Increasing mobile adoption, higher data consumption, and the demand for advanced digital services are putting pressure on African operators to deliver better performance and more engaging user experiences. One technology rising to the challenge is AI-powered radio access networks (AI-RAN).
By embedding artificial intelligence and machine learning into network management, AI-RAN allows operators to optimize resources, enhance service quality, and proactively engage users like never before.
Vendors and global alliances are effectively pre-building the AI-RAN toolbox that African operators are likely to adopt over the next network upgrade cycles, even if full AI-native RAN is not yet live across the continent.
AI-RAN in the African Context
The AI-RAN Alliance, launched in 2024, brings together 80+ members across telecom, cloud, and silicon to accelerate AI-embedded RAN architectures. Alongside this, Ericsson invests roughly USD 4–5 billion annually in R&D, much of which is focused on cloud-native RAN, automation, and AI-driven network optimization, technologies already deployed across 300+ commercial 5G networks globally. Its partners across the African continent stand to benefit from this vast proof of concept.
AI-RAN integrates AI and machine learning into the RAN—the part of the network connecting end-users’ devices to the core. Traditionally, RAN management relied on manual configuration and periodic optimization, which struggles to keep up with modern networks handling high data volumes, multiple technologies, such as 4G LTE and 5G, and diverse applications from streaming to IoT.
AI-RAN introduces real-time optimization, predictive analytics, and automation. It continuously analyzes traffic patterns, user behavior, and network conditions, allowing operators to anticipate congestion, dynamically allocate spectrum, and adjust network parameters before issues occur. This enhanced automation reduces manual intervention, speeds up decisions, and improves reliability.
Symbiotically, AI-RAN also enables proactive network management. Potential bottlenecks and performance dips can be addressed before users notice, ensuring seamless connectivity. By turning static, hardware-driven networks into intelligent, adaptive systems, AI-RAN elevates performance, resilience, and user experience, making it a cornerstone for modern telecom operations.
However, AI-RAN represents a level of integration still mainly at prototype or global vendor research stages. Africa’s AI-RAN readiness is currently tied to Open RAN and cloud-native network transformation and only a few operators have publicly committed to trials or network architecture changes that would support future AI-RAN functions.
Boosting Network Performance
One of AI-RAN’s key advantages is its ability to enhance network performance. Machine learning algorithms analyze traffic patterns, anticipate congestion, and adjust network parameters proactively, while AI-RAN can dynamically allocate spectrum, adjust transmission power, or optimize beamforming to maintain seamless coverage. The result is reduced latency, improved throughput, and a better overall experience for users. Additionally, AI-RAN helps manage interference, streamline handovers between cells, and optimize energy consumption, creating cost-efficient and sustainable network operations.
Telkom Kenya is working with Rakuten Symphony to develop and test Open RAN 4G/5G infrastructure that includes AI-driven network optimization capabilities, while Vodacom is collaborating with NVIDIA and Nokia to build AI-enabled network management platforms that leverage machine learning for operational decision-making and performance optimization.
Rakuten Symphony claims its cloud-native RAN and orchestration platform can reduce total cost of ownership by up to 40% and shorten network deployment timelines by up to 50% compared to traditional RAN, a critical metric for African markets where margins are tight and coverage expansion remains capital-intensive.
Related: Optimizing Telecom Networks: RAN and SDN Load Balancing Drive Peak Performance
Enhancing User Engagement
AI-RAN’s benefits extend beyond performance to directly improving user engagement. Real-time data analytics provide insights into user behavior, service quality, and application performance. Operators can use this data to offer personalized services, tailor promotions, and proactively address network issues.
For example, if a group of users in a specific area experiences poor video streaming quality, AI-RAN can automatically adjust the network to improve performance while the operator communicates targeted solutions to affected users. This data-driven approach strengthens customer loyalty in Africa’s competitive telecom markets.
MTN has collaborated with Rakuten Symphony, Accenture, and Tech Mahindra on Open RAN 4G/5G proof-of-concept (PoC) trials in South Africa, Nigeria, and Liberia, leveraging Rakuten’s cloud-native platform with advanced automation and autonomous network capabilities. This serves as a steppingstone toward AI-enabled RAN functionality, which includes dynamic optimization and zero-touch provisioning.
Driving 5G and IoT Innovation
AI-RAN is also critical for supporting network-as-a-service (NaaS) models and 5G monetization. As 5G networks expand, operators need to offer differentiated services beyond basic connectivity. AI-RAN enables operators to deliver on-demand network slices, edge computing capabilities, and IoT services, without requiring enterprises to invest heavily in infrastructure. This flexibility allows telecom providers to create new revenue streams, reduce capital expenditures, and provide scalable services to businesses and consumers alike.
This year, Telkom Kenya and Rakuten Symphony signed a memorandum of understanding to test Open RAN technology in Kenya, which will help support automation and AI-powered innovation in 5G network operation and future IoT deployments.
Despite its advantages, AI-RAN adoption comes with challenges. Implementing AI requires robust data collection, advanced analytics, and reliable computational infrastructure. Smaller operators may face resource constraints, while regulatory compliance and data privacy remain critical.
For Africa, specifically, partnering with global technology vendors, cloud providers, and AI specialists could help operators overcome these barriers, enabling cost-effective deployment and faster time-to-value.
The Future of African Networks
Looking ahead, it’s clear that AI-RAN is emerging in Africa; it is not widespread and is yet to achieve full-scale commercial use. Although, as 5G and other advanced technologies proliferate, operators need smarter, adaptive systems to manage complex traffic patterns, support diverse applications, and enhance user engagement. By combining AI-driven optimization with cloud-based infrastructure, AI-RAN allows operators to deliver faster, more reliable, and more personalized services. Operators who adopt and explore the potential of AI-RAN will be well-positioned to lead Africa’s connectivity journey.
The aforementioned pilot ecosystems are standardizing components such as RAN Intelligent Controllers (RICs), xApps and rApps, and AI-ready cloud platforms, meaning African operators can progressively adopt AI-assisted optimization and automation without waiting for continent-specific AI-RAN builds.
It’s clear that AI-RAN is more than just a technological upgrade; it’s a strategic evolution for Africa’s telecom industry. As digital adoption accelerates across the continent, AI-RAN will ensure that networks are not only faster and more reliable but also smarter, adaptive, and ready to meet the evolving needs of consumers and enterprises in an African context.
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