Quick Summary
This report brings together published data on AI adoption in Australian business in 2026: market size and growth, adoption by industry, the most common uses, the barriers holding businesses back, and what to do next. The key finding: the National AI Centre's AI Adoption Tracker found 43 per cent of Australian SMEs reported some level of AI adoption in December 2025 to February 2026, and businesses already using AI are moving from one-off use towards using it across more of the business. For the rest, trust and relevance are the biggest barriers.
Key fact: IMARC Group estimates the Australian AI-as-a-Service market at USD 530.6 million in 2025 and expects it to reach USD 4,633.6 million by 2034, a CAGR of 27.23 per cent.
Table of Contents
- Executive Summary
- Market Size and Growth
- AI Adoption by Industry and Business Size
- Top AI Use Cases in 2026
- Barriers to Scaling AI
- Investment and Spending Trends
- Regional Picture: Melbourne, Sydney, Brisbane, Perth
- Predictions for 2027-2030
- What Australian Businesses Should Do Next
- Frequently Asked Questions
Executive Summary
The Headlines
| Finding | Detail |
|---|---|
| 43% of Australian SMEs report some level of AI adoption | December 2025 to February 2026, down slightly from 45% the quarter before (National AI Centre) |
| Adopters are going deeper | Broad adoption across multiple parts of the business reached its highest level in seven months, while limited, one-off use is declining |
| Trust is the main barrier | Around 65% of non-adopting SMEs cited distrust of AI decision-making or a preference to keep human control |
| AI-as-a-Service market growing at 27.23% CAGR | USD 530.6M (2025) to USD 4,633.6M (2034) (IMARC Group) |
| Australian IT spending forecast at AUD 172.3B in 2026 | Up 8.9% on 2025 (Gartner) |
| Over 84,700 cybercrime reports to ASD in 2024-25 | About one every six minutes; 11% of the incidents ASD responded to included ransomware (ASD Annual Cyber Threat Report 2024-25) |
The 3 Key Takeaways
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Adoption is broad but shallow for many businesses. Fewer than half of SMEs report any AI adoption, and many of those are still at limited or one-off use. The businesses that have committed to AI are expanding their use rather than retreating.
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Managed IT is changing. Break-fix support is declining in favour of proactive managed services, and buyers increasingly expect automation and reporting to be part of the service rather than an add-on.
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Regulation is shaping priorities. Mandatory climate reporting (ASRS, phased in from 1 January 2025), Essential Eight expectations and Privacy Act reforms are pushing businesses to get their data and reporting in order, which is the same groundwork AI depends on.
Market Size and Growth
AI-as-a-Service Market
Source: IMARC Group.
| Metric | Value |
|---|---|
| Market size (2025) | USD 530.6 million |
| Projected market size (2034) | USD 4,633.6 million |
| CAGR (2026-2034) | 27.23% |
IT Spending
Source: Gartner, September 2025 forecast.
| Metric | Value |
|---|---|
| Total Australian IT spending (2026 forecast) | AUD 172.3 billion |
| Growth on 2025 | 8.9% |
ESG and Compliance Market
Source: IMARC Group.
| Market | Size (2025) | Projected (2034) | CAGR (2026-2034) |
|---|---|---|---|
| Environmental consulting services (Australia) | USD 751.9M | USD 1,186.3M | 5.04% |
Government Support
The federal government's AI Adopt Program, a $17 million initiative, funded AI Adopt Centres that give small and medium businesses guidance on adopting AI safely and free specialist training (Minister for Industry and Science, archived release). Check business.gov.au for the program's current status before relying on it.
AI Adoption by Industry and Business Size
The National AI Centre's tracker surveys Australian SMEs each month. In its December 2025 to February 2026 update:
| Measure | Finding |
|---|---|
| SMEs reporting some level of AI adoption | 43% for the quarter (44% in February 2026) |
| Previous quarter (September to November 2025) | 45% |
| Leading sectors | Health, Education and Services, with more than half of businesses using AI |
| Lagging sectors | Construction and Agriculture, with fewer than 30% adopting AI |
Source: National AI Centre.
Typical Use Cases by Industry
These are common starting points we see by industry. They are examples, not survey results.
| Industry | Common Use Cases |
|---|---|
| Financial services | Fraud detection, compliance monitoring, customer onboarding, document processing |
| Manufacturing | Predictive maintenance, quality control, supply chain optimisation, production scheduling |
| Logistics and transport | Route optimisation, fleet management, delivery tracking, demand forecasting |
| Professional services | Document review, time tracking, client onboarding, proposal generation |
| Healthcare | Patient scheduling, claims processing, clinical documentation, compliance reporting |
| Retail and e-commerce | Inventory management, demand forecasting, customer service, personalised marketing |
| Education | Student onboarding, attendance tracking, assessment marking, compliance reporting |
| Construction | Project scheduling, cost estimation, safety monitoring (early stage) |
| Agriculture | Crop monitoring, yield prediction, supply chain tracking (early stage) |
From Casual Use to Embedded Use
The tracker shows a shift inside the adopter group: broad adoption, where AI is embedded across multiple parts of the business, reached its highest level in seven months, while limited, one-off use is declining. In the tracker's words, those who have committed to AI are doubling down. The gap that matters is between individual staff trying a chatbot and AI built into a documented business process with a measured result.
Top AI Use Cases in 2026
Among SMEs using or planning to use AI, the National AI Centre found:
| Use | Share of adopters |
|---|---|
| Content generation | 54% |
| Data analytics | 54% |
| Cybersecurity and threat detection | 48% |
More complex uses, such as agentic AI, supply chain optimisation and AI-assisted HR, remain largely untapped (National AI Centre).
The automation projects we see most often in mid-market businesses are below. Savings depend on transaction volumes, wage rates and how clean the underlying process and data are, so estimate them from your own figures rather than a generic range.
Quick Wins (often deployed in a few weeks)
| Use Case | Industries |
|---|---|
| Invoice processing | All industries |
| Email triage and routing | All industries |
| Monthly report generation | Professional services, financial services |
| Customer and client onboarding | All industries |
| Password reset self-service | All industries |
Larger Automations
| Use Case | Industries |
|---|---|
| Compliance documentation | Financial services, healthcare, government suppliers |
| ESG and Scope 3 data collection | Businesses in scope for ASRS reporting and their suppliers |
| Lead scoring and routing | Professional services, financial services |
| Data reconciliation | All industries |
| Vendor management | All industries |
AI Agents
| Agent Type | Industries |
|---|---|
| Customer inquiry resolution | Professional services, retail, healthcare |
| Data reconciliation | Financial services, manufacturing |
| Compliance monitoring | Financial services, healthcare, government |
| ESG data collection | Businesses in scope for ASRS reporting |
Barriers to Scaling AI
The National AI Centre identifies three barriers that explain why more than half of Australian SMEs are yet to meaningfully adopt AI (source):
Barrier 1: Trust
Around 65 per cent of non-adopting businesses cited either distrust in AI decision-making or a strong preference to keep human control over their business processes. This was consistent across business sizes and locations.
Barrier 2: Relevance
More than half of non-adopting businesses (54 per cent) said AI is not relevant to their business. The tracker reads this as a lack of visible, relatable examples rather than a rejection of AI.
Barrier 3: Not Knowing Where to Start
Nineteen per cent of SMEs said they simply do not know how to use AI in their business, up on the previous quarter.
What We See in Mid-Market Projects
In our own work, two further problems slow businesses down once they have decided to use AI:
- Data is not ready. Data spread across many systems, with inconsistent formats, missing fields and no single source of truth, means every pilot starts with custom data preparation.
- No clear ROI measurement. If a pilot's result is not measured, scaling it competes with every other budget item on gut feel rather than evidence.
Investment and Spending Trends
Gartner forecasts Australian IT spending to reach AUD 172.3 billion in 2026, up 8.9 per cent on 2025 (Gartner).
For an individual business, AI spending usually falls into these categories. Costs vary widely with scope, so get quotes against a defined process rather than relying on generic ranges.
| Spending Category | What It Covers |
|---|---|
| AI tool subscriptions (Copilot, ChatGPT and similar) | Per-user licences for individual productivity |
| Automation projects (agency or consultant) | Building and integrating a specific automation |
| Managed IT with automation included | Ongoing operations with monitoring, patching and reporting automated |
| In-house AI or automation role | A dedicated person to own the roadmap and build |
| ESG and ASRS compliance support | Data collection, calculation and reporting for climate disclosures |
Regional Picture: Melbourne, Sydney, Brisbane, Perth
Published adoption data is not broken down by city, so treat this as a guide to where demand comes from rather than a ranking.
| City | Industries driving demand |
|---|---|
| Melbourne | Professional services, healthcare, education, manufacturing |
| Sydney | Financial services, professional services, logistics, technology |
| Brisbane | Logistics, healthcare, construction, resources |
| Perth | Mining, resources, logistics, manufacturing |
Predictions for 2027-2030
2027
| Prediction | Probability |
|---|---|
| Automation and reporting expected as part of managed IT services | High |
| First ASRS reports from Group 2 entities (reporting from 1 July 2026) | Certain |
| AI automation becomes standard in managed IT contracts | High |
| Cyber insurance requires Essential Eight Maturity Level 2 | Medium-High |
| "AI agent" searches exceed "AI automation" searches | High |
2028
| Prediction | Probability |
|---|---|
| First ASRS reports from Group 3 entities (reporting from 1 July 2027) | Certain |
| Autonomous IT operations (self-healing infrastructure) available | Medium-High |
| Break-fix MSP model effectively dead for mid-market | High |
| AI-powered ESG reporting is standard offering | High |
2029-2030
| Prediction | Probability |
|---|---|
| Reasonable assurance required for ASRS disclosures | Medium |
| AI agents handle majority of routine IT operations | Medium |
| Strategic advisory is the core MSP value proposition | High |
| Traditional MSPs are commodity providers competing on price | High |
What Australian Businesses Should Do Next
If You Are at Level 1 (Casual User)
- Purchase one AI tool for a specific team and measure its impact
- Map the processes where staff spend the most manual time
- Identify your top 3 automation opportunities with ROI estimates
If You Are at Level 2 (Tool Adopter)
- Document and tidy up the target processes and their data before automating them
- Build a 12-month AI roadmap with prioritised automations
- Begin deploying quick-win automations (invoice processing, email triage)
If You Are at Level 3 (Process Automator)
- Expand to 5-10 automations using shared infrastructure
- Deploy AI agents for complex, multi-step processes
- Establish AI governance framework and quarterly review process
If You Are at Level 4 (Strategic Deployer)
- Explore AI agents for autonomous workflow management
- Integrate AI into your competitive strategy
- Share your AI learnings with industry peers
If You Are at Level 5 (AI-Native)
- Maintain competitive advantage through continuous AI optimisation
- Explore emerging AI capabilities (multimodal agents, autonomous decision-making)
- Consider AI-enabled products or services as new revenue streams
Frequently Asked Questions
How many Australian businesses use AI?
The National AI Centre's AI Adoption Tracker found 43 per cent of Australian SMEs reported some level of AI adoption in December 2025 to February 2026. That includes limited, one-off use. Fewer businesses have AI embedded across multiple parts of the business, although that group is growing.
What is the single highest-ROI AI use case?
It depends on your volumes, but email triage and routing often pays back well because it applies to every employee, runs continuously and needs little integration. Invoice processing is another strong candidate because the time saved is easy to measure and defend.
How quickly can a business go from Level 1 to Level 3?
With a clear plan and dedicated effort, typically 6-12 months. Months 1-2: process mapping and first automations. Months 3-6: data and integration improvements and expanded automation. Months 6-12: more complex workflows and a governance framework. Without a plan, the same journey often takes 18-36 months.
What is the biggest mistake Australian businesses make with AI?
Starting with tools instead of strategy. Buying Copilot, ChatGPT, or an AI chatbot without understanding which business processes to automate, what the ROI would be, and what infrastructure is needed to support scaled deployment. This leads to "pilot purgatory", isolated experiments that never compound.
Will AI replace Australian jobs?
AI will replace tasks, not jobs. The businesses that use AI to augment their staff (eliminating repetitive tasks, freeing time for strategic work) will see higher retention, higher satisfaction, and higher revenue per employee. The businesses that use AI to replace staff will lose institutional knowledge and damage morale. How the overall effect on employment plays out is still uncertain; what is clear is that the gains come from redesigning work, not just adding a tool.
About This Report
This report draws on published sources: the National AI Centre's AI Adoption Tracker, IMARC Group market estimates, Gartner's IT spending forecast and ASD's Annual Cyber Threat Report. Each is listed under Sources below. Use cases, regional notes and predictions are our own view from working with Australian businesses, not survey results.
Start With the Process
Most automation wins, AI or otherwise, start with a clear map of how the work is done today and where the data lives. If you want help documenting and fixing a process before automating it, see our business process mapping service. Where the bottleneck is systems that do not talk to each other, ERP integration is usually the first step.