MTN Group has underscored emerging trends in artificial intelligence (AI) infrastructure following NVIDIA’s GTC 2026 conference. Charles Molapisi, MTN’s Group Technology and AI Executive, said operators must now view AI as an infrastructure challenge, not just a software or application opportunity.
“In the AI game, it’s land and energy first. The one who converts electrons into revenue at the lowest cost wins,” Molapisi said, highlighting the growing importance of energy-efficient computing and site selection.
He noted that workload optimisation is critical, with different processors-GPUs, CPUs, and Language Processing Units required depending on whether AI tasks involve training, inference, or continuous operations. “Know thy workloads. The processor mix will be critical to deliver better economics,” he added.
Molapisi also pointed to NVIDIA’s shift from traditional accelerators to the Vera Rubin platform, describing it as the industry’s move toward “AI factories”-data centres designed to continuously generate AI intelligence at scale.
He emphasised the rapid growth of agentic AI and large-scale inference systems, which operate autonomously and require low-latency networks and always-on compute. “Agentic AI and inference at scale are huge growth areas,” he added.
Finally, Molapisi highlighted opportunities for telecoms to embed AI across distributed networks, including radio access networks and edge computing, enabling real-time AI inference close to users.
MTN’s insights signal that AI infrastructure-spanning energy, compute, and distributed networks will be a defining factor in the next wave of AI deployment across Africa and globally.
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