Unveiling the Jobs and Skills Australia Generative AI Capacity Study

The Generative Artificial Intelligence (Gen AI) Capacity Study, released by Jobs and Skills Australia on 14 August 2025, marks the nation's first comprehensive, whole-of-labour-market analysis of Gen AI's potential impacts. Commissioned to guide policymakers, educators, and employers through the evolving digital landscape, this landmark report titled "Our Gen AI Transition: Implications for Work and Skills" draws on task-level assessments across all occupations using the Australian and New Zealand Standard Classification of Occupations (ANZSCO). It addresses widespread worker anxieties about job displacement by emphasizing augmentation—where AI enhances human capabilities—over outright automation.

In the context of Australian higher education, where academics, lecturers, researchers, and administrative staff juggle teaching, research, and service duties, the study offers timely reassurance. Universities like the University of Sydney and RMIT are already experimenting with Gen AI for curriculum design and research support, positioning higher ed as a sector ripe for productive integration rather than disruption. This report synthesizes data from interactive tools, case studies, and economic modeling to forecast a future where AI boosts productivity without mass layoffs.

Core Framework: Measuring Exposure to Gen AI

The study's exposure framework adapts methodologies from the International Labour Organization (ILO), scoring each occupational task on two axes: augmentability (how much Gen AI can enhance performance, scored 0-1) and automatability (likelihood of replacement, also 0-1). Aggregate scores reveal that across Australia's 13 million-strong workforce, augmentation potential significantly outpaces automation risks. For instance, only 21% of workers are in roles with medium-to-high automatability exposure, while up to 79% face minimal changes, with Gen AI handling just small, routine portions of their duties.

Higher education exemplifies this balance. Tasks like lesson planning, data analysis in research, and report drafting score high on augmentation but low on full automation, as human judgment remains irreplaceable. The report's interactive higher education data explorer highlights discipline-specific exposures: humanities and social sciences show moderate augmentation for writing-intensive roles, while STEM fields benefit from AI in simulations and coding assistance.

Sectors and Occupations: Winners and Low-Risk Areas

Gen AI's reach varies sharply by industry. Administrative and clerical roles—data entry clerks, receptionists, and accountants—top the vulnerability list, with high automatability due to repetitive tasks. Conversely, hands-on professions like tradespeople (plumbers, electricians), nurses, and cleaners exhibit the lowest exposure, as physical dexterity and empathy defy current AI capabilities.

In higher education, administrative support staff may see efficiencies in scheduling and record-keeping, but core academic roles fare well:

• University Lecturers and Tutors: Augmentation in preparing slides and quizzes (up to 30% task time savings), but irreplaceable in student mentoring and interactive seminars.
• Research Scientists: AI accelerates literature reviews and hypothesis generation, potentially doubling output without job losses.
• Academic Administrators: Automation of compliance reporting frees time for strategic planning.

The report notes early adoption in professional services (25% usage rate), contrasting with slower uptake in manual sectors.

Higher Education Spotlight: Case Studies from Australian Universities

Real-world examples from the study's case studies illuminate Gen AI's role in unis. One non-market sector initiative involved co-designing AI tools for assessments, where educators at an unnamed Australian university collaborated with students on a homegrown platform. This hybrid approach maintained academic integrity while enhancing feedback loops—lecturers reported 40% faster grading without compromising quality.

Another case from tech-adjacent higher ed roles showed AI-powered matching tools accelerating skills-based hiring for research assistants, reducing time-to-hire by 50%. These narratives underscore a shift from fear to opportunity, with universities like Monash and Curtin leading pilots in AI literacy integration. For job seekers eyeing research assistant positions, this signals new pathways blending human insight with AI efficiency.

Adoption Trends and Current Realities in Australia

Adoption remains nascent: only 15-20% of Australian workers report regular Gen AI use, skewed toward professionals, women, youth, and tertiary-educated cohorts—precisely higher ed demographics. Shadow AI—unauthorized personal use—is rife, with surveys indicating 30% of office workers experimenting covertly due to unclear policies.

In universities, uptake is higher in research (e.g., ChatGPT for grant writing drafts) but cautious in teaching amid academic honesty debates. The Digital Transformation Agency's trials inform government-wide guidelines, stressing ethical deployment. This gradual rollout mitigates risks, allowing time for upskilling via platforms like higher ed career advice resources.

Skills Imperative: Upskilling for the Gen AI Era

The study identifies surging demand for AI literacy, prompt engineering, critical evaluation of AI outputs, and ethical reasoning—skills amplifying human strengths. Higher ed graduates enter exposed fields, necessitating curriculum reforms: 78% work in Gen AI-influenced roles per VET and higher ed analysis.

• Short-term: Micro-credentials in AI augmentation for lecturers.
• Medium-term: Embed Gen AI in degree programs, as at University of Queensland.
• Long-term: Lifelong learning hubs partnering with higher ed jobs platforms.

Government recommendations urge targeted training investments, projecting 7.2 million workers needing reskilling—50% of the workforce.

Stakeholder Perspectives: From Fear to Optimism

Workers' concerns linger—38% of youth fear displacement—but experts like those at Engineers Australia highlight benefits outweighing risks. University vice-chancellors advocate balanced policies, citing RMIT's Professor in Generative AI role as evidence of job creation. Employers report productivity gains (20-30% in pilots), while unions push for safeguards.

A balanced view emerges: Gen AI as a tool for equity, aiding diverse learners in higher ed without supplanting educators. Recent polls show 60% of academics optimistic post-study release.

Policy Pathways and Future Outlook

Jobs and Skills Australia proposes a national AI skills accelerator, ethical frameworks, and monitoring dashboards. By 2030, Gen AI could add billions to GDP via productivity, with higher ed pivotal in talent pipelines.

Challenges persist: uneven regional adoption (urban vs rural unis), bias mitigation, and infrastructure gaps. Yet, the trajectory reassures: net job growth in AI-related fields, like 1,500+ organizations seeking AI skills in 2024.

Photo by Amanda Jones on Unsplash

Actionable Insights for Higher Ed Professionals

For lecturers eyeing stability, focus on lecturer jobs with AI integration; researchers, leverage tools for faster publications. Job hunters: build AI portfolios via free resume templates. Institutions: invest in training to retain talent.

This study dispels doomsday scenarios, charting a collaborative future. Explore opportunities at Australian academic jobs amid this transition.

In summary, generative AI job security in Australia looks solid, especially in higher education, where human-centric roles thrive alongside tech.