Australia is working harder than ever, and getting less in return.

Labour productivity growth has fallen to just 0.3% in the past year, even as total hours worked rose by 2.2%. Our 20-year average has more than halved, from 1.7% to 0.8%, the weakest performance in over 50 years. New Zealand tells a similar story. For CIOs and technology leaders, this is not an abstract economic problem. It is playing out right now, across every team, every system, every organisation you lead.

monday.com’s independent research with EnterpriseWorks, spanning 400+ knowledge workers and senior leaders across ANZ, points to a clear conclusion: productivity isn’t stalling because people aren’t trying hard enough. It’s stalling because of how work is designed.

The problem isn’t effort. It’s design.

The research reveals a striking 32-point gap between strategic clarity and execution. Eighty-three percent of employees understand how their work connects to organisational priorities. Yet only 51% say their organisation actually organises work around those priorities. The gap between intent and reality is being filled with something costly: manual coordination, redundant meetings, and fragmented data.

Knowledge workers are spending 45% of their working week in meetings, with fewer than half agreeing those meetings are necessary or move work forward. Thirty-eight percent report significant time lost to manual tasks. Forty-two percent spend meaningful time creating or updating reports and presentations, rising to 62% for senior leaders. These are not inefficiencies at the margins. They are systemic.

The AI opportunity and its limits

Artificial intelligence represents a genuine inflection point. The forecast productivity upside is $116 billion for Australia and $76 billion for New Zealand. But the research is clear: that value will not materialise automatically.

Today, only 51% of knowledge workers have AI access and use it regularly. Among those whose teams actively use AI, 71% say it has meaningfully reduced manual work. The tools are proving their value, but adoption is uneven, skills are lagging, and most organisations have not redesigned workflows to make room for what AI frees up. Scaling AI without connected data, standardised processes, and practical capability-building will not close the productivity gap.

Three shifts for CIOs to lead

The research points to three areas where technology leaders have direct influence. First, connect strategy to execution by making priorities visible and measurable, not just communicated. Second, simplify and connect systems so that people stop being the integration layer between disconnected tools and data. Third, build AI capability in the flow of daily work, and deliberately reinvest the capacity it creates into higher-value outcomes.

The organisations pulling ahead are not those doing more. They are those designing better: fewer priorities pursued with more focus, connected systems that surface the right information at the right time, and teams with the skills and space to use AI well.

The productivity dividend is real. But it will only be unlocked by leaders who are willing to redesign how work gets done, not just accelerate the way it is done now.

Based on findings from The Workforce Productivity Report, EnterpriseWorks, 2026.