The State of AI Readiness in Australia
Australian businesses are adopting AI faster than most executives realise. But readiness varies dramatically by industry, company size, and which dimensions you measure.
Based on our assessment data, here's a snapshot of where different industries stand across the eight dimensions of AI readiness.
Technology: Leading But Not Everywhere (Avg: 68/100)
Tech companies score highest overall, but that hides significant variation. Startups and digital-native companies score 75+ consistently. Legacy tech companies — the ones built on on-premise software — often score below 50 on data infrastructure because their own systems are siloed.
Strengths: Technology stack, talent, culture
Gaps: Governance (many tech companies still treat AI ethics as optional), financial readiness (uncertain unit economics for AI features)
Finance: Strong Data, Weak Culture (Avg: 61/100)
Financial services have excellent data infrastructure — years of regulatory requirements have forced good data practices. But cultural readiness is surprisingly low. Risk-averse cultures resist the experimentation that AI adoption requires.
Strengths: Data, governance, process maturity
Gaps: Culture (risk aversion), strategy (AI often siloed in innovation labs)
Healthcare: The Governance Challenge (Avg: 52/100)
Healthcare organisations want to use AI but face legitimate governance concerns. Patient data regulations, clinical validation requirements, and liability questions create real barriers. The organisations that score highest have invested in AI governance frameworks early.
Strengths: Process maturity, strategy (clear use cases in diagnostics and admin)
Gaps: Governance (regulatory complexity), technology (legacy systems)
Professional Services: Hidden Potential (Avg: 55/100)
Law firms, accounting firms, and consultancies are sitting on gold mines of structured process knowledge but many haven't connected this to AI opportunity. The ones that have are seeing dramatic efficiency gains in document review, research, and client communication.
Strengths: Process maturity, talent (analytical thinking translates well)
Gaps: Technology (underinvestment in infrastructure), data (client data is often unstructured)
Retail: Fast Adopters, Shallow Depth (Avg: 49/100)
Retail has been quick to adopt consumer-facing AI (chatbots, recommendations) but slow to build deeper AI capabilities. Many retailers have AI features but no AI strategy — a classic technology-first mistake.
Strengths: Culture (comfort with experimentation), strategy (clear ROI cases)
Gaps: Data (fragmented across channels), talent (limited internal AI skills)
Manufacturing: The Automation Advantage (Avg: 47/100)
Manufacturing companies that have invested in Industry 4.0 and IoT are well-positioned for AI. Those that haven't are the furthest behind of any industry. The gap within manufacturing is the widest of any sector.
Strengths: Process maturity (operational discipline), financial readiness (used to capital investment)
Gaps: Talent (critical shortage of AI/ML skills), technology (OT/IT divide)
Education: Big Ambitions, Small Budgets (Avg: 44/100)
Education institutions understand AI's potential but struggle with funding and governance. Universities score higher than K-12, and private institutions score higher than public ones. The biggest constraint is financial readiness.
Strengths: Culture (intellectual curiosity), strategy (research-informed approach)
Gaps: Financial readiness (budget constraints), technology (legacy systems)
Government: Governance First, Everything Else Second (Avg: 41/100)
Government agencies score highest on governance (they have to) but lowest on technology and culture. Procurement processes and risk aversion slow AI adoption significantly. The agencies that succeed are the ones with executive champions willing to push boundaries within governance frameworks.
Strengths: Governance, process maturity
Gaps: Technology, culture, talent
Media: Disrupted and Responding (Avg: 50/100)
Media companies face existential pressure from AI and are responding with urgency. Content generation, personalisation, and audience analytics are the primary use cases. But many media companies lack the data infrastructure to do AI well.
Strengths: Strategy (existential motivation), culture (creative adaptability)
Gaps: Data (content is unstructured), financial readiness (declining traditional revenue)
What This Means For Your Organisation
Industry averages are useful benchmarks, but every organisation is different. Your specific AI readiness depends on your strategy, your data, your people, and your culture — not just your industry.
The most valuable insight isn't where your industry ranks. It's understanding your specific strengths and gaps across all eight dimensions, so you can focus investment where it matters most.
Take the free Quick Scan to see exactly where you stand relative to your industry peers.