Why AI success in Africa hinges on power infrastructure — Gary Chomse

As AI adoption accelerates across Africa, the infrastructure supporting it must evolve just as quickly.

In this interview with Nairametrics, Gary Chomse, Regional Director for Central and Southern Africa, explores why power, cooling and compute must now be treated as a connected ecosystem.

He also shares insights on building resilient infrastructure amid power constraints, the rise of liquid cooling and sovereign data infrastructure, and how organisations in Nigeria can prepare today for the demands of tomorrow’s AI workloads.

Nairametrics: Why is power infrastructure becoming just as important as the AI technology itself?

Gary Chomse: AI is changing the demands placed on digital infrastructure. Previous generations of data centres were designed around relatively stable workloads, but AI applications require significantly higher power densities and can experience rapid fluctuations in energy demand. In many cases, the challenge goes beyond delivering more computing capacity; it also means that sufficient power needs to be delivered reliably and efficiently to support those workloads.

As graphics processing units (GPUs) and high-density AI clusters increase power density, data centre operators must manage three critical pressures:

• Concentrated loads: Managing extremely high-density footprints and highly dynamic power variations.
• Continuous availability: Supporting power continuity where even micro-outages can impact AI model training and performance.
• Environmental responsibility: Improving energy efficiency and optimising Power Usage Effectiveness (PUE) while scaling operations.

These changes make traditional, silo-based approaches to power distribution and management insufficient, requiring operators to adopt an integrated ecosystem where the power train acts as a coordinated system rather than a collection of isolated parts.

As organisations across Africa explore AI opportunities, infrastructure readiness will become a critical success factor. Power systems, cooling technologies and energy management platforms must work together seamlessly to support increasingly demanding AI workloads.

Nairametrics: Many African countries, including Nigeria, continue to face power reliability challenges. How can organisations prepare for AI adoption while operating within these constraints?

Gary Chomse: Infrastructure planning needs to be approached strategically from the outset if possible. Organisations should focus on building resilient, energy-efficient architectures that can support future growth while accommodating local power realities.

This means investing in modern power management systems, improving energy efficiency, adopting advanced cooling technologies and putting in place appropriate backup and redundancy capabilities. It also means taking a holistic view of infrastructure, recognising that power, cooling and IT systems are no longer separate considerations.

At the same time, organisations also need to consider the broader regulatory landscape. Recent measures by the Central Bank of Nigeria (CBN), including the requirement for payment transaction data to be stored locally from 2027, reflect a growing emphasis on data sovereignty and domestic digital infrastructure. As more organisations invest in local data hosting to meet these requirements, deploying facilities with resilient power, cooling and energy management capabilities will become increasingly important.

Nairametrics: How do you see AI changing data centre design across Africa over the next few years?

Gary Chomse: We expect AI to drive one of the most significant transformations the industry has experienced in decades. Data centres will increasingly need to support higher rack densities, more advanced cooling technologies and significantly greater power capacity than traditional facilities.

Liquid cooling will become more common as businesses deploy high-performance AI workloads, while modular, scalable infrastructure approaches will help operators respond more quickly to changing business requirements.

We are also likely to see growing investment in sovereign digital infrastructure and AI capabilities as governments and enterprises seek greater control over their data and digital ecosystems. As mentioned, policy developments, such as the CBN’s recently announced initiative, are likely to accelerate investment in domestic data centres and edge infrastructure while creating stronger foundations for future AI adoption.

For Africa, this represents a major opportunity to build next-generation infrastructure that supports economic growth, innovation and digital competitiveness.

Nairametrics: What should organisations in Nigeria be doing today to ensure they are prepared for future AI demands?

Gary Chomse: The most important step is to start planning infrastructure with AI in mind, even if larger-scale deployments are still emerging. Organisations should assess whether their existing facilities can support higher power densities, evaluate their energy efficiency strategies and identify areas where infrastructure modernisation may be required.

They should also consider how evolving regulatory requirements, including increasing emphasis on local data hosting and data sovereignty, may influence future infrastructure planning and capacity requirements.

AI adoption is not solely a technology decision; it is also an infrastructure decision. Businesses that establish a strong foundation today will be better positioned to take advantage of emerging AI opportunities tomorrow.

The organisations that succeed will be those that view power, cooling and compute as a connected ecosystem designed to support long-term growth and innovation.

Nairametrics: How is Vertiv helping organisations build the AI-ready infrastructure needed to support future growth?

Gary Chomse: As AI workloads become more power-intensive, businesses need to move beyond traditional approaches to infrastructure planning. The focus should not simply be on adding more power capacity, but on managing power intelligently across the entire environment.

At Vertiv, we advocate a converged approach that considers the entire power chain, from the utility grid through to the IT equipment itself, and the thermal chain, from the chip to heat reuse. This is a system-level approach in which power, thermal, controls and services are designed, engineered and validated as one interdependent architecture.

By taking this holistic approach, organisations can gain greater visibility into energy management, optimise resource utilisation and improve overall operational efficiency. This is particularly important as AI workloads become increasingly dynamic, with power demands that can fluctuate significantly depending on processing requirements.

Modern infrastructure solutions also allow operators to monitor and manage energy usage in real time, helping them balance performance, resilience and efficiency objectives. Ultimately, organisations that build AI-ready power infrastructure today will be better positioned to scale AI initiatives efficiently.