Depending on which survey you read, somewhere between 37 and 68 per cent of Australian businesses have adopted artificial intelligence. The Tech Council of Australia says AI is adding $21 billion annually to GDP and could reach $142 billion by 2030. The CSIRO puts adoption at 68 per cent. The National AI Centre, tracking through monthly surveys of 400 SMEs, puts the figure at 37 per cent. MYOB's Bi-Annual Business Monitor says 29 per cent of SMEs are using AI tools, up from 23 per cent six months earlier.
The variation in those numbers tells you something important. When surveys cannot agree on how many businesses are even using AI, the chances of finding clean evidence that it is driving revenue growth are slim.
And that is exactly what the data shows. AI adoption in Australian SMEs is accelerating. Evidence that it translates to measurable revenue improvement is thin.
This is not an argument against AI. It is an argument for honesty about what the data actually supports, and what business owners should realistically expect from their investment.
The wide range in reported adoption rates comes down to definition. What counts as "adopting AI" varies enormously across surveys.
The CSIRO's figure of 68 per cent covers all Australian businesses and uses a broad definition that includes any form of AI or machine learning integration. The Department of Industry's June 2025 analysis synthesised multiple sources and concluded that "large enterprises have broadly embraced AI" while "approximately one-third of SMEs" have adopted it. The AiGroup put the figure at 52 per cent across all business sizes.
The National AI Centre's Adoption Tracker, run through Fifth Quadrant with 400 different SMEs responding each month, provides the most granular SME-specific data at 37 per cent. MYOB's figure of 29 per cent comes from a survey of 1,087 Australian SMEs and specifically asks about AI tool usage.
The MYOB data is arguably the most relevant for small and medium business owners. It captures businesses with fewer than 200 employees and asks about actual tool usage rather than general "adoption."
Within that 29 per cent, the breakdown by age group is notable. Generation Y business owners report 45 per cent adoption. Baby Boomers report 20 per cent. Start-ups show 38 per cent digital tool adoption broadly, compared to lower figures for established businesses.
Only 7 per cent of SMEs have integrated AI into their products or services, down from 9 per cent in the previous period. The vast majority of AI use among SMEs is for internal processes, not client-facing applications.
The MYOB data provides the most useful breakdown of how businesses perceive AI's impact on their operations.
Of SMEs using AI tools, 82 per cent reported a positive impact, up from 78 per cent in the prior survey period. That sounds compelling until you look at how they are measuring it.
Some 46 per cent of businesses using AI do not measure its impact at all. Of those 46 per cent, 74 per cent said measurement was "unnecessary." Among those that do measure, the most common method is checking whether objectives were met (21 per cent), followed by revenue per employee (18 per cent).
The average productivity rating businesses gave their AI tools was 6.3 out of 10. Agriculture rated highest at 6.9. Retail and hospitality rated lowest at 5.5.
These are self-reported assessments, not measured outcomes. An 82 per cent positive perception with 46 per cent not measuring anything means roughly 38 per cent of AI-using businesses are reporting positive impact without any measurement framework to support the claim.
This does not mean AI is not helping those businesses. It means the evidence base is built on perception rather than data.
If you are looking for a sector where technology adoption has produced measurable productivity outcomes, agriculture is the strongest example in the Australian data.
The MYOB SME Performance Indicator for Q2 2025 identified agriculture as the standout sector, with activity growth of 13 per cent. Mining and public administration also performed strongly. At the same time, agricultural employment has fallen from approximately 360,000 to 300,000 over five years, a reduction of roughly 17 per cent.
Technology adoption, including automation, precision agriculture, and data-driven decision-making, has been cited as a key driver of this productivity gain. The sector is producing significantly more output with fewer people.
This is a genuine technology-to-productivity story. But there are two important caveats.
First, the technology driving agricultural productivity is largely automation and sensor technology, not AI in the way most SME owners understand it (chatbots, content generation, data analysis tools). The lessons from agriculture are about capital-intensive technology substitution for labour, which is a fundamentally different proposition for a services business.
Second, the productivity gain came alongside significant job losses. For an SME owner in professional services, construction, or retail, the question is not just whether AI can improve productivity but what that means for their team and operating model.
One of the most commercially relevant findings across the data is the gap between mid-market businesses and smaller enterprises.
MYOB's Mid-Market Survey from October 2025, covering 506 businesses, found that 34 per cent were prioritising AI investment over the next five years, 44 per cent were planning CRM upgrades, and 48 per cent cited operational efficiency as the main driver of technology investment.
The performance gap between these mid-market businesses and smaller firms is significant. Some 52 per cent of mid-market businesses reported revenue growth, compared to 22 per cent of smaller businesses. Profitability improvement was reported by 56 per cent of mid-market respondents. Economic confidence was higher, with 57 per cent expecting improvement.
It is tempting to draw a line between higher AI adoption and better financial performance. The mid-market data would seem to support it. But the correlation runs through a confounding variable: resources.
Mid-market businesses have more staff, more capital, more management capability, and more operational infrastructure. They are better positioned to select, implement, and extract value from any technology investment, not just AI. A business with a dedicated IT function, defined processes, and management reporting will get more from an AI tool than a business where the owner is doing the bookkeeping at 10pm.
The implication is not that smaller businesses should avoid AI. It is that AI without operational maturity does not deliver. The businesses seeing measurable results are the ones with the infrastructure to measure results in the first place.
The most frequently cited figure in Australian AI coverage is the Tech Council of Australia's projection that AI could add $142 billion annually to GDP by 2030, with SMEs projected to achieve 22 per cent faster productivity growth than large firms over 2025 to 2030.
A disclosure that matters here: this projection comes from "Australia's AI Opportunities Report," which was commissioned and funded by OpenAI. The research was conducted in partnership with the Tech Council, but the primary funding came from a company with a direct commercial interest in widespread AI adoption. This does not necessarily invalidate the findings, but it is context that is frequently omitted from media coverage and that readers should have when evaluating the projection.
The report also states that AI currently adds $21 billion per year to Australian GDP. The gap between $21 billion today and $142 billion by 2030 requires a roughly sevenfold increase in four years. That is possible but represents an extremely aggressive growth assumption.
The Tech Council's broader survey data found that 93 per cent of workers believe AI will augment their jobs rather than replace them, and 72 per cent reported a positive or very positive impact from technology over the past decade. These sentiment figures are useful for understanding workforce attitudes but do not measure economic impact.
Pulling together the various sources, here is what the evidence reasonably supports about AI adoption and revenue impact for Australian SMEs.
Adoption is genuinely increasing. The upward trend across all surveys is consistent, even if the absolute numbers differ. More SMEs are using AI tools today than 12 months ago.
The primary use case is efficiency, not revenue generation. MYOB's framing is telling: businesses are adopting AI to "control costs and manage administrative workloads." The AI Group data shows technology investment intentions strongly positive at +34, driven by process improvements rather than new revenue streams. This is a cost story, not a growth story.
Measurement is largely absent. Nearly half of AI-using businesses do not measure impact at all. Among those that do, the methods are basic. There is no widespread, data-supported evidence of direct AI-to-revenue correlation for Australian SMEs.
The benefits accrue disproportionately to better-resourced businesses. Mid-market firms with more infrastructure, management capability, and measurement frameworks report better outcomes. This is consistent with technology adoption research across every era, not unique to AI.
Barriers to adoption are practical, not philosophical. The MYOB data shows time (17 per cent), cost (21 per cent), and understanding (18 per cent) as the main barriers. Businesses are not opposed to AI. They lack the capacity to implement it properly while running their existing operations.
The honest advice for SME owners considering AI investment is less exciting than the headlines but more useful.
Start with measurement. Before investing in any AI tool, establish baseline metrics for the processes you want to improve. If you cannot measure the current state, you cannot measure the improvement. This is basic, but 46 per cent of businesses are skipping it entirely.
Focus on efficiency before revenue. The data supports AI as a cost reduction and time-saving tool for SMEs. Content generation, data entry automation, basic analysis, and administrative task reduction are the use cases with the most consistent positive feedback. Revenue-generating AI applications (pricing optimisation, sales automation, product integration) require more sophistication and investment.
Build the operational foundation first. The mid-market performance gap is not primarily about technology. It is about the management and financial infrastructure that makes technology investments productive. Businesses with clear processes, accurate financial data, and management reporting frameworks will extract more value from any technology, including AI. This is where working with an embedded finance team like Scale Suite creates compounding value: the operational visibility that makes every subsequent investment more effective.
Tax incentives can help with the cost barrier. The MYOB data shows 23 per cent of SMEs would find tax deductions helpful for AI investment, and 22 per cent wanted more guidance on implementation. The existing instant asset write-off provisions and R&D tax incentive may apply to some AI investments. Consult your tax adviser on specifics.
The other side of the adoption question is worth addressing. While the revenue case for AI is unproven at the SME level, the risk of non-adoption is real.
Two-thirds of Australian SMEs are not yet using AI tools. As adoption increases among competitors, the productivity gap between adopters and non-adopters will widen. The MYOB data shows 41 per cent of SMEs have no online presence at all. For these businesses, AI is not the next step. Basic digital capability is.
The businesses most at risk are those in the middle: too large to ignore technology entirely, too small to have dedicated capability to implement it. These are the businesses that would benefit most from structured support, whether through advisory relationships, embedded service providers, or peer learning networks.
Depending on the source and definition, between 29 and 37 per cent of Australian SMEs are using AI tools. MYOB's Bi-Annual Business Monitor (November 2025, surveying 1,087 SMEs) reported 29 per cent usage, while the National AI Centre Adoption Tracker (Fifth Quadrant, 400 SMEs monthly) reported approximately 37 per cent. Broader surveys covering all business sizes report higher figures, with the CSIRO at 68 per cent.
There is currently no strong, data-supported evidence of a direct AI-to-revenue correlation for Australian SMEs. The MYOB data shows 82 per cent of AI-using businesses report positive impact, but 46 per cent do not measure impact at all. Mid-market businesses with higher adoption rates also report higher revenue growth (52 per cent vs 22 per cent for smaller businesses), but this correlation runs through broader factors including management capability and operational infrastructure.
The primary use cases are internal efficiency and cost reduction. MYOB's data shows businesses using AI to "control costs and manage administrative workloads." Only 7 per cent have integrated AI into their products or services. Common applications include content generation, data entry automation, basic analysis, and administrative task reduction.
The Tech Council of Australia estimates AI currently contributes $21 billion annually to Australian GDP, with a projection of $142 billion by 2030. This projection comes from "Australia's AI Opportunities Report," which was funded by OpenAI. The projection requires roughly sevenfold growth in four years.
According to the MYOB Bi-Annual Business Monitor, the main barriers are cost (21 per cent), understanding how to implement AI (18 per cent), and time (17 per cent). The National AI Centre also identified a gap between intended and deployed responsible AI practices, suggesting that even businesses committed to AI in principle face practical implementation barriers.
Agriculture shows the strongest evidence of technology-driven productivity gains, with 13 per cent activity growth despite a 17 per cent decline in employment over five years. Mining and financial services also show strong technology adoption outcomes. Retail and hospitality report the lowest AI productivity ratings at 5.5 out of 10 in the MYOB data, compared to the average of 6.3.
Our embedded finance teams deliver management reporting, process documentation, and financial visibility through shared platforms, giving SME owners the measurement frameworks and operational foundations needed before and after any technology adoption. We help you know what is working and what is not.
We review and update articles periodically. At time of writing, all data and sources were current and accurate. Figures are based on publicly available datasets and should not be taken as financial advice.
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