Generative AI and the future of work in Australia (2024)

(62 pages)

In a 2019 report, Australia’s automation opportunity: Reigniting productivity and inclusive income growth, McKinsey examined the possible impact of automation on the future of work. Australia’s economy was at the tail end of a three-decade boom and losing momentum fast—yet the automation wave was on the horizon, bringing the possibility of inclusive economic growth and an uplift in productivity. The report found that, to realize this promise, Australia would need to embrace rapid automation adoption and facilitate social inclusion in the process.1Australia’s automation opportunity: Reigniting productivity and inclusive income growth, McKinsey, March 3, 2019.

What is generative AI?

In this report, generative AI (gen AI) encompasses applications typically constructed using foundation models, a class of artificial neural networks that have layered structures comparable to the human brain’s neuron networks.1For more, see “Generative AI and the future of work in America,” McKinsey Global Institute, July 26, 2023 and The economic potential of generative AI: The next productivity frontier, McKinsey, June 14, 2023. This type of AI is called generative because of its capacity to create new content based on deep learning, or processing patterns and information from large amounts of data. One example is ChatGPT, which uses its data sourced from the internet to respond to questions and create a variety of written content—from poetry and stories to essays and computer code.2James Purtill, “How Australians are using ChatGPT and other generative AI in their everyday lives,” ABC Science, April 14, 2023.

Gen AI tools can also be used to generate graphics. Leonardo.Ai, developed by a North Sydney-based start-up, generates images and videos online from text prompts. In an interview for this report, cofounder J.J. Fiasson explains that Leonardo.Ai aims to help people to move quickly from idea to visual creation, an exercise which could otherwise take days or weeks. Users can input basic stick figures which the technology outputs as realistic drawings—for example, a line with some green dashes can be rendered into an oak tree.3“Leonardo.Ai accelerates global growth, generates 700 million AI images in less than a year on AWS,” Amazon media alert, November 27, 2023.

Despite many users interacting with these platforms for curiosity’s sake alone, gen AI nevertheless has the potential to perform an array of business-related functions—from product design to writing music and from customer service chatbots to assistance with scientific advancements. Still, gen AI’s early stage limitations require consideration to avoid unwanted legal, ethical, or plagiarism-related consequences. Human input and assessment, adequate monitoring, and awareness of possible inaccuracies are critical to ensure that gen AI is used responsibly.4“Generative AI and the future of work in America,” McKinsey Global Institute, July 26, 2023; The economic potential of generative AI: The next productivity frontier, McKinsey, June 14, 2023.

Half a decade later, a lot has changed—not least because of the profound shifts that the COVID-19 pandemic brought to the Australian economy. In 2023, generative AI (gen AI) emerged as a significant new force with the potential to reshape the future of work.2Insights from the first six months of JobKeeper, The Australian Government the Treasury, October 11, 2021; The economic potential of generative AI: The next productivity frontier, McKinsey, June 14, 2023. With its advanced natural language capabilities, gen AI could become ubiquitous, embedded into knowledge workers’ everyday tools (see sidebar, “What is generative AI?”). As gen AI continues to evolve through 2030, it could affect a more comprehensive set of work activities, transforming skills demand in Australia.

The acceleration of gen AI, alongside overlapping macroeconomic trends, prompted us to reexamine automation and the future of work. A new report by McKinsey, Generative AI and the future of work in Australia, aims to reflect what Australia’s mix of occupations could look like in 2030, including potential shifts in skills demand and how workers may need to reskill to stay productively employed and transition to new roles. This article explores some key findings from the report’s analysis.

The accelerated capabilities of machines

In 2019, the McKinsey Global Institute estimated that 44 percent of Australians’ time at work could be automated by adopting the technology of the time.3Australia’s automation opportunity: Reigniting productivity and inclusive income growth, McKinsey, March 3, 2019. In 2023, we revisited the topic to assess how the rapid emergence of gen AI has accelerated machines’ capabilities, finding that 62 percent of existing task hours could be automated using the technology available at the time of analysis. This potential could rise further to between 79 and 98 percent by 2030.

However, there could be a substantial time lag between technical potential and realized change—developing capabilities into technical solutions takes time, the cost of implementing solutions may exceed the cost of human labor, and the pace of adoption could be influenced by social or regulatory dynamics.

Accounting for these potential sources of friction, we modeled a series of adoption scenarios. While the early scenario suggests that just above 50 percent of activities could be automated by 2030, the late scenario could see just 2 percent in the same year. The midpoint of these scenarios would imply that around one-quarter of work hours could be automated by 2030. This is an eight percentage point acceleration with the inclusion of gen AI (Exhibit 1).4Based on a historical analysis of various technologies, we modeled a range of adoption timelines from eight to 27 years between the beginning of adoption and its plateau, using sigmoidal curves (S-curves). This range implicitly accounts for the many factors that could affect the pace at which adoption occurs, including regulation, levels of investment, and management decision making within companies.

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In a midpoint adoption scenario, every sector and occupation in Australia sees increases in automation, with associated potential for productivity gains. The introduction of gen AI has altered the adoption pattern observed in the 2019 report, Australia’s automation opportunity5Australia’s automation opportunity: Reigniting productivity and inclusive income growth, McKinsey, March 3, 2019.—automation is now rapidly encroaching on knowledge work, and the activities of white-collar workers, higher-wage roles, and workers in metropolitan areas. Automation adoption in educational services, professional, scientific, and technical services, and finance and insurance could see the most profound impact from gen AI (Exhibit 2).

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The new landscape of human work

Technology-driven shifts intersect with other macro factors, such as an aging population, the net-zero transition, and increased infrastructure spending. When these factors are combined, up to 1.3 million workers—9 percent of Australia’s total workforce—may need to transition out of their current roles into new occupations by 2030.6Here, 1.3 million transitions are distinct from regular employment churn within the economy. In this case, an individual would move into a different occupation from their current one, as opposed to current measures of churn where an individual may leave one business and go to another business to perform the same occupation.

When looking at future demand for jobs, and potential occupational transitions, three distinct occupational groups emerge:

  • Resilient and growing occupations include those in science and technology, healthcare, and professional services, which remained in demand during the pandemic. In this group, after automation, there could be net demand for 1.5 million additional jobs in 2022–30 and up to 210,000 required occupational transitions.
  • Stalled but rising occupations—building and mechanical installation and repair—saw downturns from 2019–22 related to the pandemic and global supply shortages.7Infrastructure beyond COVID-19—A national study on the impacts of the pandemic on Australia, Infrastructure Australia, December 16, 2020. Alongside growing infrastructure demand, job demand could increase by 290,000, with 200,000 occupational transitions.
  • Disrupted and declining occupations saw low growth or decline from 2019 to 2022 and are likely to continue to shrink, with up to 850,000 occupation transitions by 2030. Declining demand for jobs in office support, production work, food services, and customer service and sales could see almost 850,000 workers leaving their current occupations and finding jobs in different occupations (Exhibit 3).

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Understanding the nuances of these changes, and their potential impact on individuals and businesses, is crucial for a smoother transition. For instance, roles that are categorized within the lowest wage quintile and those without bachelor’s degree requirements are, respectively, 5.0 and 1.8 times more likely to experience occupational transitions than roles within the highest wage quintile and with higher education requirements. Women, who are underrepresented in jobs with growing demand, such as technology-related roles, and overrepresented in office support and customer service, are 1.2 times more likely to be affected by job transitions than men.8Australian Bureau of Statistics; McKinsey Global Institute analysis.

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Skill building may be a crucial tool to navigate a changing jobs landscape

Staying relevant in this rapidly changing environment could require workers to build new skills continuously. There could be greater demand for occupations requiring social, emotional, and technological skills, and relatively less demand for occupations requiring only basic cognitive skills by 2030.

Social and emotional skills, such as empathy, are often considered critical in healthcare and may continue to be paramount. However, with the increasing use of digital systems in healthcare delivery and the overall digitization of jobs and industries, healthcare workers may also need to build their digital skills.

Demand is anticipated to shrink for activities that primarily only require basic cognitive skills. The recurring, routine tasks in office support roles, for example, can often be completed by software and AI. Consequently, individuals could spend more time on higher-value work. For instance, retail employees could shift their focus from routine tasks, such as payment processing, to customer assistance—thereby delivering a superior customer experience.

Higher education could remain essential as demand increases in STEM, health, business, and legal professions. The need for bachelor’s degrees could grow by 17 percent by 2030, while tertiary and higher qualifications could make up about 2 percent more of the labor market. Still, about 60 percent of the labor market might not require a tertiary degree in 2030.

This continued and increasing demand for certain skill sets presents opportunities for upskilling and transitions to better-paid positions, which could rebalance the economy toward higher-wage jobs. More Australians could secure higher-paying positions—provided they have access to skills training and education.

Successful integration of automation and gen AI could boost the Australian economy and benefit businesses

Assuming all factors are in place, gen AI has the potential to increase Australian labor productivity by 0.1 to 1.1 percentage points a year through 2030.9We conservatively use the low and midpoint scenarios for these productivity numbers, given uncertainty concerning how productivity benefits will be captured. For both low and midpoint, we created two scenarios: a pessimistic scenario in which labor displaced by automation rejoins the workforce at 2022 productivity levels, and a more optimistic scenario in which it rejoins at 2030 productivity levels, net of automation. In both scenarios, we have incorporated labor displaced rejoining in line with the expected 2030 occupational mix. All other projections (such as, for example, jobs lost and jobs gained), are based on the midpoint adoption scenario. The range reflects a late and average speed of gen AI adoption, along with full-time equivalent hours released from deploying these technologies being redeployed back into the economy. Both scenarios account for the occupational mix expected in 2030. When we combine gen AI with all other automation technologies, the productivity growth could range from 0.2 to 4.1 percent a year in the late and midpoint adoption scenarios, respectively. But as a year-on-year increase of 4.1 percentage points would be up to four times greater than recent historical productivity growth levels, this potential is unlikely to be fully realized, especially as there could be significant transition costs and second-order effects (Exhibit 4).

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Despite headwinds such as an aging population, automation and gen AI offer opportunities. If Australia were to achieve even half of the potential productivity uplift, it could be on track to rekindle the faster economic growth of the post-1990s heyday. Enabling factors to help achieve this improvement include leaders who prioritize adoption, redesigned processes, effective change management, and strategies to ensure value capture from new efficiencies.

For the purposes of this research, we identified three sectors to bring to life how gen AI could transform the future of work in particular industries:

  • In retail trade, technology has the capability to introduce greater personalization, redefining the customer experience. Automation could improve inventory, back-office, and supply chain management, while gen AI could augment key functions such as customer service, and marketing and sales.
  • In financial services and insurance, gen AI adoption could reshape the way employees carry out risk assessments, fraud detection, software development, and customer service. Nearly one-third of task hours could be automated by 2030.
  • In the public sector, gen AI could transform activities such as education delivery, interactions with citizens, financial analysis, and R&D. In all these areas, productivity gains and improvements in accuracy and service could come as a result.
Generative AI and the future of work in Australia (5)

Gen AI and the future of work

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Considerations for employers, governments, and educators

It will not be a straightforward task for Australia’s stakeholders to realize the full benefits of automation and gen AI while ensuring that the coming transition in occupations and skills is well planned and fair.

Three main groups of stakeholders have an opportunity to take meaningful action:

Employers can consider the following questions to prepare for workforce evolution:

  • How will gen AI affect our competitive advantage and value proposition?
  • Do we have a strategic workforce plan that matches demand and supply with the capabilities we need?
  • How do we create sustainable value at scale?

Governments can help unlock the benefits of task augmentation and automation, providing a transparent regulatory framework and supporting those most vulnerable to role transitions. Government leaders can consider the following questions:

  • How can we create a simple, balanced regulatory environment?
  • How can governments support business adoption of automation?
  • How might we drive automation adoption in the public sector?
  • How can we encourage reskilling and provide a safety net for those transitioning to new roles?

Education institutions, supported in part by governments, can prepare to meet the evolving needs of employers and workers who are transitioning between occupations. Educators can consider the following questions:

  • How can we develop a more responsive and agile education system?
  • How can we leverage gen AI to improve outcomes through personalized learning?

Gen AI unlocks a future that may differ markedly from the present. Some people may fear the development, thinking it will negatively impact the way that we live and work. Others may embrace it, believing it will enhance productivity and help meet the needs of the planet and its people. Supporting an optimistic outlook, Australia’s economy has proved robust through challenging times, and shifts from gen AI could unlock benefits for Australia—including higher job demand and productivity. However, this potential may only be realized if employers, governments, and educators are able to adopt the technology in a bold and thoughtful way. Such strategic action could ensure that future generations of Australians benefit from the same prosperity that the country has experienced over the past three decades.

Chris Bradley is a director of the McKinsey Global Institute and a senior partner in McKinsey’s Sydney office, where Jules Carrigan is a senior partner and Seckin Ungur is a partner; Gurneet Singh Dandona is a senior expert in the New York office.

The authors wish to thank Juhi Daga, Jack Dalrymple, Lauren East, Andrew Goldberg, Sean O’Brien, Laura Scott, and Alok Singh for their contributions to this report.

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Generative AI and the future of work in Australia (2024)

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