AI adoption is no longer optional, it is a strategic priority for enterprises seeking measurable ROI and competitive advantage. Around the world, organisations are rapidly building high-density data centres to power AI workloads, while governments and global alliances are investing in next-generation infrastructure.

At the enterprise level, public cloud vendors are aggressively expanding capacity for AI services. However, many organisations, particularly in defence, government, and financial sectors, face strict data residency, compliance, and

security requirements. For them, private cloud has become a critical enabler, delivering the control, sovereignty, and scalability needed to run AI workloads securely and cost-effectively.

Many enterprises cannot fully utilise public cloud services due to the sensitive nature of their work or data. Defence, government, and financial organisations often require their data to remain on-premises or in tightly managed colocation facilities to maintain security and complianc

According to a 2025 Broadcom survey of 1,800 senior IT leaders, 55 per cent of enterprises globally are investing in private infrastructure for AI workloads. IDC predicts that over 75 per cent of enterprises in Asia Pacific will run significant workloads on private clouds within a “hybrid, fit-for-purpose infrastructure.” In the Middle East and Africa, the private cloud market is growing at a CAGR of 28.77 per cent between 2023 and 2028, according to MarketNtel Advisors.

Delivering efficiency, scalability, and on-demand growth in private data centres is complex. Infrastructure capacity is finite, and predicting growth trajectories is difficult. The starting baseline is often conservative, which makes forecasting for future success challenging.

Trusted technology vendors and systems integrators play a critical role in this journey. Infrastructure companies are developing AI factory capabilities to support customers’ on-premises requirements, help define use cases, right-size infrastructure, and tackle the most challenging aspect, predicting future scaling needs.

At the same time, hyperscale providers are bringing their global cloud capabilities into enterprise and colocation data centres with “air-gapped” and “sovereign” on-premises solutions. These extend GPU deployment capacity and enable organisations to accelerate their AI agenda while maintaining data control.

Choosing between “build your own” or going with a hyper-scale solution in your data center / collocation premises depends upon:

1. the use case

2. the ecosystem of software partners and integrations required

3. inter-operability and dependency on your existing workloads.

4. speed to market and functional deployment

The key to success with these deployments lies in the following principles, not matter which route you take from build your own or hyper-scale supported initiatives.

1. Start small with high-impact use Cases. Choose use cases with a high probability of success that can deliver value quickly and build confidence.

2. Collaborate with partners. Work closely with your provider ecosystem to determine your current infrastructure baseline and plan for capacity headroom should adoption accelerate.

3. Review and adjust regularly. Establish quarterly or periodic review cycles with stakeholders to revisit the roadmap, scale successful initiatives, and pivot away from what is not working. Plan ahead for scaling logistics, which may include smart contracts with providers to pre-stock critical infrastructure for rapid deployment.

4. Avoid Oversizing. Overprovisioning can be costly and difficult to scale down in dedicated environments. Start lean and expand as needed, always returning to first principles when in doubt

5. Secure Flexible Contracts. Negotiate long-term, adaptable agreements with partners that allow changes in direction and pace as business needs evolve.

It's a continuous process which needs to be honed as we go along and most importantly a transparent partnership with the right strategic & trustworthy partners for your journey to realize the potential of AI deployments for your enterprise.

In the end the most important point is to drive measurable ROI from AI initiatives and have the flexibility to change directions when needed.

Putting this into practice needs your undivided attention, focus and commitment to drive AI adoption in your enterprise.

So connect with your trusted partners and discuss the possibilities of smart contracts to establish your hosted private infrastructure to scale and deliver your critical use cases