For more than a century, Africa’s communications networks have been built in uneven bursts. The convoy arrived at the port before the hinterland. Mobile leapfrog fixed. Coverage expanded faster than capacity planning. Today, the discussion has once again moved away from just access and toward what those networks actually support. Productivity. Industrial adjustment. A public service that works under pressure.
Ericsson’s current position in Africa lies in this tension. The company no longer speaks only to mobile phone operators about coverage maps. It tells governments, utilities, mines, ports, and emergency agencies how networks behave when called upon to be of economic importance. That framework is important because Africa’s digital economy is no longer a hypothesis. It is already constrained by energy supplies, skills shortages and uneven organizational capacity.
Majida Lalu Kassi, head of Ericsson’s Western and Southern Africa business, explains this challenge from a practical perspective. The network must perform more work without consuming proportionally more power. They must serve industries that cannot tolerate spikes in delays or outages. They also need to remain affordable in markets where margins are thin and demand is volatile.
5G as impactful infrastructure
Much of the discussion about 5G in Africa still centers around the pace of deployment and the awarding of spectrum. That would leave out the big story. In some markets in Africa, 5G is arriving at a moment when operators can make architectural decisions they already regret in older markets. Non-standalone deployments have lower initial costs, but lock your network into a legacy core, limiting the applications you can realistically run.
There is a growing argument, especially among vendors and large operators, that Africa can move directly to 5G on its own in selected corridors. Mines, ports, logistics bases, industrial parks. It is clearer where performance can be measured and economic benefits can be realized. That logic is not idealistic. It’s an economical thing. A standalone core reduces complexity over time, creates room for automation, and reduces operational costs.
Here, Erickson’s argument becomes more nuanced. The company talks less about actual speed and more about predictability. Low latency to maintain low latency. Capacity that can be expanded without manual intervention. A network that can be tailored to specific industry operations rather than general consumer demands.
Artificial intelligence as an operating layer, not a product
Artificial intelligence often appears in African technology debates shrouded in abstraction. The promise is broad. The use case remains vague. But on the network side, AI has already been quietly integrated for years. Ericsson’s system uses machine learning to predict traffic flows, detect failures, and manage radio resources. This is not experimental. It is operational.
The next phase goes even deeper. An AI system that not only optimizes but also makes decisions. When to turn off the device. When to reroute traffic. When to allocate capacity to your private network beyond public demand. These decisions are even more important in Africa, where energy is often expensive and unreliable. Every watt saved increases runtime.
Kassi describes this as a disruption of the energy curve. The network consumes more data without consuming energy at the same rate. This goal sounds abstract until you consider rural base stations operating on diesel or hybrid power. In such an environment, efficiency is not a sustainability slogan. Determine whether the service exists at all.
Edge intelligence and computing geography
Africa’s data geography is uneven. Hyperscale data centers are concentrated in several countries. Although the connection between them is improving, the latency still varies widely. Therefore, the idea of bringing intelligence closer to users goes beyond a technical preference. It becomes a necessity.
Edge computing allows processing to take place closer to mines, factories, and transportation hubs. For mine safety systems and port automation equipment, traveling to and from distant data centers is not practical. Ericsson’s work here intersects with private 5G networks, where carriers or enterprises control both connectivity and computing.
However, there is also a sense of tension that cannot be resolved. Edge deployments reduce latency and bandwidth costs, but increase complexity. Managing distributed systems requires skills. The security model must be locally robust. African markets need to decide where edge makes sense and where centralization is more efficient.
Skills, systems and slow work behind the scenes
Infrastructure alone does not build a digital economy. Africa’s skills gap remains one of its most persistent constraints. Ericsson’s education and graduate programs are part of a broader effort to localize expertise in cloud, AI and network engineering. These programs don’t make headlines, but they form a workforce that can operate and adapt complex systems over time.
There are also governance issues. AI-driven networks raise questions regarding accountability, data processing, and operational transparency. Regulators across Africa are at very different stages of preparation. Some people are actively working on these questions. Other companies remain focused on indemnity obligations and price controls.
This uneven institutional capacity creates friction. Advanced networks can exceed rules for monitoring networks. This gap can lead to delays in implementation and risk aversion among operators. It also opens up room for experimentation in markets that want to update their regulatory frameworks along with technology.
Industry use cases where theory and friction collide
Mining is one of the clearest examples of where 5G and AI intersect with direct value. Self-driving cars, remote control, and safety monitoring all rely on reliable, low-latency connectivity. The logic is similar for ports. Container tracking, automated cranes, and coordinated logistics benefit from deterministic networks.
Public safety is another field where performance is not optional. Emergency communications require priority response and resilience under stress. Here, private and hybrid networks offer greater government control, but also require long-term operational commitments.
What these fields have in common is nothing new. It’s reliability under constraints. Africa’s digital economy will grow where systems work consistently, not where demonstrations are impressive.
Energy realities and the limits of ambition
Energy remains the most difficult constraint to ignore. Africa has an early opportunity to build parallel networks with renewable energy. Solar-powered base stations and hybrid systems are already commonplace. AI can optimize its use, but it cannot replace missing infrastructure.
Decisions about where data is processed, how networks are powered, and how long-term operations are funded drive outcomes bigger than any single technology. Ericsson’s net-zero emissions goal intersects with carrier economics in complex ways. Efficiency saves money. Capital investments still require confidence in the return.
Where Africa’s digital economy could settle down
The most likely path forward will not be smooth, but it will be one that works. Advanced networks are concentrated around economic nodes. Consumer coverage is steadily expanding, but not uniformly. AI is deeply embedded in operations and largely invisible to users. Private networks are becoming the norm in heavy industry and logistics.
Africa’s digital economy does not mirror Europe or Asia. They evolve under different constraints and with different priorities. Vendors like Ericsson are positioning themselves as long-term partners in the process, not just equipment suppliers.
Results depend less on grand vision and more on whether the network can continue to function during power outages, traffic spikes, or lack of skills in the field. In Africa, durability is the true measure of progress.
For more technology and business news from the African continent, visit TECHTRENDSKE.co.ke.
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