included in the survey. Due to its narrow focus on members of LinkedIn (who are mainly professionals), it excludes the rate of AI skills penetration for less-skilled workers.

Source: OECD.AI (2025), ‘Cross-country AI skills penetration’.

Investment in AI in Australia and across the globe

Venture capital (VC) investment expenditure in AI can be used to monitor growth in capital provided to start-up companies and small businesses with long-term growth potential. OECD data shows VC investment in AI in Australia increased substantially from A$100 million in 2017 to just under A$2.2 billion in 2021 (see Figure 2). Investment subsequently more than halved to A$906 million in 2023, but the reasons for this decline are not specified.

Figure 2 Venture capital investment in AI, Australia, 2012 to 2023 (A$ million)

Note: OECD data in USD has been converted to AUD using the average exchange rate for each year.

Source: OECD.AI Policy Observatory, Live data sourced from Prequin; Reserve Bank of Australia, Historical Data, Exchange Rates.

The rise and decline in AI VC investment in Australia aligns with trends also observed in both the US and China, which are world leaders in AI investment. Our World Data shows global corporate investment in AI in real terms increased dramatically from US$17 billion in 2013 to US$337.4 billion in 2021, before almost halving to US$168 billion in 2023. Global private investment in AI stood at US$85 billion in 2023, with the US contributing 70% (US$60 billion).

S&P Global suggests that the cost of developing AI models and higher interest rates has constrained investment in AI in recent years. As a result, larger corporations with greater financial resources (such as Google, Amazon and Microsoft) have dominated recent AI investment activity.

The Stanford HIA 2024 AI Index also highlighted the significant decline in global investment in AI in 2023, with a major reason being a fall in the level of mergers and acquisitions. The index showed a substantial shift in global private equity investment to AI infrastructure, research and governance in 2023 compared with the previous year, and contracting investment in medical and health care services.

Conclusion

International research reveals several potential benefits and risks to the Australian economy in adopting AI. While higher educated professionals and managers are more likely to be exposed to AI, the overall impact of such exposure on employment and wages remains uncertain.

Aggregate productivity and efficiency benefits from the development and diffusion of AI may be reduced if its development and use is restricted to a few large corporations. Given these challenges, Parliament may want to monitor this area and consider how to ensure AI’s benefits are being distributed widely and equitably, and that workers have the skills and training necessary to engage in this new technological landscape.