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.