State of AI in Australian Business (2026)

This report synthesises data from 12 major research publications covering over 8,000 surveyed businesses to map the state of artificial intelligence in Australia as of early 2026. Every claim is sourced. Where estimates conflict, we present both figures and explain the discrepancy.

Australia has 2.73 million actively trading businesses (ABS, June 2024). The vast majority are small. The question this report addresses is not whether AI is important (that debate is over) but how deeply it has actually penetrated Australian business, where the gaps are, and what the economic consequences of inaction look like.

The global AI landscape in 2026

To understand where Australia stands, you need the global baseline.

Adoption is near-universal at the surface level

The McKinsey Global AI Survey, published in March 2025 and based on 1,491 participants across 101 nations, found that 78% of organisations now use AI in at least one business function, up from 72% in early 2024 and 55% a year before that. Generative AI specifically has reached 71% adoption, up from 65% in early 2024.

But these numbers obscure the maturity gap. When McKinsey asked about the depth of deployment, only 1% of company executives described their gen AI rollouts as "mature." More than 80% said they are not seeing tangible impact on enterprise-level EBIT from their AI use.

The Stanford HAI AI Index 2025 provides the investment context: global AI investment reached $252.3 billion. Private AI investment alone hit $109.6 billion in 2024. The money flowing into AI infrastructure is unprecedented.

The BCG value gap

Boston Consulting Group's 2025 report on the AI value gap introduced a useful framing. BCG classified organisations into three categories based on their AI maturity and found that only 5% qualify as "future-built," meaning they have integrated AI into core business operations and are capturing measurable value. The remaining 95% are either experimenting, piloting, or have not started.

BCG also found that AI agents (autonomous systems that can plan, reason, and take action) account for 17% of the value being captured by the most advanced organisations. This signals a shift from AI as a tool you query to AI as a system that operates.

How AI is actually being used

The Anthropic Economic Index, based on millions of anonymised conversations on Claude.ai, provides the most granular data on real-world AI usage patterns. The findings from their February 2025 report:

Source: Anthropic Economic Index, February 2025

Software development and writing account for nearly half of all AI usage. The rest is distributed across education, administration, science, and finance. Physical labour roles (farming, fishing, forestry) represent 0.1% of AI conversations.

Two data points stand out. First, AI usage splits 57% augmentation (AI collaborating with humans) and 43% automation (AI performing tasks directly). In most cases, AI is not replacing workers. It is working alongside them. Second, only 4% of occupations show AI usage across 75% or more of their tasks, while 36% show usage in at least 25% of tasks. AI has spread wide, but not yet deep.

By September 2025, the Index's follow-up report noted a significant shift: automation usage had risen to exceed augmentation for the first time, with directive task completion (user gives AI a task, AI completes it) jumping from 27% to 39% of interactions. AI is getting more autonomous.

In the United States, 40% of employees now report using AI at work, up from 20% the previous year. The adoption speed has no precedent among prior technologies.

Australia's position: invested but underperforming

The global picture is one of rapid adoption with shallow depth. Australia mirrors this pattern, but with a concerning lag.

The adoption numbers

The Australian Government's AI Adoption Tracker, published by the National AI Centre and based on monthly surveys of 400 SMEs by Fifth Quadrant, provides the most consistent longitudinal data on Australian AI adoption.

Q1 2025 figures by business size:

Source: AI Adoption Tracker, Q1 2025

The size gap is the defining feature. Large businesses are more than twice as likely to have adopted AI as micro businesses. This is not simply about budget. Large enterprises have dedicated technology teams, established data infrastructure, and the organisational capacity to experiment. A micro-business owner with four employees is their own IT department, HR department, and CIO.

The Deloitte Access Economics/Amazon report, published in November 2025 and based on a survey of 1,000 Australian SMBs, found that only 5% are fully AI-enabled. Those that are see profitability rise by approximately 45% when moving from basic to intermediate maturity, and roughly 111% when moving from intermediate to fully enabled.

How Australia compares globally

Deloitte's 2026 State of AI in the Enterprise report, based on 3,235 business and IT leaders across 24 countries, puts the Australian performance gap into sharp relief:

Source: Deloitte State of AI in the Enterprise, 2026

The headline: only 65% of Australian organisations plan to raise AI investment, compared to 84% globally. Only 12% of Australian leaders report that AI is already transforming their business, compared to 25% globally. The gap is not in awareness or interest. It is in execution and investment commitment.

Australia is slightly ahead on one metric: 28% of Australian respondents have moved 40% or more of AI pilots into production, versus 25% globally. And 57% expect to reach that level within six months. The potential for rapid acceleration exists. The question is whether organisations will follow through.

The Indeed Hiring Lab analysis published in April 2026 provides a labour market lens. In February 2026, 6.2% of Australian job postings on Indeed mentioned AI, up from 3.3% a year earlier. After remaining stable through 2023 and 2024, references to AI surged in 2025. However, two-thirds of AI-related postings came from just 1% of employers. AI hiring demand is concentrated among a small number of companies, not broadly distributed.

The economic opportunity

Multiple authoritative estimates quantify what Australia stands to gain from AI:

These estimates use different methodologies, assumptions, and timeframes, which explains the variation. The Deloitte figure is the most conservative because it models a specific, incremental change: one in ten SMBs moving up one step. The CSIRO and Google figures project broader economy-wide potential.

Regardless of which estimate you use, the gap between Australia's AI potential and its current adoption level is measured in hundreds of billions of dollars.

AI adoption by industry

The aggregate adoption numbers hide significant variation across sectors. Some industries are moving fast. Others have barely started.

The AI Adoption Tracker by industry (Q1 2025)

Source: AI Adoption Tracker, Q1 2025

The gap between retail (46%) and agriculture (19%) is 27 percentage points. More concerning: 35% of businesses in agriculture, construction, and manufacturing are not even aware of AI's potential applications. The awareness gap compounds the adoption gap.

Professional services: the leading edge

Professional services (legal, accounting, consulting) lead Australian AI maturity, and the data is increasingly specific.

Legal: The LexisNexis 2025-26 Australian Legal AI Survey, based on responses from over 1,000 legal professionals, found that 69% are now using or planning to use generative AI for legal work. Confidence in using AI has risen from 75% in 2023-24 to 90%. The most common application is legal research (45% of users), and the primary measure of success is time savings (38%). Inaccurate or fabricated outputs remain the top concern at 39%.

The Thomson Reuters 2026 AI in Professional Services Report, covering 1,500 professionals across legal, tax, accounting, and government, found generative AI use has nearly doubled, with 40% of professionals saying their organisations now use it, up from 22% the previous year. More than 80% of current users engage with it weekly.

Accounting: The State of AI in Accounting Report 2026 by Agile Market Intelligence, covering 400 Australian practices, found that almost 50% of accounting practices aim for complete AI integration. ChatGPT, Gemini, Claude, and similar standalone tools account for approximately 45% of overall AI use, while 44% prefer existing software with AI features from Xero or MYOB. Only about one in ten firms is not currently considering AI use.

The CPA Australia Business Technology Report 2025 found that nearly all businesses report some level of AI usage, but most indicate only moderate integration. The most common use cases for accounting and finance teams are data analytics and insights, research, and improving written communications. The main barriers to technology investment remain costs, low perceived return on investment, and concerns around data privacy and cybersecurity.

Real estate: The Australian Property Technology in 2026 report by Yardi and the Property Council of Australia, based on a survey of 236 senior leaders, found that 55% of Australian property organisations are implementing or operating AI systems. But only 18% say their AI capability is "stable and growing." Skills gaps, cited by 28% of respondents, have replaced cost as the primary barrier to adoption.

Healthcare: governance first, scale later

Healthcare AI adoption in Australia is proceeding cautiously, driven by regulatory requirements and patient safety considerations. The Australian Digital Health Agency's Corporate Plan 2025-2026 outlines a framework that prioritises governance, ethical guardrails, and workforce capability alongside innovation.

The Digital Health Cooperative Research Centre is developing a national classification and governance framework specifically for AI in healthcare, adapting the OECD AI Classification Framework for Australian conditions. Clinical decision support systems are being piloted at hospitals including Blacktown Mount Druitt Hospital in Western Sydney, with projects like VALID-AI assessing AI's effectiveness in detecting patient deterioration.

The Health and education sector's 45% adoption rate in the AI Adoption Tracker is encouraging, but much of this is administrative AI (scheduling, data entry, documentation) rather than clinical decision-making. Clinical AI faces higher regulatory hurdles and longer validation cycles, which is appropriate given the stakes.

The SMB gap: Australia's central challenge

The data tells a consistent story across every report we reviewed: the gap between large enterprises and small businesses is the single biggest structural problem in Australian AI adoption.

Why it matters

Australia's economy runs on small business. Of the 2.73 million actively trading businesses, 97% are small businesses (fewer than 20 employees). If AI's productivity benefits accrue primarily to large enterprises while small businesses lag, the result is a widening competitive gap that affects employment, local economies, and regional communities.

The Deloitte Access Economics modelling quantifies this. Moving SMBs from basic to intermediate AI maturity delivers approximately 45% profitability improvement. Moving from intermediate to fully enabled delivers roughly 111%. These are not theoretical numbers. They are based on observed differences in a survey of 1,000 Australian SMBs.

But the pathway from awareness to adoption is steep for small businesses. The barriers are specific and practical:

Time. A small business owner wearing six hats does not have a spare afternoon to evaluate AI tools, learn how to use them, and integrate them into existing workflows. The AI Adoption Tracker consistently shows that lack of time is a primary barrier for micro and small businesses.

Knowledge. Knowing that AI exists is different from knowing which tools solve which problems, how to evaluate them, and how to avoid the risks. The 35% of agriculture, construction, and manufacturing businesses that are "not aware" of AI applications are not disengaged; they are in sectors where the practical use cases are less obvious than they are for a law firm or accounting practice.

Cost perception. Many AI tools have free or low-cost tiers (ChatGPT, Claude, Gemini), but the perception that AI requires significant investment persists. The real cost for SMBs is not the tools themselves. It is the time investment to learn and implement them, and the risk of choosing wrong.

Data readiness. Advanced AI applications require clean, structured data. Many SMBs operate on spreadsheets, handwritten notes, and fragmented systems. Before they can benefit from AI analytics, they need basic digital infrastructure.

The two-speed economy

The data points toward what researchers are calling a "two-speed" digital economy. On one side: large enterprises and digitally native businesses using AI to capture significant productivity gains. On the other: millions of small businesses operating much as they did in 2023.

The Indeed Hiring Lab data reinforces this: two-thirds of all AI-related job postings in Australia come from just 1% of employers. AI capability is concentrating among a small number of organisations rather than diffusing across the economy.

This has implications for AI strategy. The businesses that gain the most from AI are not necessarily the ones with the biggest budgets. They are the ones that start with a clear problem, pick the right tool, and integrate it into an existing workflow. A five-person accounting firm that uses AI for client correspondence, data entry, and research gains more relative value than a 500-person company that runs an AI pilot in one department.

What AI can do today: practical applications for Australian businesses

The discussion around AI in business often oscillates between hype ("AI will replace all jobs") and dismissal ("AI is just a chatbot"). Neither is accurate. Here is what AI tools can actually do for businesses in 2026, with specific examples relevant to Australian sectors.

Text and document work

Generative AI is strongest at text-based tasks. This includes drafting communications, summarising documents, translating between plain English and technical language, and restructuring information.

For a law firm, this means first-pass contract review, case law summarisation, and client correspondence drafts. The LexisNexis survey found 45% of Australian legal professionals already use AI for legal research. For an accounting firm, it means data extraction from bank statements, draft correspondence to clients, and research memos. For a real estate agency, it means listing descriptions, tenant communications, and compliance documentation.

These applications do not require custom-built AI systems. Off-the-shelf tools like Claude, ChatGPT, and Gemini handle them effectively. The barrier is not technology. It is workflow design: knowing where to insert AI into an existing process, and how to verify the output.

Data analysis and pattern recognition

AI can process and surface patterns in datasets that would take humans days to review manually. This is where the productivity gains are most measurable.

A retail business can use AI to analyse sales data and identify purchasing patterns, seasonal trends, and inventory optimisation opportunities. A healthcare practice can use it to flag anomalies in patient data or streamline administrative reporting. A construction firm can use it for project cost estimation and materials planning.

The CPA Australia report found that data analytics and insights is the top AI use case for accounting and finance teams. Accounting firms are using AI to scan thousands of ledger entries for anomalies, a task that previously required graduate-level staff and significant time.

Customer communication and response

AI-powered communication tools are particularly relevant for businesses that handle high volumes of enquiries. The Thomson Reuters report found that 40% of professional services firms now use generative AI, and more than 80% of those users engage with it weekly. The primary efficiency gain is in handling routine communications that follow predictable patterns.

For property management firms, AI can handle after-hours enquiries, maintenance request triage, and standard tenant communications. The Property Council research found that 41% of property organisations report AI's greatest benefit is improved operational efficiency.

Autonomous agents: the next phase

The distinction between AI tools and AI agents is becoming commercially important. An AI tool responds to a prompt: you ask it a question, it gives you an answer. An AI agent can plan, reason, execute multi-step tasks, and take action with minimal human oversight.

Deloitte's 2026 enterprise report found that 69% of Australian organisations are already using autonomous AI agents. BCG's research found that agents account for 17% of the value captured by the most advanced organisations. The Thomson Reuters report found that while only 15% of professional services firms currently use agentic AI, an additional 53% are planning or considering it, and 77% expect it to be central to their workflow by 2030.

The investment landscape

Money follows conviction. The investment data reveals where capital markets expect AI to create value in Australia.

Startup funding

Australian startups raised $5.48 billion across 390 deals in 2025, a 31% increase over 2024, according to the State of Australian Startup Funding report by Cut Through Venture and Folklore Ventures. AI dominated the landscape:

• $1 billion went directly to companies classified as AI
• 61% of all capital invested ($3.1 billion across 214 deals) went to companies using AI somewhere in their technology stack
• The largest rounds were Firmus Technologies ($500M and $330M for AI data centre infrastructure) and Harrison.ai ($179M Series C for medical AI)

AI is no longer a sector. It is infrastructure. Companies in fintech, biotech, climate tech, and healthtech are all building on AI foundations. The 61% figure captures this: if you strip AI out of the 2025 funding data, the Australian startup ecosystem looks significantly smaller.

In Q1 2026, approximately $1.8 billion was deployed across Australian startups. Enterprise AI infrastructure was the largest category at $420 million, followed by climate tech at $380 million. Sydney accounts for 48% of capital deployed, Melbourne 32%, Brisbane 9%.

Global context

The Stanford HAI AI Index reported $252.3 billion in global AI investment in 2024. Australia's $1 billion in direct AI startup funding is a fraction of this, reflecting the country's smaller economy. But the 61% figure (AI embedded across $3.1 billion in total funding) suggests AI's influence on Australian capital allocation is comparable to global trends.

The investment thesis is shifting. Early AI investment focused on building models (foundation models, training infrastructure). Current investment focuses on deploying AI (enterprise platforms, industry-specific applications, governance tools). This is consistent with Australia's strengths: the country is unlikely to compete with the US or China on foundational AI research, but it can lead in applying AI to specific industry problems.

Where Australia is ahead, and where it is behind

Ahead

Regulatory approach. Australia's risk-based regulatory framework sits between the EU's comprehensive legislation and the UK's sector-specific model. The Voluntary AI Safety Standard, published in September 2024, established 10 guardrails that give businesses practical guidance without imposing compliance costs on low-risk applications. Mandatory guardrails for high-risk settings are arriving in Q4 2026, giving businesses time to prepare. This phased approach is pragmatic and has drawn positive attention internationally.

Government transparency. The Digital Transformation Agency's updated policy on responsible AI use in government, effective from December 2025, mandates foundational AI training for all APS staff, requires AI impact assessments for individual use cases, and establishes governance requirements. Australia is one of few countries mandating AI literacy across its entire public service.

Healthcare governance. Australia's cautious approach to clinical AI, prioritising validation frameworks and governance before scale, may look like a disadvantage today but could prove prescient. The Digital Health CRC's work on operationalising the OECD AI Classification Framework for healthcare establishes infrastructure that other countries will need to replicate.

Pilot-to-production pipeline. Despite lagging on overall investment intent, 28% of Australian respondents in Deloitte's enterprise survey have moved 40%+ of AI pilots into production, slightly above the 25% global average. When Australian organisations commit, they execute.

Behind

Investment intent. The 65% vs 84% gap in planned AI investment increases is the most concerning data point in this report. If Australian businesses invest less in AI than global peers over the next two years, the productivity gap will compound.

Transformation depth. Only 12% of Australian leaders say AI is already transforming their business, half the global rate of 25%. Most Australian AI usage remains focused on automating existing processes rather than redesigning workflows. 61% report improved efficiency, but only 30% are using AI to deeply transform their ways of working.

SMB adoption. With 33% adoption among micro businesses and only 5% fully AI-enabled across all SMBs, Australia's small business sector is significantly underweight on AI. Given that small businesses comprise 97% of all Australian businesses, this is not a niche problem.

Skills supply. The Indeed Hiring Lab found that AI-related job postings are concentrated among a tiny fraction of employers. Over half of Australian companies in Deloitte's survey cite talent and skills gaps as a barrier to scaling AI. The ACS Digital Pulse 2024 reported that Australia's technology sector contributes $124 billion to the economy, but skilled worker shortages persist across multiple technology disciplines.

Data maturity. The Property Council research found that for many Australian organisations, "AI ambition is running ahead of data maturity, systems integration and workforce readiness." This is not unique to property. Many Australian businesses lack the clean, structured data that AI systems need to deliver value.

The regulatory landscape

Australia's approach to AI regulation is entering a decisive phase.

The current framework

The Voluntary AI Safety Standard, published in September 2024 and updated with the Guidance for AI Adoption in October 2025, provides 10 guardrails covering accountability, risk management, data governance, testing, human oversight, transparency, and stakeholder engagement. The standard is voluntary and does not create new legal obligations. It is designed to help organisations operate within existing Australian laws (privacy, consumer protection, anti-discrimination, directors' duties) while preparing for future regulation.

What is coming

The Department of Industry, Science and Resources confirmed in February 2026 that mandatory AI obligations will take effect for high-risk applications by Q4 2026, with broader requirements phased in through 2027. The proposed model classifies AI applications into four tiers:

Source: DISR Proposals Paper, September 2024

A new AI Safety Commissioner's office is expected to be operational by mid-2026, with a regulatory sandbox for testing high-risk AI applications under supervised conditions.

For most SMBs, the regulatory impact will be minimal. Generative AI assistants, marketing tools, and productivity applications fall into the limited-risk or minimal-risk categories. The compliance burden concentrates on organisations deploying AI in high-stakes decisions: hiring, lending, medical diagnosis, and critical infrastructure.

The Treasury's review of Australian Consumer Law in relation to AI found that existing consumer protections (misleading and deceptive conduct, product safety standards) largely apply to AI-enabled goods and services. This means businesses using AI in customer-facing applications already have legal obligations, regardless of when mandatory AI-specific regulation arrives.

International comparison

Australia's approach sits between three established models:

• EU AI Act (enforcement began February 2025): prescriptive, comprehensive, and far-reaching. High compliance costs.
• UK approach: sector-specific, delegating AI oversight to existing regulators (FCA for financial AI, MHRA for medical AI). Flexible but fragmented.
• US approach: largely voluntary, with sector-specific executive orders and agency guidance. Limited federal legislation.

Australia has borrowed the EU's risk-based classification but adapted it with more flexibility for the regulator and a phased implementation that gives businesses time to prepare. For organisations already following the Voluntary AI Safety Standard, the transition to mandatory compliance should be manageable.

What comes next

The data paints a clear picture of where Australia stands: wide adoption, shallow depth, and a significant gap between large enterprises and the small businesses that make up the vast majority of the economy.

Three trends will define the next 12 to 18 months.

The move from tools to agents. Generative AI tools that respond to prompts are giving way to autonomous agents that plan and execute multi-step tasks. Deloitte found 69% of Australian organisations are already using AI agents. The Thomson Reuters report found 77% of professional services firms expect agentic AI to be central to their workflow by 2030. Organisations that build agent capabilities now will have a structural advantage.

Regulation as a forcing function. Mandatory guardrails for high-risk AI arriving in Q4 2026 will force organisations to document their AI systems, assess risks, and implement governance processes. For many businesses, this will be the catalyst that moves AI from ad hoc usage to structured deployment. Companies that have been following the voluntary standard will be ahead.

The SMB acceleration. The conditions for rapid SMB AI adoption are falling into place: capable free-tier tools (Claude, ChatGPT, Gemini), industry-specific AI applications, and increasing competitive pressure from early adopters. The Deloitte data suggests that 57% of Australian organisations expect to reach significant AI deployment milestones within six months. If even a fraction of SMBs follow through, the aggregate numbers will shift quickly.

The $44 billion GDP opportunity modelled by Deloitte requires just one in ten SMBs to advance one step. That is not a moonshot. It is achievable with practical, incremental adoption: automating one document process, implementing one AI assistant, integrating one data analysis tool. The organisations that treat AI as a strategic capability rather than a novelty will capture disproportionate value.

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Methodology

This report draws on the following primary data sources:

• Deloitte Access Economics/Amazon "AI Edge for SMBs" (November 2025): Survey of 1,000 Australian SMBs with bespoke AI Maturity Index and economic modelling.
• Deloitte "State of AI in the Enterprise" (February 2026): Survey of 3,235 business and IT leaders across 24 countries, with Australian-specific breakdowns.
• McKinsey Global AI Survey (March 2025): 1,491 participants across 101 nations, weighted by GDP contribution.
• Stanford HAI AI Index 2025: Annual compendium of AI research, investment, and policy data from academic and industry sources.
• Anthropic Economic Index (February and September 2025): Analysis of millions of anonymised Claude.ai conversations mapped to O*NET occupational tasks.
• BCG AI Value Gap (October 2025): Classification of organisations by AI maturity and value capture.
• Australian Government AI Adoption Tracker (Q1 2025): Monthly surveys of 400 Australian SMEs by Fifth Quadrant, published by the National AI Centre.
• CPA Australia Business Technology Report 2025: Survey of technology usage across Australian businesses with focus on accounting and finance.
• LexisNexis Australian Legal AI Survey 2025-26: Over 1,000 legal professionals surveyed on AI adoption, confidence, and use cases.
• Thomson Reuters 2026 AI in Professional Services Report: 1,500 professionals across legal, tax, accounting, and government.
• State of AI in Accounting Report 2026 (Agile Market Intelligence/Access Group): 400 Australian accounting practices surveyed.
• Australian Property Technology in 2026 (Yardi/Property Council): 236 senior property leaders surveyed.
• Cut Through Venture/Folklore Ventures State of Australian Startup Funding 2025: Comprehensive analysis of $5.48 billion in startup funding.
• Indeed Hiring Lab Australian AI Adoption (April 2026): Analysis of AI mentions in Australian job postings on Indeed.

Where reports use different definitions of "adoption" (ranging from "has used ChatGPT once" to "fully integrated AI into core operations"), we note the definition. Where estimates conflict, we present both figures. All URLs were verified at the time of writing.

Sources

• Deloitte Access Economics/Amazon: The AI Edge for SMBs - 1,000 AU SMBs surveyed, $44B GDP opportunity, AI maturity modelling
• Deloitte State of AI in the Enterprise 2026 - 3,235 leaders across 24 countries, Australian vs global comparison
• McKinsey: The State of AI 2025 - 78% of orgs using AI, only 1% mature rollouts, workflow redesign as top value driver
• Stanford HAI AI Index 2025 - $252.3B global AI investment, comprehensive research and policy tracking
• Anthropic Economic Index - Millions of Claude conversations analysed, 57%/43% augmentation/automation split, occupation-level data
• BCG: The Widening AI Value Gap - Only 5% "future-built," agents account for 17% of AI value
• Australian Government AI Adoption Tracker - Monthly survey of 400 SMEs, adoption by business size, industry, and AI application type
• AI Adoption in Australian Businesses, Q1 2025 - 82% large business adoption, 33% micro business adoption, industry breakdown
• CPA Australia Business Technology Report 2025 - Technology usage across AU businesses, AI in accounting and finance, barriers to investment
• CSIRO AI Roadmap - AU$315B potential economic contribution
• Google/Access Partnership: Turning Australia's AI Opportunities Into Impact - $280B economic benefits by 2030
• ACS Digital Pulse 2024 - Tech sector $124B contribution to AU economy
• ABS Counts of Australian Businesses - 2.73M actively trading businesses
• LexisNexis 2025-26 Australian Legal AI Survey - 1,000+ legal professionals, 69% using or planning AI, 90% confident
• Thomson Reuters 2026 AI in Professional Services Report - 1,500 professionals, GenAI use doubled to 40%, only 18% track ROI
• State of AI in Accounting Report 2026 - 400 AU practices, 50% aiming for complete AI integration
• Australian Property Technology in 2026 (Yardi/Property Council) - 55% implementing AI, skills gaps as top barrier
• Indeed Hiring Lab: Australian AI Adoption - 6.2% of job postings mention AI, two-thirds from 1% of employers
• Cut Through Venture/Folklore: State of Australian Startup Funding 2025 - $5.48B raised, 61% AI-embedded, $1B direct AI
• DISR Voluntary AI Safety Standard - 10 guardrails for safe and responsible AI use
• DISR Proposals Paper: Mandatory Guardrails for AI in High-Risk Settings - Four-tier risk classification, three regulatory options
• DTA AI Policy Update - Mandatory AI training for APS staff, governance requirements
• Australian Digital Health Agency Corporate Plan 2025-26 - Digital health strategy, AI governance framework
• Digital Health CRC: AI Classification Framework for Healthcare - OECD framework adapted for AU healthcare
• Treasury: ACL Review re AI - Existing consumer law applies to AI-enabled goods and services