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DATA CENTRE FEATURE SERIES
MANAGING TECHNOLOGICAL OBSOLESCENCE Another challenge discussed by the panel was how to design data centres that remain relevant as technologies evolve. Matthews noted that major infrastructure components, such as power systems, are changing rapidly. For example, large-scale uninterruptible power supply( UPS) systems that were considered cutting-edge a decade ago may now be insufficient for modern AI workloads.
To mitigate this risk, OADC prioritises investment in long-life infrastructure such as busbars and cabling rather than installing large numbers of expensive power units upfront.“ We might design the facility with space for five UPS systems but install only one initially. When the demand grows, we simply add the additional units,” he said.
This approach allows operators to avoid premature obsolescence while maintaining the ability to scale.
AI READINESS: A REALISTIC 12 – 18-MONTH ROADMAP When asked what a realistic AI-readiness roadmap looks like, the panel agreed that planning horizons should remain relatively short. Subramani suggested that 12 to 18 months is the most practical timeframe.“ You can’ t realistically plan ten years ahead in this industry anymore. The technology and the demand profile will be completely different.”
Within that period, organisations should focus on three key areas:
• Workload planning – understanding the types of AI applications that will run on the infrastructure.
• Deployment strategy – deciding whether workloads will be hosted on-premises, in colocation facilities, or in hyperscale clouds.
• Scalability – ensuring infrastructure can evolve as demand grows.
Piorko added that companies often overlook an even more fundamental question: why they want AI in the first place.
“ Everyone wants to have something AI. But the first question should be: what do you need it for? Is it revenue growth, automation, optimisation?” he said. Only once those objectives are clear should companies start designing the infrastructure required to support them.
“ For us, one of the biggest challenges is the human interface. You need technicians who understand both critical infrastructure and IT systems,” he said.
As a result, OADC is investing heavily in recruitment and training.“ AI won’ t replace people in this sector. If anything, we’ ll need more highly skilled people to operate these facilities,” Matthews said.
DESIGNING FOR CLIMATE RESILIENCE The panel also explored the impact of extreme weather on data centre design. In coastal regions such as Nigeria, Matthews said operators must consider risks such as storm surges, ocean swells and heavy rainfall.
In some cases, this leads to innovative design solutions. For example, one OADC facility has no ground-level operations floor, with the first usable level elevated above the surrounding terrain to mitigate flooding risks.
Subramani added that modern data centre planning increasingly includes detailed climate modelling.“ Each site is unique,” he said.“ You analyse rainfall patterns, flooding risks and other climatic factors during the design stage to ensure the facility remains resilient.”
Looking ahead, the panel agreed that global data consumption will continue rising rapidly, particularly as AI adoption accelerates. However, that does not necessarily mean the world will see exponentially more data centres.
Instead, Matthews suggested that facilities will become more powerful and more efficient, handling greater workloads within smaller footprints. Edge computing may also play a role, distributing smaller data centres closer to users.
Piorko added that while infrastructure will continue expanding, future investment will increasingly focus on applications that deliver real economic value.“ At the moment there is a lot of hype around AI. But eventually the investment will become more focused on where it creates real societal and economic benefit.”
For Africa’ s rapidly growing digital economy, that balance – between infrastructure expansion, efficiency, and meaningful AI deployment – may define the next phase of data centre development. RACA
Data artificial centres intelligence
THE HUMAN FACTOR IN AI-READY FACILITIES While much of the discussion focused on infrastructure, Matthews emphasised that people remain just as important as technology. Operating AI-ready data centres requires new skill sets that combine traditional facilities engineering with advanced IT expertise.
RACA Journal I July 2026
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