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    Home » Nigeria’s Data Centres Must Be AI-Ready, Warns Schneider Electric
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    Nigeria’s Data Centres Must Be AI-Ready, Warns Schneider Electric

    Ugochukwu Levi FBy Ugochukwu Levi FNovember 24, 2025Updated:January 8, 2026No Comments12 Views
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    Schneider Electric has warned that Nigeria must urgently upgrade its data infrastructure to meet the power, cooling, and management demands of artificial intelligence workloads, or risk falling behind regionally. Ajibola Akindele, speaking for Schneider Electric in West Africa, said today that many of the country’s data centres lack the resilient power and efficient cooling systems needed to support AI and cloud services at scale, raising concerns for businesses and the broader Nigerian digital economy. The company highlighted that AI-driven workloads, such as large language model training and real‑time analytics, can spike energy use and heat generation far beyond levels seen in conventional applications, increasing demand on distribution systems and on-site generation. Schneider Electric called for accelerated investment in energy‑efficient infrastructure, modern power and cooling solutions, and targeted training to ensure centres across Nigeria can sustain growing data volumes and remain competitive.

    Power reliability remains the most pressing constraint for Nigeria’s data centres. Many facilities depend on a mix of grid supply and on‑site generators; when AI workloads spike, the combined draw can overwhelm distribution networks and raise operating costs. Schneider Electric warns that without upgrades to electrical distribution and investment in more resilient energy infrastructure, centres will struggle to deliver the uptime and performance required by cloud and AI services.

    Cooling is the second critical bottleneck. Modern AI servers produce substantially more heat than traditional racks: training a large model can push power density and heat output per rack far beyond levels for routine business applications. That requires more advanced, energy‑efficient cooling systems and better thermal management to protect hardware and sustain consistent performance. Legacy facilities with limited chilled‑water capacity or inadequate airflow simply cannot host sustained AI workloads without major retrofits.

    Capacity and systems integration are also limiting factors. Several existing centres in Nigeria operate close to peak capacity and lack modular designs that allow quick expansion. Schneider Electric recommends modular, scalable architectures and automation tools that improve load balancing and fault response. Such systems can increase efficiency, lower the total cost of ownership and enable facilities to scale for cloud services and high‑density computing.

    For example, a mid‑sized data centre running conventional web and business applications may draw a few hundred kilowatts per rack under peak load; a comparable cluster supporting AI training can multiply that demand, requiring both higher power delivery and denser cooling. Addressing these differences means deploying tailored power distribution units, more efficient UPS solutions, and precision cooling that, together, reduce energy waste while maintaining performance.

    Schneider Electric’s proposed solutions include comprehensive energy audits, targeted deployment of high‑efficiency cooling technologies, and modernised power systems that prioritise redundancy and automation. Implementing these measures would help centres across Nigeria manage surges in demand, improve operational efficiency and support the country’s broader digital infrastructure ambitions.

    Schneider Electric emphasised that technical upgrades must be matched by investment in people and governance to ensure sustainable adoption of AI‑ready data centres. Ajibola Akindele said the company is urging coordinated action from government, industry and businesses to fund programmes that build local capacity and management skills for modern data centre operations.

    Key priorities include: targeted training to develop technicians and data‑centre managers who can operate advanced power and cooling systems; deployment of automation and monitoring tools to improve fault response and efficiency; and public‑private investment models that lower the upfront cost of upgrades. Schneider Electric noted that without dedicated training pipelines and clear industry standards, centres risk under‑utilising new systems and losing performance gains.

    Investment can take several forms: direct capital for modular expansions to increase capacity, subsidies or incentives to accelerate retrofits, and partnerships with international providers to transfer technical expertise. For businesses, the benefits include lower operating costs, improved uptime and greater competitiveness in regional cloud and AI markets. For the wider economy, strengthening data‑centre capability supports Nigeria’s digital infrastructure goals and can attract further cloud and manufacturing investment.

    Schneider Electric recommended that governments publish clear timelines and standards for data‑centre resilience and sustainability, while companies plan multi‑year investment and workforce development strategies. The company said progress on these fronts would be critical to realising the full economic value of AI and cloud services across Nigeria’s centres.

    The warning from Schneider Electric underscores that improving power reliability, deploying efficient cooling and investing in training and modern systems are urgent priorities if Nigeria is to capture the economic gains of AI and cloud adoption. Without coordinated government and industry action to fund resilient digital infrastructure and practical solutions, the country risks losing competitiveness in West Africa’s fast‑growing data economy. Schneider Electric said progress on standards and multi‑year investments would be needed over the coming years to secure performance, sustainability and capacity across Nigeria’s data centres today.

    Ugochukwu Levi F
    Ugochukwu Levi F

    Bio

    Ugochukwu is a freelance journalist and Editor at AIbase.ng, with a strong professional focus on investigative reporting. He holds a degree in Mass Communication and brings extensive experience in news gathering, reporting, and editorial writing. With over a decade of active engagement across diverse news sources, he contributes in-depth analytical, practical, and expository articles that explore artificial intelligence and its real-world impact. His seasoned newsroom experience and well-established information networks provide AIbase.ng with credible, timely, and high-quality coverage of emerging AI developments.

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