Nine In Ten Australian Workers Use AI On The Job But Only One In Ten Say It Has Improved Performance

Australian workers are adopting AI at a higher rate than their counterparts in the United States and United Kingdom, but most organisations are failing to convert that usage into measurable business outcomes, according to new research that quantifies the hidden labour involved in making AI tools usable.

The Work AI Index, published by Glean’s Work AI Institute – a research collaborative involving academics from Stanford University, UC Berkeley and Harvard – surveyed 6,000 full-time digital workers across the US, UK and Australia, including 1,500 in Australia.

The headline finding is stark: 90 per cent of Australian digital workers now use AI at work, compared with 84 per cent in the US. But only 10 per cent say AI has significantly improved their organisation’s performance, behind both the US at 12 per cent and the UK at 18 per cent.

The productivity paradox

The report identifies what it calls a new productivity paradox. AI is making individual tasks feel faster, but the cumulative burden of supplying context, checking quality and stitching together disconnected tools is falling on employees in ways that are not being recognised or accounted for.

Australian workers report that AI already automates 27 per cent of their work output and expect that figure to rise to 34 per cent over the next year. But much of that value is being absorbed by what the report terms “botsitting” – the unrecognised effort of prompting, correcting and redoing AI-generated work.

Workers spend an average of 6.5 hours per week on botsitting, close to a full working day. Roughly four in ten say AI sessions fail outright, requiring a restart, substantial rework or a reset back to zero.

Forty-three per cent of Australian workers report feeling worn out by AI tools, compared with 33 per cent in the US.

A quality-control problem

Beyond the time cost, the report points to a growing quality issue around AI-generated output that employees have not verified, do not fully understand or cannot stand behind.

Seventy-seven per cent of Australian AI users admit to at least one unchecked AI-output behaviour, a higher rate than both the UK at 70 per cent and the US at 64 per cent.

Forty-five per cent say they have delivered AI-generated work they could not fully explain. And 36 per cent have blamed AI for a mistake that was actually their own.

Seventy-three per cent of Australian workers have corrected or redone AI-assisted work in the past month, with 30 per cent doing so at least weekly.

Dr Rebecca Hinds, Head of the Work AI Institute at Glean, argued that adoption alone is not producing the results organisations expect.

“Too many companies are treating AI adoption like a vanity metric – more seats, more prompts, more usage,” Hinds explained. “But adoption alone doesn’t create transformation. The state of AI at work in Australia points to a bigger opportunity: when organisations pair AI enthusiasm with the right operating discipline, they can turn productivity gains into lasting business impact instead of losing them to rework, cleanup and unverified output.”

AI moving into high-stakes decisions

The survey reveals that AI is not confined to routine productivity tasks. It has moved into areas with material consequences for employees.

Seventy-four per cent of Australian workers have used AI as a notetaker in meetings. Sixty-six per cent have had AI facilitate a meeting. And 58 per cent have sent a digital twin to attend in their place.

AI is also being applied to workforce decisions. One in three Australian workers say AI is already being used in performance evaluations. One in five say it is being used in termination decisions, and 35 per cent expect it to be used in that context within a year.

Workers are becoming the integration layer

More than half of Australian workers – 56 per cent – say important information they need to do their job is not connected to or accessible through AI tools. The same proportion say vendor contracts are limiting how effectively their organisation can use AI, compared with 47 per cent in both the US and UK.

In these context-poor AI environments, the consequences are measurable. Workers are 112 per cent more likely to feel worn out by AI, 81 per cent more likely to deliver work they cannot explain and 90 per cent more likely to use unapproved tools.

The implication is that when enterprise AI tools lack access to the right organisational data, employees are forced to act as the integration layer themselves – manually supplying context, cross-referencing information and working around gaps in what the AI can see.

A workforce risk, not just a productivity issue

The report frames the strain on workers as a retention risk, not just a productivity drag.

Frequent botsitters in Australia are 59 per cent more likely to be actively looking for another job. Workers who admit to shipping unchecked AI-generated work are 3.4 times more likely to be actively job-hunting.

Dom Price, Work AI Institute Expert and Work Futurist, pointed to the gap between the speed of AI adoption and the pace of organisational change.

“AI is different because it doesn’t just ask organisations to adopt another tool – it asks them to change how work gets done,” Price told media. “Right now, too many companies are trying to push AI-speed change through legacy-speed systems.”

“The winners will be the ones that build the human infrastructure around AI: clearer decision-making, better context, stronger governance and teams that know when to trust AI, when to challenge it and when to keep the work human,” he continued.

What the organisations pulling ahead are doing differently

The report draws a distinction between organisations that are seeing results from AI and those that are not, and the difference is not the volume of AI usage.

In what the report labels “transformative” Australian organisations, workers are more likely to say their employer provides sufficient AI training and support, regularly reviews AI policies, explains the rationale behind governance decisions, rewards AI skills and treats AI as an opportunity to redesign work rather than simply automate existing workflows.

The finding suggests that the next gap in enterprise AI is not adoption but the operational and managerial infrastructure around it – training employees on when to use AI and how to verify its output, treating workarounds as signals that official tools are falling short and building governance into daily decisions rather than treating it as a static policy document.

Methodology

The Work AI Index is based on a survey of 6,000 full-time digital workers conducted between December 2025 and January 2026, split across 3,000 respondents in the US, 1,500 in the UK and 1,500 in Australia. Digital workers are defined as full-time workers who perform most of their work on a computer or digital tools. The report also draws on analysis of anonymised, aggregated workplace AI interactions from the Glean platform.

Last Updated on June 13, 2026 by Nick Ross