Australian organisations are expected to spend more than A$33.6 billion on public cloud services in 2026, an increase of 17.9% from 2025, according to the latest forecast from Gartner.
Software-as-a-service (SaaS) remains the largest spending category for Australian organisations in 2026, forecast to reach almost A$16.4 billion.
This 13.8% increase marks slower growth over 2025 as the market matures, with organisations prioritising license optimisation, slower seat growth and tighter application portfolio scrutiny.
Cloud System Infrastructure Services (IaaS) is the fastest growing category (24.1%) year over year in terms of spending, while Cloud Application Infrastructure Services (PaaS) is also seeing strong growth with forecasted growth of 20.9%.
Australian Public Cloud Services End-User Spending, 2025-2026 (Millions of AUD)
|
Segment |
2025 Spending |
2025 Growth (%) |
2026 Spending |
2026 Growth (%) |
|
Cloud Application Infrastructure Services (PaaS) |
8,265 |
23.1% |
9,996 |
20.9% |
|
Cloud Application Services (SaaS) |
14,386 |
15.0% |
16,377 |
13.8% |
|
Cloud Desktop-as-a-Service (DaaS) |
141 |
8.9% |
155 |
9.7% |
|
Cloud System Infrastructure Services (IaaS) |
5,717 |
23.5% |
7,092 |
24.1% |
|
Total |
28,508 |
18.9% |
33,619 |
17.9% |
Source: Gartner (May 2026)
"AI‑driven demand for high‑performance cloud infrastructure is changing how Australian organisations are prioritising cloud spending this year,” said Adrian Wong, Director Analyst at Gartner.
“While AI compute demands are driving rapid IaaS growth, the ultimate goal for Australian organisations is business value. As the market shifts from early AI experimentation to real-time inference and agentic AI, organisations are relying heavily on robust PaaS environments to manage autonomous workflows and integrate them into core applications.”
Wong said that the increasing focus on cloud efficiency this year is also underpinning AI infrastructure strategies.
“There’s a shift toward inference-optimised approaches as organisations fine-tune smaller domain-specific models instead of relying on larger general purpose LLMs," he said.
"Many are turning to hybrid cloud architectures to push this processing to the edge, which lowers cloud costs while still supporting automation at scale.”




