Australian employees are losing half their week to admin

Ask any Australian professional how work is going, and ‘flat out’ is usually part of the answer. It’s a badge of honour in this country to be run off your feet, seen as proof of contribution and demand. But new research from Workday is prompting HR and people leaders to look past how much activity fills the working day and scrutinise what that time is actually buying the business.

Roughly three in 10 ANZ employees now lose more than seven hours a week on unfulfilling copy/paste work and manually shuttling information between disconnected systems.

The hidden cost of the ‘copy/paste’ workday

At the same time, Workday research disproves the instinctive assumption that when productivity stalls, people have disengaged. An overwhelming 96% of ANZ employees report a positive experience at work. They are also notably optimistic about the role of AI in their day-to-day roles.

Three-quarters of respondents describe friction created by administrative tasks as a significant daily obstacle, and 63% say they spend at least half their working time on this kind of manual translation work rather than on the roles they were actually hired to perform.

Australia’s engaged, willing employees are quietly absorbing an operational failure through effort and attention. One IT director quoted in the research summed up the toll plainly: constantly fixing inconsistent data and chasing approvals keeps people occupied without ever feeling like genuine progress.

Bolt-on AI isn’t closing the gap

AI adoption alone has not been able to resolve the issue because most deployments sit at the edges of work rather than inside it. The output still has to be manually collected, checked and carried to the next system by a person.

Only 30% of ANZ organisations have embedded AI directly into core workflows, rather than adding it on top of and around existing systems. The consequences show up not just in time but also decision quality: 73% of employees say decisions stall when information is missing or unclear, and 64% report regular disagreement within teams over whose figures are correct.

What’s actually working

The organisations pulling ahead are the ones integrating AI into the systems already running the business such as payroll, approvals, forecasting and onboarding, rather than treating it as an add-on. Employees in this group are using AI agents to monitor performance metrics, manage onboarding, route cross-departmental approvals and support budgeting.

For teams under pressure to justify AI investment, the evidence points to a clear priority order. The return lies in identifying where work genuinely breaks down between systems and closing that specific gap with AI that has real access to core data and workflows.

Left unaddressed, this is a cost that shows up later, in attrition and disengagement among the very employees an organisation can least afford to lose.

Four steps organisation leaders should take now

Getting the foundation right requires organisations to bring its own data to the table:

1. Audit where the hours are actually going: Most organisations track productivity through output metrics, not through where employees’ time is genuinely being spent. Pulse surveys, time-use studies or simple team interviews will usually surface the ‘copy/paste’ tasks eating into the working week faster than any system log will.
2. Bring workforce experience data into technology decisions: Too many AI and systems investment decisions are made by IT and finance alone, with HR consulted only on rollout and change management. HR leaders should be pushing to get employee experience and workload data into the business case itself, before the tool is chosen.
3. Ask harder questions of technology partners: Before approving another point solution, HR should be pressing vendors and internal IT on a specific question — does this tool sit inside the core workflow, with real access to the underlying data, or is it bolted on, generating more output for someone to manually move? The answer determines whether the investment reduces workload or simply adds to it.
4. Make workload relief part of the retention conversation: Exit interviews, engagement surveys and stay conversations should be explicitly probing for administrative burden and system friction, not just satisfaction and pay. This is where the earliest warning signs of quiet attrition will show up, well before resignation numbers move.
5. Protect the goodwill that’s currently propping up the system: Employees are absorbing this friction because they’re engaged, not because it’s sustainable. HR leaders who can show visible progress on removing that burden will be the ones who convert current goodwill into lasting retention, rather than watching it quietly run out.

The organisations that treat this as a genuine HR and operating-model priority, not just a technology upgrade, will be the ones best placed to hold on to their most capable people through the next phase of AI adoption.

Image credit: iStock.com/Pekic