Opinion article

How Australia’s skills will evolve with Generative AI

As GenAI revolutionises industries worldwide, the critical question arises: How can Australia optimise AI to bridge the skills gap and adapt to the evolving jobs landscape? 

The recent surge in Generative AI (GenAI) adoption in the workplace underscores the technology’s pivotal role in driving productivity growth globally. Microsoft and LinkedIn’s latest 2024 Work Trend Index reveals that AI is significantly changing the workplace, with 84 per cent of knowledge workers in Australia already using AI at work. 

Amidst this trend, Australia, like many advanced economies, continues to grapple with a widespread skills shortage, with hopes that AI may help alleviate some of this shortfall.

As GenAI revolutionises industries worldwide, the critical question arises: How can Australia optimise AI to bridge the skills gap and adapt to the evolving jobs landscape?

Although the net impact of GenAI on the labour market remains uncertain, one thing is clear: there will be a significant shift in the skills required for many jobs. LinkedIn’s Skills-First Report previously found the skill sets required for jobs have changed significantly since 2015, and with AI accelerating this trend, jobs are expected to change as much as 68 per cent by 2030. 

Recent research by LinkedIn and Mandala, using LinkedIn data covering more than 41,000 skills and 15 million Australian members, indicates that GenAI will affect the skills composition for approximately 7.2 million Australian workers.

The magnitude of this transition underscores the necessity for policymakers, companies and workers to realign their strategic approaches, particularly in planning for skills acquisition, exploring diverse educational pathways and ensuring equitable employment opportunities. 

Fortunately, unlike previous technological revolutions, we now have the advantage of using data and analysis to gain a deeper understanding of this transition's implications by adopting a ‘skills-first’ approach. By focusing on skills rather than degrees or job titles, organisations can not only access a wider array of candidates to help fill the skills gap, but also learn how existing roles will evolve with GenAI.

The impact on job roles and skills

To understand the effects of GenAI on job roles, it is essential to examine its potential impact on the required skills composition. Any impacted skills could be grouped as either GenAI-replicable or GenAI-complementary skills. Job roles could then be mapped into three categories: 

  • Augmented Jobs, where the core skills required include large shares of both GenAI-replicable and GenAI-complementary skills; 
  • Disrupted Jobs, which include a large share of GenAI-replicable skills and a relatively low share of GenAI-complementary skills; and
  • Insulated Jobs, which are relatively insulated from GenAI, having a small proportion of GenAI-replicable core skills.

Jobs requiring specialised service skills, such as those of healthcare professionals, are typically insulated from GenAI due to their reliance on human interaction. In contrast, positions in sectors like financial and insurance services, which involve a large proportion of GenAI-replicable skills, are more susceptible to disruption.

Notably, the effects of GenAI will not be uniformly distributed across the workforce. Professionals, women, younger workers and those with tertiary education are more likely to experience either augmentation or disruption.

Demographic impacts of GenAI on labour market opportunities

Women face greater GenAI disruption (around six percentage points difference) compared with men, which may be primarily due to occupational gender segregation. Women tend to be overrepresented in roles more susceptible to disruption by generative AI, such as Medical Administrative Assistant and Legal Assistant, whereas men are overrepresented in roles potentially augmented by generative AI, such as Electrical and Mechanical Engineer. 

Despite similar concerns about AI changes, men are 1.4 times more likely to express an interest in learning AI skills. Gender equity investments in managerial changes, training and business processes will be critical, so that women don’t fall further behind. 

In this adapted environment, soft skills are in high demand – women have a 28 per cent higher share of soft skills listed on LinkedIn, such as team leadership, strategic leadership, and collaboration, suggesting an opportunity to help close the gender gap.

Gen Z faces the highest disruption and a 15 per cent greater impact from GenAI compared with Baby Boomers. This is due to their predominance in entry-level roles that require GenAI-replicable skills, which are highly susceptible to AI disruption. Conversely, Baby Boomers tend to occupy senior positions that require GenAI-complementary skills, where they can leverage their extensive experience, thus facing lower susceptibility to AI disruption. 

Despite this discrepancy, younger workers benefit from a higher likelihood of having AI literacy and a longer career ahead of them, enabling them to upskill through new pathways and adapt to emerging technologies more effectively.

Workers in Australia holding Bachelor's degrees or higher are more likely to be impacted by GenAI compared to those with Associate's degrees. This trend indicates a shift in the dynamics of technological disruption, where new technology is now impacting higher-skilled positions. Unlike prior technological shifts that mainly affected lower-paid jobs, GenAI is poised to significantly affect some of the most skilled and highest-paid positions, prompting further skilling in GenAI-complementary skills.

As Australia grapples with the challenges and opportunities of GenAI, prioritising a skills-first approach will become paramount. Understanding this approach will be essential for closing the national skills gap and fostering equitable opportunities in employment and education. 

These nuanced insights provide a glimpse into the evolution of Australia's skills, laying the groundwork for a seamless transition to an AI-driven economy.

About the authors
AL

Audrey Lobo-Pulo

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Audrey is LinkedIn's Head of Public Policy and Economic Graph for Australia and New Zealand.