Schneider Electric Urges Nigeria to Build AI-Ready Data Centres

Fadekemi Ajakaiye

Schneider Electric has warned that Nigeria’s data centre infrastructure must evolve rapidly to meet the demands of artificial intelligence (AI), calling on operators, policymakers, and enterprises to invest in scalable, resilient, and AI-ready facilities. The company made the comments during a recent briefing in Lagos, highlighting how generative AI is transforming computing needs across banking, telecoms, healthcare, manufacturing, and government sectors.

Country President, West Africa, Mr. Ajibola Akindele, Schneider Electric, said traditional facilities are ill-equipped for the energy, cooling, and density requirements of AI workloads, particularly as inferencing — where AI delivers real-time predictions — becomes more widespread.

“Software is no longer a background tool for data centres in Nigeria. It is the intelligence that allows operators to anticipate changes in demand, optimise energy use, and ensure resilient performance even in the face of power constraints,” Mr. Akindele said.

Schneider Electric distinguished between AI training and inferencing, noting that training requires racks exceeding 100 kW per cluster, placing extreme pressure on power and cooling systems, while inferencing workloads, although traditionally less energy-intensive, are growing increasingly complex, reaching 40–80 kW per rack in some cases.

The company projected that by 2030, approximately 25 percent of new Nigerian data centre builds will support less than 40 kW per rack, 50 percent will accommodate 40–80 kW per rack for mixed workloads, and 25 percent will exceed 100 kW per rack for large-scale training clusters. These shifts, Schneider Electric said, necessitate rethinking power distribution, cooling, networking, and software orchestration.
Country President, West Africa, Mr. Ajibola Akindele, Schneider Electric, added that AI inferencing will increasingly occur at the edge, in colocation facilities, and on-premise in regulated sectors such as banking and healthcare, requiring low-latency, locally controlled environments.

Schneider Electric urged operators to adopt liquid cooling, scalable electrical architectures, high-performance networking, and intelligent power distribution systems. Software-driven solutions such as DCIM, EPMS, and BMS are critical for real-time monitoring, predictive maintenance, and capacity planning.

“As AI evolves, Nigerian operators will need automated systems that reduce downtime, improve power efficiency, and enable data centres to scale without sacrificing reliability,” Mr. Akindele said.
The company identified three key trends shaping Nigeria’s AI future: increasing model complexity with multimodal capabilities, a shift toward low-latency on-site inferencing, and the growth of AI-as-a-Service, which demands modular, flexible, and high-density infrastructure.

Schneider Electric concluded that Nigerian data centre operators, cloud service providers, and public-sector stakeholders must proactively design infrastructure around density, flexibility, and long-term efficiency to support the country’s digital economy.