Australia Leads AI Agent Adoption at 46%, but Managers Pay the Price

Australia ranked first among seven surveyed markets for AI agent adoption, with 46% of Australian directors and senior managers using AI agents (autonomous software tools that complete multi-step work with limited intervention) for complex tasks, against a global average of 38%. The figure comes from Nielsen research commissioned by monday.com, published November 11, 2026, which surveyed 1,701 Directors and Senior Managers at companies with at least 500 employees across the US, UK, Australia, Germany, France, Brazil and Singapore.

The adoption headline carries a second number that reframes it: 58% of Australian respondents expect to manage more agents than people within the next 12 months. That is the scale of the shift now landing on managers' desks in one of the world's fastest-adopting AI markets.

monday.com coined a term for what the data shows: "agent sprawl" — a build-up of AI agents, software tools and automated hand-offs inside organisations without clear ownership, controls or measures of value. The survey results, the company argues, demonstrate that deploying agents is not the same as reorganising work around them.

What is happening to managers' time?

The burden numbers are the sharpest in the dataset. Some 59% of Australian leaders said they now spend more time reviewing and guiding their team's output since AI use increased — the highest result of the seven markets. A third said AI adds hours to their working day.

In Australia, 62% of respondents said identifying and testing where AI creates value requires more effort than it saves. That finding points to a gap between adoption and return: the technology arrives faster than the workflows designed to exploit it.

The extra workload, according to the research, comes from tasks surrounding the technology rather than from operating the tools themselves. Managers still need to decide what work to delegate, provide context, connect systems, check results and correct errors — while remaining responsible for the final output.

Why is software complexity growing alongside AI?

Australian respondents reported measurable changes in their software environments, and every result sits at or near the top of the seven-market table:

• 65% said they are using more software tools since adopting AI — the highest share among the seven markets.
• 58% said their tools have become more interdependent.
• 36% said manual steps in workflows have increased.

That pressure persists despite high self-reported AI maturity. More than two-thirds of Australian respondents described their teams as advanced or expert AI users, and 69% said their organisation provides sufficient AI training. Confidence, in other words, has not translated into lighter workloads.

Gavin Watson, Regional Director, AI & Industries at monday.com, said the problem lies in how adoption is measured: "Agent count is fast becoming a vanity metric. Giving one employee ten agents doesn't make them ten times more productive if they inherit ten streams of work to supervise. Businesses need to measure whether the entire workflow moves faster, with less rework and fewer hand-offs. Every agent also needs a job description, a defined outcome, its own permissions, a clear point of human escalation and one accountable owner. Without that discipline, agent adoption simply creates more work the organisation can't see."

How are managers dividing work between people and AI?

The survey documents a decisive shift in task allocation. Only 14% of Australian Directors and Senior Managers said they mainly assign tasks to people and use AI as a secondary tool. The distribution now tilts the other way:

• 45% said they reserve work requiring human judgement for staff and shift remaining tasks to AI.
• 26% said they assume AI will handle most execution, with employees focusing more on editing and strategy.
• 14% still lead with people and treat AI as secondary support.

As that balance shifts, accountability concerns rise. Nearly half of respondents — 44% — said they fear agents will not receive enough human oversight or control. Almost one in three, or 31%, said they worry about being held personally accountable for an agent's work. A large majority, 84%, said good management now requires different skills in the age of AI.

The issue extends beyond individual firms. Australian policymakers and public agencies are examining how organisations use AI systems and how much autonomy those systems should have, with closer scrutiny of agent access, human oversight, productivity effects and workforce implications. The survey lands in the middle of that policy conversation.

How is AI changing performance reviews?

The research suggests AI is restructuring how employers assess staff. Four in five Australian organisations surveyed said they have changed the way they evaluate employees since adopting AI. Of those, 37% said they have significantly changed their evaluation criteria — again the highest result among the seven markets.

Nearly six in ten respondents said an employee's original contribution has become harder to evaluate when work passes through several AI tools or AI-supported processes. A separate finding compounds the recursion: 40% of organisations now use AI to draft performance reviews.

Watson said those changes risk making individual judgement less visible inside businesses: "Agent sprawl makes work harder to coordinate and talent harder to see. When several agents help research, draft and assess the same output, polish and speed stop being reliable evidence of ability. Businesses risk rewarding the best-presented work rather than the strongest judgement, while overlooking the people who set the direction, challenged the answer, caught the mistake and took responsibility for the result. Unless performance systems capture those decisions, companies will lose sight of where human capability actually sits."

Why the numbers matter

The dataset captures a market at a specific inflection point: adoption is running ahead of management practice. Australia leads the seven markets on agent usage, on tool proliferation, on supervision hours and on changed evaluation criteria — and it also posts the highest share of respondents saying AI costs more effort than it saves, at 62%.

For enterprises, the actionable question the survey raises is the one Watson articulates: whether the entire workflow moves faster, with less rework and fewer hand-offs. For policymakers weighing agent oversight rules, the 44% of managers already worried about insufficient human control provides an early signal of where regulation and operational reality may collide. The 12-month window in which 58% of Australian managers expect to supervise more agents than people will test whether governance, measurement and performance systems can keep pace with deployment.