Knowledge Hub Australia

The world is entering a defining moment for digital infrastructure. Artificial intelligence has moved from experimentation to ubiquity, and with it, a new operational paradigm is taking shape — one where agents rather than applications become the primary engines of digital value creation. This is the dawn of the agentic AI era, and its success depends on one thing above all else: robust, intelligent, and scalable infrastructure.

Australia’s technology leaders have reached a clear consensus on AI’s strategic importance. Nearly three-quarters of ANZ organisations now rate it a core business priority, with AI and automation ranking as the second highest digital transformation objective for 2025, behind only cybersecurity. And yet IDC’s 2025 ANZ Digital Ecosystem Survey of 440 organisations found, in a separate question, that 73% of respondents agree their AI investments have not delivered expected returns.

The way organizations deliver applications has undergone a significant shift over the past few years. Pre-pandemic, virtual desktop infrastructure (VDI) was often seen as a niche solution for specific use cases. Post-pandemic, it has become a cornerstone of modern IT strategies, driven by the rise of remote work and the need for secure, scalable access to business-critical applications.

AI is reshaping enterprise economics, and it’s happening faster than most organisations can keep up with. On one side, investment in AI is accelerating across models, compute, and data. On the other, labour is shifting as manual work declines and roles evolve. The expectation is clear: productivity should rise. But it isn’t that simple. Right in the middle of these changes is a critical gap, organisations don’t actually understand productivity.

For decades, service management has run on the same cycle: something breaks, a ticket gets filed, a human resolves it. And AI is making that loop run exponentially faster.

But, what if we could do things differently? That’s what Venkat Venkataraman, Freshworks VP of AI products, believes is possible. His perspective is that real transformation isn’t a faster version of the old model, but a different one, where problems are caught and neutralized before an employee ever notices, and where IT’s value gets measured by what never broke rather than by how fast the break got fixed.

The question enterprises are asking has changed. It’s no longer whether to deploy AI agents — it’s why so few deployments ever move beyond the pilot stage. IDC projects that the number of actively deployed AI agents will exceed 1 billion worldwide by 2029 — 40 times more than in 2025.

Somewhere in most organisations an application development project sits at ninety percent. A small team built it quickly with AI writing much of the code, a demo went well six months ago, and nothing has moved since. What remains is everything that must be reviewed and confirmed before anyone lets it near production.

Hybrid work has changed where people collaborate, but the office remains important for conversations that benefit from shared focus and human connection. Meeting rooms therefore play a central role, shaped less by the technology they contain than by how easily people can use it.

The most effective collaboration technology fades into the background. When people can join, share, and contribute without stopping to decipher the room setup, attention stays on the conversation. Friction has the opposite effect: it delays meetings, weakens confidence, and encourages people to find workarounds.

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.

As digital transformation accelerates, organizations are confronting a growing strategic imperative: establishing digital sovereignty. More than a regulatory concept, digital sovereignty represents the ability of enterprises and nations to control and protect their data, infrastructure, and software in accordance with local laws, values, and operational requirements. In practice, it means understanding precisely where data resides, who has access to it, and how technological dependencies influence business continuity, competitive advantage, and customer trust.

A vendor deadline can create urgency. It cannot tell a CIO whether the business is ready to change. Yet support milestones, shifting commercial models and product roadmaps can push organisations towards major technology commitments before the business case is clear. The systems at the centre of those decisions still run payroll, close the books, manage supply chains and serve customers. Their value does not disappear when a support policy changes. For CIOs, the challenge is preserving that value while creating room for what comes next. Third-party software support can help organisations continue running existing enterprise systems with independent expertise outside the vendor’s prescribed upgrade roadmap. That can give leaders more flexibility over when, where and why they modernise. It also creates an opportunity to reassess whether the proposed roadmap still serves the business, explore alternatives and choose a pace of change the organisation can absorb.

Most boardroom conversations about AI are still framed as a cloud story: which model, which hyperscaler, how much compute. But the decisions that actually move the needle for Australian businesses rarely happen in the cloud. They happen on the factory floor, in the branch, on the network edge, in the field — the moment a customer is standing in front of a teller, a truck is rerouted, or a fault is detected on a substation. Agentic AI’s real value shows up exactly there, at the point of action, not in a dashboard reviewed after the fact.

For years, IT teams have worked towards the goal of preventing disruption before employees experience it. The challenge was never a lack of ambition, but a lack of technology capable of continuously understanding what was happening across complex IT environments and acting on that insight in real-time. Agentic AI now offers the possibility of finally closing that gap.

Almost every organisation I speak with are using GenAI, and most have tried agents. Far fewer can show value. With AI now built into most software and hardware, access isn’t the issue. The value comes from reimagining the operating model, the work and what people do.

For two decades, virtualisation was the quiet constant of enterprise IT. It was rarely questioned because it rarely needed to be. That has changed. Licensing restructures, bundled subscriptions and rising renewal costs across the VMware ecosystem have forced many organisations to confront a platform they had long treated as settled.