Ready for what's next?

AI never stands still. Your IT needs to keep up.

AI is changing how organisations work and how IT infrastructure needs to perform, from AI-enabled workplace devices to servers, storage and data centre infrastructure.

Preparing for AI goes beyond investing in more powerful hardware. Businesses need the right technology, the flexibility to adapt as requirements change and a strategy to manage investments throughout their lifecycle.

CHG-MERIDIAN helps organisations source, finance and manage their technology infrastructure, supporting AI readiness while maintaining financial and operational flexibility.

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Why AI readiness matters

AI as a growth driver

66% of investors expect AI to increase productivity at the companies they invest in over the next 12 months.(PwC, 2024)

AI Readiness

71% of CEOs believe their technology operating models are not ready for AI and digital transformation. (Gartner, 2025)

AI investment challenges

50% of Infrastructure & Operations leaders cite lack of budget as a major challenge for AI adoption. (Gartner, 2025)

What does AI-ready IT Infrastructure require?

AI readiness requires infrastructure built to support how AI is used, processed and scaled. From workplace devices to computing power, storage and security, every layer needs to be considered as technology and business requirements evolve.

AI Workplace AI-enabled workplace devices are changing how employees work, with new processing capabilities supporting AI applications directly on the device. For organisations, the challenge is ensuring that workplace technology can support evolving AI requirements while remaining secure, manageable and cost-effective.

AI Servers AI workloads can require significant computing power, including high-performance servers and specialised processors such as GPUs. As demand grows and technology evolves, organisations need to plan infrastructure investments carefully, balancing performance, cost and the flexibility to adapt.

Storage & Security AI places increasing demands on data storage, networking and security infrastructure. Organisations need reliable, scalable technology to support growing workloads, protect sensitive information and maintain operational resilience.

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How can businesses invest in AI infrastructure while maintaining flexibility?

Assess: Understand the full cost of AI infrastructure

AI infrastructure investment goes beyond the initial purchase price. Deployment, maintenance, energy consumption, technology refresh and end-of-life management all contribute to the total cost of ownership.

Taking a lifecycle approach helps organisations make more informed investment decisions and plan for future requirements.

Modernise: Keep pace with evolving technology

AI technology is evolving rapidly, and infrastructure requirements can change as new applications and workloads emerge.

Flexible technology lifecycle models can help organisations plan equipment refreshes and adapt to changing performance requirements, without relying on rigid replacement cycles.

Optimise: Make better use of IT budgets

AI infrastructure can require substantial investment. Flexible financing and usage-based models can help organisations manage upfront costs and maintain capital for other business priorities.

The focus is on making technology investments more manageable throughout their lifecycle.

Scale: Adapt as AI requirements change

As AI projects move from initial testing to wider deployment, infrastructure requirements may grow or change.

Planning technology acquisition and financing around business needs can help organisations respond to changing demand while maintaining greater financial and operational flexibility.

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FAQs

What is AI-ready IT infrastructure?

AI-ready IT infrastructure provides the computing, processing, storage, networking and security capabilities required to support an organisation's AI workloads and use cases.

Requirements vary depending on the applications being used and whether AI processing takes place on devices, on-premises, in the cloud or across hybrid environments.

How does AI affect IT hardware requirements?

AI can increase demand for GPUs, NPUs, high-performance CPUs, memory and storage.

The specific requirements depend on the workloads involved. Some AI applications can run on existing infrastructure, while others require specialised hardware, additional computing capacity or upgraded workplace devices.

How can companies finance AI infrastructure?

Organisations can purchase AI infrastructure outright or consider alternative approaches such as leasing and usage-based financing.

The appropriate model depends on investment requirements, cash flow objectives, technology lifecycles and the organisation's financial strategy. Considering the total cost of ownership can help businesses evaluate their options.

Why are flexible IT usage models relevant for AI?

AI technology and business requirements continue to evolve, making long-term infrastructure planning more challenging.

Flexible usage models can help organisations manage investment costs, plan technology refreshes and adapt their infrastructure over time, subject to the terms of the agreement.