Building future-ready AI infrastructure: how organisations can thrive in an AI-driven future
Australian organisations are well-placed to avoid strategic missteps, if they consider four critical factors before making strategic AI infrastructure investments.
AI adoption is accelerating globally, revealing a host of previously unknown challenges. As a smaller economy, Australia is unlikely to lead the adoption pack. But as a technologically advanced and educated society, our organisations can learn from the mistakes of others to become the best at implementation.
Recent analysis from Deloitte shows organisations worldwide are grappling with architectural challenges as they scale AI programs and transformations. These challenges include cost pressures of scaled AI workloads and difficulty adapting existing cloud and infrastructure strategies in an AI-dominated landscape.
Australian organisations are well placed to avoid these strategic missteps, if they consider four critical factors before making strategic AI infrastructure investments such as LLM selection or AI infrastructure investment.
1. Architectural choices matter
Deloitte’s research shows choices of infrastructure strategy, cloud platform, enterprise software, and model selection are interdependent, and must be made jointly. These selections ultimately impact the drivers of not just cost, but also overall AI effectiveness as architecture choices impact the availability of models.
Patterns of AI adoption globally show that most organisations start their AI journey with a phased approach, by leveraging existing public cloud architectures to access leading AI services. This provides an effective way to build out AI capability at low incremental cost to understand patterns of demand.
As AI demand scales it becomes apparent that organisations must be more selective with placement of AI workloads across environments and models, so it is best to plan for eventual hybrid or private infrastructure usage – knowing what the total cost of ownership (TCO) tipping point is, while being able to leverage existing investments in public cloud architecture that provide access to world leading frontier models.
Global adoption indicates a trend of creating a ‘best of breed’ approach providing choice between public cloud and private dedicated services, such as owned infrastructure or Neocloud providing GPU-as-a-service.
2. Total cost of ownership
Deloitte’s global research indicates that when cloud computing costs reach 60-70 per cent of the total cost of purchasing dedicated systems, organisations are best served to consider a ‘best of breed’ approach. This allows for lower-complexity AI needs to be funnelled to cheaper models and platforms, following major players like OpenAI.
Australian organisations should model total cost scenarios early, considering not just initial deployment costs but long-term operational expenses.
Experienced organisations are navigating this complexity by modelling workload costs across multiple platforms, providing visibility into future costs and guiding AI ‘workload placement’ in a ‘best of breed’ manner.
3. Data sovereignty
Australia’s regulatory landscape, including the Privacy Act and upcoming reforms, creates specific data sovereignty requirements that may result in architectural implications to AI platforms.
This consideration becomes particularly critical when selecting LLM providers, as many global services may process Australian data in offshore locations in default configurations. Organisations should establish clear data sovereignty policies before selecting infrastructure partners, to ensure compliance with current and anticipated regulatory requirements. This is of particular importance to organisations operating under stricter controls in sectors such as healthcare and government.
4. Cybersecurity posture
Use of AI and agentic solutions introduces new and complex risks to cyber security that must be considered early in adoption cycles. In addition, Australia’s unique cyber security landscape – including requirements under the Security of Critical Infrastructure Act, the Defence Industry Security Program and guidelines from the Australian Cyber Security Centre – demands careful consideration of AI infrastructure security implications.
Global patterns show that organisations often underestimate the security complexity introduced by AI systems, particularly in hybrid and edge computing scenarios.
Australian businesses should evaluate how AI infrastructure choices align with their existing security frameworks and regulatory obligations, including incident reporting requirements and critical infrastructure protection measures.
Australian organisations must balance the urgency of AI adoption with the strategic importance of infrastructure decisions that will impact organisations for years to come. By carefully considering total cost, data sovereignty, architectural alignment, and cyber security requirements, Australian organisations can build AI infrastructure that serves both immediate needs and long-term strategic objectives.
Building these requirements into initial infrastructure decisions can help avoid costly mitigations and help accommodate changing business needs, regulatory requirements, and technological advances without requiring complete system overhauls.
The global AI infrastructure landscape continues to evolve rapidly, but the fundamental principles of strategic planning, regulatory compliance, and architectural thoughtfulness remain constant. Australian organisations that apply these principles while leveraging lessons from global experience will be best positioned to thrive in an AI-driven future.
Jason Hutchinson is Deloitte Australia National Lead Partner of Engineering, AI & Data and James Allan is Deloitte Australia Lead Partner of Engineering.
 
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Disclaimer
This publication contains general information only and Deloitte is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services. This publication is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision or taking any action that may affect your business, you should consult a qualified professional adviser. 
Deloitte shall not be responsible for any loss sustained by any person who relies on this publication. 
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Originally published as Building future-ready AI infrastructure: how organisations can thrive in an AI-driven future
