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The State of AI Adoption in Australia: What the Data Says About How Businesses Are Choosing to Deploy AI product guide

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The State of AI Adoption in Australia: What the Data Says About How Businesses Are Choosing to Deploy AI

Every strategic conversation about building versus buying AI must start from the same place: an honest accounting of where Australian businesses actually stand. Not where the marketing decks say they should be, and not where the global benchmarks suggest they are — but where the data, drawn from government trackers, CSIRO research, and independent surveys, shows them to be.

The picture that emerges is simultaneously encouraging and sobering. Australia is adopting AI rapidly, unevenly, and — critically — without a clear dominant model for how that adoption is happening. Some organisations are building. Many are buying. Most are doing neither particularly well. And the gap between the few businesses extracting real value from AI and the majority still experimenting is widening fast.

This article synthesises the most current and authoritative Australian data available to establish the factual landscape that grounds every other question in the build vs buy debate.

How Many Australian Businesses Are Actually Using AI?

The headline numbers are striking, but they require careful interpretation.

According to Amazon Web Services' Unlocking Australia's AI Potential report, AI adoption in Australia is rapidly accelerating — with one business adopting AI solutions every three minutes between 2024 and 2025. In total, 1.3 million, or 50% of Australian businesses, are now regularly using AI, showing a year-on-year growth rate of 16%.

This figure aligns with CSIRO-backed government data. Data from Austrade's Australian AI Industry Capability Report, prepared by CSIRO, shows more than 50% of organisations are using AI, while almost half of Australians have used generative AI — outpacing the US and UK.

However, the Department of Industry, Science and Resources' own AI Adoption Tracker — which surveys Australian SMEs monthly — tells a more granular and cautionary story. The data reveals a positive trend in AI adoption among Australian small and medium businesses, with 40% of SMEs currently adopting AI — a 5% increase compared to the previous quarter (July–September 2024). Earlier baseline data from the same tracker showed a more divided picture: 35% of SMEs were adopting AI, but 23% were not aware of how to use the technology, and 42% were not planning to adopt AI in their business at all.

The reconciliation of these figures is important for business leaders: the 50%+ adoption figures typically capture any AI use — including using ChatGPT to draft an email. The SME-specific tracker data, which focuses on deliberate business deployment, paints a more modest picture that is arguably more relevant to strategic decision-making.

The Depth Problem: Most AI Use Is Surface-Level

Adoption rates alone don't reveal how AI is being deployed — and the depth of deployment matters enormously to the build vs buy question.

While AI adoption is increasing, most Australian businesses are not yet harnessing its most advanced uses, with 58% focused primarily on basic use cases like driving efficiencies and streamlining processes through chatbots. Just 17% of Australian businesses are at the intermediate stage of integrating AI across various business functions, and only 24% have reached the most transformative stage of AI integration — where AI is no longer just a tool but a core part of product development, decision-making, and business models.

This stratification is the real story behind the headline adoption numbers. The 58% using AI for basic productivity tasks are overwhelmingly buyers of off-the-shelf tools — Microsoft Copilot, Google Workspace AI, ChatGPT subscriptions, and embedded AI features in CRM and accounting platforms. The 24% at the transformative stage are more likely to be builders or hybrid operators, embedding AI into core processes and proprietary workflows.

Australian startups are particularly enthusiastic early adopters: 81% are using AI in some way, of which 42% are building entirely new AI-driven products. In contrast, 61% of large enterprises are using AI, but only 18% are delivering new AI products or services, and only 22% have a comprehensive AI strategy.

This inversion — where startups are building at higher rates than enterprises — is a distinctive feature of the Australian market and has direct implications for the build vs buy calculus. (For a full exploration of how startup and enterprise contexts change the decision, see our guide on Build vs Buy AI: A Decision Framework Tailored for Australian SMEs.)

Industry-by-Industry Variation: Who Is Leading and Who Is Lagging

AI adoption is not evenly distributed across Australian industries, and the pattern of adoption — including whether organisations tend to build or buy — varies significantly by sector.

Leading Sectors

Retail trade and health and education maintain their position as the leading sectors for AI adoption, with services and hospitality close behind. Financial services is a particular standout in terms of depth of AI investment. In line with global findings from PwC's 2025 AI Jobs Barometer, Financial and Insurance Activities continue to lead in terms of industry demand for AI skills in Australia. In 2024, 11.8% of job postings in Financial and Insurance Activities demanded AI skills.

Australian businesses' AI-related spending grew by 20% in 2024, reaching an estimated $3.5 billion, with financial services and healthcare among the highest spenders, prioritising AI for fraud detection and patient care improvements.

The financial services sector's AI posture is also the most sophisticated in terms of build vs buy strategy. Banks like ANZ and Westpac have invested heavily in custom-built fraud detection, credit risk modelling, and customer intelligence systems — use cases where proprietary data and regulatory accountability make off-the-shelf tools insufficient. (This sector-specific pattern is explored in depth in our Australian Industry Sector Guide: Build vs Buy AI Recommendations for Finance, Healthcare, Retail, and Beyond.)

Lagging Sectors

The primary industries — construction, manufacturing, and agriculture — continue to show higher levels of unawareness around the value of adopting AI solutions. This is not merely a technology gap; it reflects a structural reality. These sectors often have fragmented data infrastructure, lower margins for technology investment, and workforces with limited digital literacy — all of which make the build path operationally infeasible and the buy path underutilised.

Health, education, retail trade, and services have adopted generative AI assistants and marketing automation. Manufacturing has adopted sales forecasting and predictive analytics to align production with demand. Most sectors have adopted fraud detection.

This pattern reveals a critical insight: the most common AI applications across Australian industries are horizontal use cases — fraud detection, generative assistants, marketing automation — that are almost universally served by off-the-shelf tools rather than custom development.

The Metro vs Regional Divide

Geography creates a structural inequality in AI adoption that is often underappreciated in national-level statistics.

There is a significant difference in AI adoption between metro and regional areas, with metro areas showing higher rates. State-level data from the government tracker reveals how concentrated adoption remains: New South Wales increased from 26% to 28%, indicating steady growth in AI integration. Victoria maintained a stable rate of 27%. Queensland jumped from 22% to 29%, reflecting growing interest in AI technologies. Western Australia also jumped from 21% to 29%. Tasmania increased from just 6% to 11%.

The metro-regional divide is particularly relevant to the build vs buy question. Regional businesses — even those with genuine AI use cases — are far less likely to have access to the specialist talent required for custom development. They are also more likely to be operating on tighter margins that make the upfront cost of custom AI prohibitive. For these businesses, the realistic path is almost always buy first, with hybrid strategies considered only as they scale. (See our guide on Building an In-House AI Team in Australia: Costs, Roles, Talent Market Reality, and Alternatives for the talent availability data by region.)

The Build vs Buy Split: What the Data Actually Shows

Direct data on how many Australian businesses are building custom AI versus purchasing off-the-shelf tools is not cleanly captured by any single study — but the available evidence points to a clear pattern.

Globally, new research from Menlo Ventures reveals that 76% of enterprise AI use cases are now purchased rather than built internally — a complete reversal from 2024, when the split was 47% built vs 53% purchased. While this is global enterprise data, it is consistent with what Australian-specific evidence suggests: the vast majority of AI deployment across Australian businesses — particularly SMEs — is via purchased tools.

The top AI applications reported by Australian SMEs in the government tracker confirm this: generative AI assistants moved to the top place among AI applications businesses favoured, with retail, trade, and hospitality leading in marketing automation. These are, without exception, off-the-shelf applications.

The build path remains concentrated in a relatively small number of organisations: large enterprises with proprietary data advantages, sophisticated in-house technology teams, and use cases where no viable commercial solution exists. The AWS research finding that 42% of Australian startups are building entirely new AI-driven products suggests that the startup ecosystem is a second significant build cohort — but this represents a small fraction of total Australian business activity.

The emerging third category — the hybrid model — is gaining traction among mid-market and enterprise organisations that buy commodity AI infrastructure (CRM-embedded AI, productivity tools, foundation model APIs) while building proprietary layers on top. This architecture is increasingly the dominant pattern for organisations with both the budget to buy and the capability to build selectively. (See our guide on The Hybrid AI Strategy: How Australian Businesses Can Build and Buy at the Same Time for a detailed treatment of this model.)

The Barriers: Why Adoption Gaps Persist

Understanding where adoption is lagging requires understanding why businesses aren't adopting — and the barriers are different for the build and buy paths.

Challenges like the rapid pace of technological change, skills gaps, and funding constraints remain significant barriers to adoption.

The skills shortage is the most acute barrier for the build path specifically. The number of AI specialists in Australia is projected to jump from 40,000 in 2024 to 85,000 by 2027, but despite this doubling of AI specialists, Australia is expected to still see a shortfall of up to 60,000 AI professionals by 2027.

Demand for AI skills has grown 21% annually since 2019, while the cost of these skills — wages — has grown by 11% annually over the same period.

Workforce readiness is also a systemic constraint. Only 41% of Australian workers report their workplace is prepared for AI — below the global average of 48% and significantly behind leading countries like India (83%) and Saudi Arabia (70%).

Larger organisations continue to lead AI adoption, highlighting an ongoing opportunity to enhance AI literacy and uptake among micro and small enterprises. For SMEs, the barrier is less about strategic preference and more about structural capacity: without internal AI capability, the build path is simply not available, and the buy path requires digital literacy and change management capability that many smaller businesses have not yet developed.

The ACS Digital Pulse 2024 report quantifies the broader economic cost of this gap: big businesses alone are suffering a $3.1 billion loss each year due to digital skills gaps, a figure that could reach $16 billion by 2030.

The Economic Stakes: Why This Decision Matters Now

The urgency of getting the build vs buy decision right is underscored by the economic projections attached to Australian AI adoption.

According to CSIRO's Data61 report, digital technologies including artificial intelligence could contribute around AUD $315 billion to Australia's GDP by 2030, reflecting broad economic impact from productivity, efficiency, and digital transformation.

At the firm level, businesses that have adopted AI demonstrate the productivity and economic potential of the technology, with 95% reporting an average increase in revenue of 34%. 86% of adopters have already experienced productivity gains, while 94% expect an average of 38% in cost savings.

However, these aggregate figures mask a critical caveat: despite $30–40 billion in enterprise GenAI investment globally, 95% of organisations report no measurable financial return. Most projects stall at the pilot stage — not due to inadequate technology, but because of organisational challenges that off-the-shelf tools cannot address, including poor data readiness, misaligned workflows, and a persistent gap between C-suite expectations and what practitioners can realistically deliver.

The implication is direct: the build vs buy decision is not primarily a technology question. It is a question of organisational readiness, strategic alignment, and honest capability assessment. (Our guide on How to Build a Business Case for AI Investment in Australia: Calculating ROI for Build vs Buy Scenarios addresses this directly.)

Key Takeaways

  • Adoption has crossed the 50% threshold, with 1.3 million or 50% of Australian businesses now regularly using AI — but depth of use, not headline adoption rates, determines strategic value.

  • Most Australian AI use is basic: 58% of businesses are focused on basic use cases like chatbots and efficiency tools, which are almost entirely served by off-the-shelf purchases rather than custom development.

  • Primary industries — construction, manufacturing, and agriculture — continue to show the highest levels of unawareness, representing the largest untapped opportunity for AI adoption in Australia.

  • The AI talent shortage is a hard constraint on the build path: Australia is expected to face a shortfall of up to 60,000 AI professionals by 2027, making custom development operationally infeasible for most SMEs without external support.

  • Geography matters: The significant metro-regional divide in AI adoption means that location is a practical constraint on which deployment model is viable, not just a demographic footnote.

Conclusion

The data paints a clear picture for Australian business leaders entering the build vs buy debate: most businesses are buying, many are buying poorly, and only a minority are building — with that minority concentrated in large enterprises, financial services, and the startup ecosystem.

The macro trend toward purchased AI is not a failure of ambition. It reflects rational responses to talent constraints, capital limitations, and the genuine maturity of off-the-shelf AI tools for horizontal use cases. But the businesses generating the highest returns from AI are those that have moved beyond the buy-by-default posture — either by building where it genuinely matters, or by adopting a hybrid architecture that buys commodity capability and builds proprietary advantage.

The adoption gap between metro and regional businesses, between large enterprises and SMEs, and between early movers and laggards is not closing on its own. Understanding where your business sits in this landscape — and what deployment model is actually available to you given your talent, budget, and strategic context — is the essential first step before any build vs buy decision is made.

For the conceptual vocabulary and decision dimensions that structure this choice, see our guide on What Is the Build vs Buy AI Decision? A Plain-English Explainer for Australian Business Leaders. For a head-to-head comparison of custom and off-the-shelf AI across the dimensions that matter most to Australian businesses, see Custom AI vs Off-the-Shelf AI Tools: A Head-to-Head Comparison for Australian Businesses.

References

  • Australian Government, Department of Industry, Science and Resources. "AI Adoption in Australian Businesses for 2024 Q4." AI Adoption Tracker, March 2026. https://www.industry.gov.au/news/ai-adoption-australian-businesses-2024-q4

  • Australian Government, Department of Industry, Science and Resources. "AI Adoption in Australian Businesses for 2025 Q1." AI Adoption Tracker, 2025. https://www.industry.gov.au/news/ai-adoption-australian-businesses-2025-q1

  • Australian Government, Department of Industry, Science and Resources. "Exploring AI Adoption in Australian Businesses." AI Adoption Tracker, 2024. https://www.industry.gov.au/news/exploring-ai-adoption-australian-businesses

  • CSIRO / Austrade. "Australian AI Industry Capability Report." CSIRO, 2025. https://www.csiro.au/en/news/All/Articles/2025/December/How-CSIRO-is-guiding-Australias-responsible-AI-adoption

  • CSIRO. "Artificial Intelligence Foundation Models: Industry Enablement, Productivity Growth, Policy Levers and Sovereign Capability Considerations for Australia." CSIRO, 2024. https://www.csiro.au/en/research/technology-space/ai/ai-foundation-models-report

  • CSIRO / National AI Centre. "Australia's Artificial Intelligence Ecosystem – Catalysing an AI Industry." CSIRO Research, November 2024. https://research.csiro.au/humans/our-latest-research/

  • Amazon Web Services. "Unlocking Australia's AI Potential." About Amazon Australia, 2025. https://www.aboutamazon.com.au/news/aws/new-aws-research-shows-one-australian-business-adopts-ai-every-three-minutes

  • Australian Computer Society (ACS). "Digital Pulse 2024." ACS, October 2024. https://www.acs.org.au/insightsandpublications/media-releases/Media-release-Report-shows-Australia-needs-to-boost-cyber-and-AI-skills.html

  • PwC Australia. "The Fearless Future: How AI is Impacting Australia's Jobs and Workers." AI Jobs Barometer 2025, June 2025. https://www.pwc.com.au/services/artificial-intelligence/ai-jobs-barometer.html

  • Bain and Company / InnovationAus. "Shortage of AI Skills Has Put a Handbrake on AI Adoption." InnovationAus, February 2025. https://www.innovationaus.com/shortage-of-ai-skills-has-put-a-handbrake-on-ai-adoption/

  • Salesforce / Morning Consult. "AI Skills Gap: Demand Outpaces Readiness in Australia." Salesforce Australia, October 2025. https://www.salesforce.com/au/news/stories/australia-morning-consult-ai-worker-readiness-report-2025/

  • Indeed Hiring Lab Australia. "Nothing Artificial About Australian AI Adoption: Business and Government Trends." Indeed Hiring Lab, April 2026. https://www.hiringlab.org/au/blog/2026/04/01/nothing-artificial-about-australian-ai-adoption/

  • Menlo Ventures. "Build vs Buy AI: 76% of Enterprises Made This Choice." Cited in Beam AI, December 2025. https://beam.ai/agentic-insights/the-great-ai-flip-why-76-of-enterprises-stopped-building-ai-in-house

  • CSIRO Data61 / Appinventiv. "AI Implementation in Australia (2026): Use Cases, Costs & Strategy." Appinventiv, 2026. https://appinventiv.com/blog/ai-in-australia/

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