Strategic positioning and distinctive characteristics
- Alignment with traditional strengths: Australia’s AI innovation is emerging organically from existing industrial capabilities rather than developing in isolation. It has high specialisation in sectors like specialised construction and chemical manufacturing.
- Dual‑track ecosystem: Australia shows a distinctive hybrid positioning as a developed 'AI‑taker’ and a developing ‘AI‑maker’. It balances global technology adoption with targeted domestic innovation in areas of competitive advantage.
- Research–industry alignment: Geographical alignment between research specialisations and regional industry strengths creates naturally specialised innovation corridors. These corridors allow academic expertise to directly enhance industrial capabilities.
- Evolutionary rather than revolutionary: Unlike global trends emphasising pure software or consumer technology disruption, Australia’s AI ecosystem has a more evolutionary approach that enhances and extends existing economic strengths.
Trends, patterns and specialisations in Australian AI businesses
- A sample of Australian AI companies: This report found a sample of 1,533 AI companies that contribute to Australia’s AI ecosystem, including 1,121 private companies and 412 public companies. Of the private businesses, 110 were new, founded in 2023 or 2024. While the sample does not fully capture all AI companies, it highlights the substantial and growing presence of AI businesses in the ecosystem.
- Adoption to innovation: The Australian AI ecosystem largely focuses on how to adopt and integrate AI to enhance existing processes. Businesses are increasingly transforming operations with AI in response to new opportunities and competitive dynamics. At the same time, a growing number of companies and research teams are developing proprietary AI tools, though much of the ecosystem remains reliant on globally developed foundation models.
- Concentrated urban clusters: Analysis found 25 distinct geographical clusters containing 858 AI companies (68% of geocoded firms). Melbourne’s central business district emerged as Australia’s largest AI cluster with 188 companies, followed by clusters in Sydney, Brisbane and Perth.
- Regional specialisation: Each major cluster shows distinctive specialisation patterns. Perth focusing on resource applications, Canberra on government and defence, and regional centres developing niche capabilities, like digital media in Maroochydore on Queensland’s Sunshine Coast.
- Complementary sectoral focus: Public AI companies primarily operate as adopters instead of developers. The strongest representation is in energy, raw materials and utilities (82 companies or 20% of public AI companies in our sample) and healthcare (77 companies or 19% of the public AI company sample). Private AI companies focus more on specialised innovation, concentrated in business processes (494 companies or 44% of the private AI company sample) and information technology (IT) infrastructure (346 companies or 31% of the private AI company sample).
- Small enterprise dominance: Small enterprises dominate our cohort of private AI businesses, with 85% of companies employing fewer than 50 staff. This creates a vibrant but potentially fragile innovation ecosystem.
AI research and product innovation patterns
- Rapid expansion in research and development (R&D): Australia’s AI ecosystem is experiencing significant growth, with AI‑related patents nearly quadrupling from 170 in 2015 to 629 in 2024. Over the same period, AI‑related research publications more than doubled.
- Research output growth: Australia’s AI research output grew from 5.3% of total scholarly publications in 2015 to 11.6% in 2024. This indicates an increasing prioritisation of AI research in the national innovation agenda.
- Through the global AI surge: Despite strong absolute growth in AI publications, Australia’s share of global output declined from 2.6% in 2015 to 1.9% in 2024. This trend reflects the extraordinary global expansion of AI research – rising 218% from 206,160 publications in 2015 to 655,454 in 2024 – rather than a decline in Australia’s productivity.
- Distinctive research strengths: Australia shows unique research specialisations in AI, with particularly strong specialisation in veterinary science, arts and humanities, and dentistry, indicating distinctive national capabilities.
- Multidisciplinary integration: AI methods have penetrated diverse research disciplines beyond computer science (18% of AI publications) and medicine (16%), extending to environmental, agricultural and social sciences.
- Manufacturing‑led patenting: Ten manufacturing industries appear in the top 15 patenting sectors showing strong orientation toward enhancing traditional industries.
- Knowledge‑to‑commercial gap: Despite robust research output (93,302 AI‑related publications between 2015 and 2024), Australia shows a significant gap in commercialisation. While the number of AI patents has grown, it remains low, with only 4,075 patents filed over the same period. This equates to nearly 23 research publications for every patent highlighting a disconnect between research activity and commercial outcomes.
- Resilient growth trajectory: Despite global economic fluctuations, including the COVID‑19 pandemic, Australia’s AI R&D activities maintained consistent growth in both research output and patent applications, showing the ecosystem’s resilience.
Dynamics of the AI skills and labour market
- Recruitment drive: In 2024, 1,532 organisations (3.8% of hiring organisations) sought workers with AI‑related skills, up from 483 organisations (2.7%) in 2015.
- Growing skills demand: Requirements for technical AI‑related skills have increased across all industries, rising from 0.2% of job postings in 2015 to 0.9% in 2024.
- Concentrated hiring patterns: AI hiring remains disproportionately concentrated, with 100 companies accounting for 58% of all AI job postings. Additionally inner Sydney, Melbourne, Brisbane and Perth accounted for 64% of position locations.
- Diverse skill requirements: AI‑related job postings frequently mention both technical capabilities (machine learning, programming languages, mathematics) and broader skills (communication, management, leadership), indicating the need for multifaceted talent.
- Emerging work clusters: We found 8 distinct clusters of AI‑related work. This includes business analytics, industrial process optimisation, scientific research, medical diagnosis, and training generative AI models, showing AI’s integration across economic sectors.
The data compiled in this report tell a story of a rapidly expanding AI ecosystem with more skilled workers, more companies and greater intensity of R&D activity. Australia’s AI ecosystem includes companies involved in building AI tools and models. However, its main strength lies in intelligently applying these powerful technologies to create practical business value across different sectors.