Australia is moving faster than global peers when it comes to implementing generative AI strategies and containerising applications, but skills shortages and security fears could hinder progress.
This according to the latest report from Nutanix which is based on a study conducted by Vanson Bourne in late 2024.
The United Kingdom-based research firm surveyed a total of 1,500 IT and DevOps/Platform Engineering decision-makers around the world.
Respondents were based in Asia-Pacific-Japan (APJ), North and South America; and Europe, the Middle East and Africa (EMEA).
Results from Australia-based respondents show that generative AI momentum is striking.
More than 80% of organisations have a generative AI strategy in place, and 61% are actively implementing it, six points ahead of the global average (55%).
Common use cases include customer support solutions (55%) and code generation tools (48%).
Yet, despite this rapid uptake, only 53% of Australian respondents feel they have the necessary skills to support cloud-native apps/containers, a key ecosystem for generative AI applications.
This is 10 points lower than the APJ average of 63%. Further, 83% say their infrastructure needs at least moderate improvement to support these workloads.
Michael Alp, managing director, Nutanix ANZ said the findings highlight Australian organisations aren’t short on ambition, but there’s a growing gap between strategic intent and operational execution.
“The smartest move we’re seeing right now is organisations upskilling the engineers and developers already on the ground for the new cloud-native world,” said Alp.
“These teams then take their new cloud-native skills, along with institutional IT knowledge, to make smarter infrastructure decisions that keep innovation moving, not breaking,” he added. “It’s a faster, more sustainable way to build the future and overcome the pervasive local skills gap.”
Meanwhile, 100% of surveyed organisations in Australia are at least in the process of containerising their applications, with nearly a third (31%) stating all newly developed applications are containerised. This is significantly higher than the APJ average of 22%.
AI is driving this containerisation surge with three quarters (75%) of Australian respondents citing generative AI applications as the most containerised applications in their organisation.
“Containerisation is becoming the default, not the upgrade.That tells us it’s already embedded in how teams are thinking and delivering from day one,” Alp said.
“The flip side of this shift, as is clear in the data, is some organisations may struggle to drive their generative AI momentum forward, as they lack the skills, structure, and scale needed to turn all this progress into long-term performance,” he added.
Key findings from this year’s Australian results also show that data privacy action lags behind intent.
While 98% of Australian respondents agree security and data privacy is a top priority when implementing generative AI, only 27% identify it as the most important data-related consideration once the work begins.
Also, generative AI ROI expectations grow with time. While 38 % of Australian respondents expect generative AI projects to break even or incur losses in the first year, that figure drops to 28 % over the next one to three years.
This suggests a shift in mindset among decision-makers towards a longer-term view of success, measuring ROI over multiple years rather than chasing short-term wins.
Further, MLOps platforms emerging as innovation enablers. More than half (54%) of respondents say their organisation is using third-party machine learning operations (MLOps) to accelerate building, training, and deployinggGenerative AI without having to build complex infrastructure from scratch.
In doing so, organisations are creating faster feedback loops, reducing friction, and pushing Generative AI solutions into production more quickly. But, it also suggests organisations are increasingly leveraging managed platforms to offset internal capability gaps.
