"AI in the workplace" now spans from an individual using a chatbot for a quick first draft, through to AI fully embedded in how a business operates and makes decisions. Our survey tracked this as a maturity spectrum:

• Restricted or not started

• Informal experimentation

• Formal pilots

• Implemented in workflows

• Embedded in strategy and operating model

Most conversations about "AI at work" collapses it into a single idea, usually of either hype or fear. The real picture across Australia and New Zealand is more specific: individual use has surged, organisational maturity is catching up unevenly, and the businesses furthest along aren't simply just using AI more. But using it with clearer governance, training, and measurement wrapped around it.

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We heard from 1,505 business leaders and technology professionals: 85% based in Australia and 15% in New Zealand, spanning 12+ industries and every level of seniority. Sixty percent were people leaders, breaking down as:

• C-suite: 7%

• Directors: 9%

• Heads of function: 11%

• Managers: 33%

• Individual contributors: 40%

The strongest industry representation came from:

• Government: 23%

• Technology: 20%

• Education: 9%

• Energy and Resources: 9%

• Financial Services: 7%

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How This Research Was Conducted

The survey ran in July 2026 across Australia and New Zealand, capturing responses from C-suite leaders, directors, heads of function, managers, and individual contributors. That spread, across seniority, industry, and role, is what lets us report not just whether AI is being used, but how differently it's experienced depending on where you sit in an organisation.

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How Mature Is AI Adoption in ANZ?

AI has moved into everyday work, but organisational maturity hasn't caught up at the same pace. Nearly half of respondents (49%) now use AI daily for work, up from around a third (34%) last year, and 71% use it at least weekly, up from 60% in 2025.

Organisational maturity tells a different story. Comparing 2025 to 2026:

Informal experimentation has fallen sharply, and implementation has surged, but a quarter of organisations are still only piloting. Full strategic embedding, while up six-fold, still describes fewer than one in four businesses.

Organisations scaling AI often need contract specialists fast to bridge the gap between a pilot and a production rollout. See how Talent's tech contractor network supports fast-moving AI programs.

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How Does ANZ's AI Adoption Compare Globally?

The following data is sourced externally, not from Talent's 2026 ANZ survey, and is included here for benchmarking context only.

ANZ's adoption curve is steep, but it's not necessarily ahead of the pack. Deloitte's 2026 State of AI in the Enterprise report, which surveyed 3,235 business and IT leaders across 24 countries, found that:

• Only 65% of Australian respondents intend to raise AI investment next year, compared with 84% globally.

• Just 12% of Australian leaders say generative AI is already transforming their business or industry, against 25% globally.

Separately, Melbourne Business School's global Trust and AI study, spanning 47 countries, found that employee-reported organisational AI use jumped from 34% to 71% across the 17 countries it tracked from 2022 to today. That's a trajectory broadly in line with what we're seeing in ANZ, though trust in AI has fallen even as use has risen.

Taken together: ANZ organisations are adopting AI at a comparable pace to the rest of the world, but ambition, and the confidence that AI is delivering transformative impact, is lagging behind global peers.

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Does AI Actually Make Employees More Productive?

At an individual level, yes, clearly. Here's how respondents describe AI's impact on their work:

• Saved meaningful time: 53%

• Small, task-specific gains: 32%

• No noticeable difference: 5%

• Created errors or rework: 3%

85% of respondents say AI has made them more efficient at work overall. But there's a catch worth naming: 26% say they mainly use AI to start work, not finish it. That's a sign that AI is accelerating the early stages of a task more reliably than it's carrying work through to completion.

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How Are Organisations Measuring AI ROI?

This is where the productivity story gets harder to prove. Just 8% of organisations are measuring AI's impact with clear metrics or KPIs. The rest break down as:

• Yes, but informally: 13%

• Starting to define an approach: 19%

• No, but plan to: 18%

• No current plans: 20%

• Not sure: 22%

That means 79% aren't measuring impact in any formal way. Among organisations that do measure impact, the top metrics used are:

• Time saved: 18%

• Productivity or output: 16%

• Speed of delivery: 16%

• Quality of work: 13%

• Adoption or usage rates: 12%

• Cost reduction: 11%

• Employee capability uplift: 10%

The pattern is clear: individual productivity gains are real and widely felt, but very few organisations have built the measurement discipline to turn "people feel more efficient" into a business case leadership can act on.

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What Are the Biggest AI Risks at Work?

Governance hasn't kept pace with usage, and the risk isn't theoretical misuse: it's everyday uncertainty. 57% of respondents name entering confidential or client data as a top risk behaviour. Almost 1 in 4 (23%) say their organisation has never provided AI training or a mandatory policy refresh. And just 16% are confident staff know what data is safe to enter into AI tools.

That last figure is the crux of it: even where policy exists, confidence in whether people actually understand it is low. 41% describe their organisation's AI rules as very clear, but only 16% are equally confident staff know what data can and can't be entered. That's a real gap between having a policy and people understanding it day to day.

The highest-risk behaviours respondents flagged:

• Relying on AI outputs unchecked: 57%

• Entering confidential data: 57%

• Making decisions without human oversight: 47%

• Using unapproved AI tools: 27%

• Ignoring internal AI policies: 27%

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How Are Employees Actually Misusing AI at Work?

Our own data shows what the risk categories are: over half of respondents flag unchecked outputs and confidential data entry as top concerns. Melbourne Business School's 47-country Trust and AI study puts numbers on how that plays out day to day:

• 66% of employees globally report using AI output in their work without evaluating it.

• 56% say they've made a mistake in their work because of AI.

• Over half admit they've avoided revealing when they used AI to complete work.

• Almost half say they've used AI in ways that contravene their organisation's own policies, including uploading sensitive company information into public AI tools.

This section combines Talent's 2026 ANZ survey findings with externally sourced data from Melbourne Business School's global Trust and AI study, cited above.

Building AI governance capability starts with the right people. Talent's RPO service embeds recruitment and compliance expertise directly into your team.

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Do Employees Trust AI Output?

Trust is improving, but it's conditional. 47% say AI output is getting better, and only 3% say it's getting worse, though 31% say it depends on the tool or use case, and 11% see no real change.

The bigger story is in what's holding trust back:

• Loss of human judgement: 21%

• Data security / confidentiality: 19%

• Over-reliance on AI: 16%

• Accuracy: 11%

It’s telling that 40% say AI is only useful when people know how to use it well: trust here isn't really about the technology in isolation, but about the skill of the person using it. And on the broader hype question, only 21% think expectations around AI are now more grounded; 48% say attitudes are still hype-driven, even as usage has matured.

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How Is AI Changing the Role of Managers?

Managers are becoming the AI pressure point. 80% expect AI to reshape middle-management roles, and while 76% feel at least somewhat prepared to manage AI use in their teams, only 25% feel very prepared. That's a meaningful gap between general confidence and readiness for the specifics.

The hardest parts of managing AI use, according to respondents:

• Data security and compliance: 36%

• Managing overuse or poor use: 29%

• Knowing when human judgement is required: 29%

• Measuring productivity gains: 23%

• Setting expectations for quality: 21%

• Training the team: 13%

Notably, training the team ranks lowest, even though stronger training would likely ease many of the challenges ranked above it.

On the outlook for the role itself:

• Role changes, demand stays steady: 38%

• Reduced need for the role: 23%

• Increased pressure without more support: 14%

Hiring or upskilling managers for the AI era? Talent's permanent recruitment team can help you find leaders ready for it.

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How Is AI Reshaping Workforce Planning and Hiring?

Workforce planning is shifting, but most organisations are still focused on building capability rather than redesigning work outright. The top responses to AI in workforce planning:

• Upskilling existing employees: 44%

• Reducing manual or repetitive work: 37%

• Not yet changed workforce planning at all: 26%

• Redesigning roles or workflows: 22%

• Hiring AI specialists: 22%

• Using AI directly in hiring or workforce planning: 16%

• Changing the skills they hire for: 16%

Grouped by maturity, organisations sit at different stages:

• Capability building: 60%

• Work redesign: 59%

• Hiring strategy shifted: 38%

• Using external partners to accelerate the transition: 14%

See how Talent partners with organisations on workforce redesign and AI-era hiring strategy.

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Will AI Replace Jobs in Australia and New Zealand?

The following data is sourced externally, not from Talent's 2026 ANZ survey, and is included here for benchmarking context only.

Talent's survey didn't set out to measure job displacement directly, but it's the question most readers will have, so here's what the wider research says:

• The Parliamentary Library of Australia notes that occupational exposure to AI is highest among managers, business professionals, and IT professionals.

• The same analysis cites a 2023 McKinsey report finding that low-paid workers (clerical, retail, and administrative staff) were around 14 times more likely to lose their job to AI than higher-paid workers.

• ADP's People at Work 2025 research found only 11% of Australian workers strongly believe AI will positively impact their role in the coming year, lower than the Asia-Pacific (16%) and global (17%) averages.

• The same ADP research found 9% of Australian workers fear AI could replace their job outright.

The picture that emerges isn't simple job loss or job creation: it's a redistribution of tasks within occupations, with the sharpest impact concentrated in lower-paid, more routine roles, and genuine uncertainty even among workers whose roles are considered safer.

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