MTN Group has joined a $45 million Series A funding round for U.S.-based AI radio access network (AI-RAN) firm ORAN Development Company (ODC), as the telecoms operator seeks to embed artificial intelligence into its network infrastructure.
The round includes participation from Nvidia, Nokia, Cisco, AT&T, Booz Allen Hamilton and Telecom Italia, reflecting growing industry interest in integrating AI capabilities into telecom networks.
AI-RAN technology shifts data processing from centralised data centres to the edge of the network, enabling workloads to be handled closer to users via cell towers. The approach is designed to reduce latency, lower bandwidth costs and support real-time applications.
ODC’s platform, built on Nvidia’s AI Aerial software stack, allows telecom operators to convert base stations into edge computing hubs capable of running AI models locally.
MTN, which operates in more than 15 African markets, said the investment aligns with its “Ambition 2030” strategy to expand digital infrastructure and develop new services beyond traditional connectivity.
Telecom networks are becoming more complex as the industry transitions toward 5G and future 6G systems, increasing the need for automated optimisation. AI-driven RAN systems can manage network performance, predict congestion and dynamically allocate resources.
MTN is also exploring the development of AI-enabled data centres in key markets including Nigeria and South Africa, as part of a broader push to combine centralised and edge computing capabilities.
The company said direct investment in ODC would allow it to help shape AI-RAN solutions for African operating environments, where power supply constraints and infrastructure variability remain key challenges.
Industry peers are making similar moves, with operators globally seeking to reposition themselves as providers of digital infrastructure and computing platforms rather than connectivity alone.
Analysts say AI-RAN could open new revenue streams for telecom companies by enabling them to offer edge computing services to enterprises, while also improving network efficiency and reducing operating costs.
However, adoption may be slowed by high initial investment requirements, integration challenges with legacy systems and a shortage of specialised skills.
The global edge computing market is expected to grow rapidly over the coming years, driven by rising demand for low-latency data processing and AI-powered applications.
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