Africa’s Digital Economy Is Moving Forward, But Only Where the Infrastructure Holds

For more than a century, Africa’s communications networks have been built in uneven bursts. Lines arrived in ports before hinterlands. Mobile leapfrogged fixed. Coverage expanded faster than capacity planning. Today, the conversation has moved again, away from access alone and toward what those networks actually support. Productivity. Industrial coordination. Public services that function under pressure.

Ericsson’s current positioning in Africa sits inside that tension. The company is no longer speaking only to mobile operators about coverage maps. It is speaking to governments, utilities, mines, ports, and emergency agencies about how networks behave when they are asked to carry economic weight. That framing matters, because Africa’s digital economy is no longer hypothetical. It is already constrained by energy supply, skills shortages, and uneven institutional capacity.

Majda Lahlou Kassi, who leads Ericsson’s West and Southern Africa operations, frames the challenge in practical terms. Networks must do more work without consuming proportionally more power. They must serve industries that cannot tolerate latency spikes or outages. They must also remain affordable in markets where margins are thin and demand is volatile.

5G as infrastructure with consequences

Much of Africa’s 5G discussion still circles around rollout pace and spectrum awards. That misses the larger story. In several African markets, 5G is arriving at a moment when operators can make architectural decisions that older markets already regret. Non standalone deployments are cheaper upfront, but they lock networks into legacy cores and limit what applications can realistically run.

There is a growing argument, especially among vendors and larger operators, that Africa can move directly to 5G standalone in selected corridors. Mines, ports, logistics hubs, industrial parks. Places where performance is measurable and economic returns are clearer. The logic is not idealistic. It is financial. A standalone core reduces complexity over time and creates room for automation that lowers operating costs.

That is where Ericsson’s pitch becomes more nuanced. The company talks less about raw speed and more about predictability. Low latency that stays low. Capacity that scales without manual intervention. Networks that can be tuned for specific industrial behavior rather than generic consumer demand.

Artificial intelligence as an operating layer, not a product

Artificial intelligence often arrives in African tech debates wrapped in abstraction. Promises are broad. Use cases remain vague. On the network side, however, AI has already been embedded quietly for years. Ericsson’s systems use machine learning to anticipate traffic flows, detect faults, and manage radio resources. This is not experimental. It is operational.

The next phase is deeper. AI systems that do not just optimize but also decide. When to power down equipment. When to reroute traffic. When to allocate capacity to a private network over public demand. These decisions matter more in Africa because energy is expensive and often unreliable. Every watt saved extends uptime.

Kassi describes this as breaking the energy curve. Networks consume more data without consuming energy at the same rate. That goal sounds abstract until one considers rural base stations running on diesel or hybrid power. In those environments, efficiency is not a sustainability slogan. It determines whether service exists at all.

Edge intelligence and the geography of compute

Africa’s data geography is uneven. Hyperscale data centres cluster in a handful of countries. Connectivity between them is improving, but latency still varies widely. This makes the idea of pushing intelligence closer to the user more than a technical preference. It becomes a necessity.

Edge computing allows processing to happen near mines, factories, or transport hubs. For safety systems in mining or automated equipment in ports, round trips to distant data centres are impractical. Ericsson’s work here intersects with private 5G networks, where operators or enterprises control both connectivity and compute.

There is an unresolved tension, however. Edge deployments reduce latency and bandwidth costs, but they add complexity. Skills are required to manage distributed systems. Security models must be local and robust. African markets will need to decide where edge makes sense and where centralisation remains more efficient.

Skills, institutions, and the slow work behind the scenes

Infrastructure alone does not build a digital economy. Africa’s skills gap remains one of the most persistent constraints. Ericsson’s education and graduate programs are part of a broader effort to localise expertise in cloud, AI, and network engineering. These programs are not headline grabbing, but they shape who can operate and adapt complex systems over time.

There is also the question of governance. AI driven networks raise issues around accountability, data handling, and operational transparency. Regulators across Africa are at very different stages of readiness. Some are actively engaging with these questions. Others are still focused on coverage obligations and pricing controls.

This uneven institutional capacity creates friction. Advanced networks can outpace the rules meant to oversee them. That gap can slow deployment or create risk aversion among operators. It also opens space for experimentation in markets willing to update regulatory frameworks alongside technology.

Industry use cases where theory meets friction

Mining remains one of the clearest examples of where 5G and AI intersect with immediate value. Autonomous vehicles, remote operations, and safety monitoring all depend on reliable, low latency connectivity. In ports, the logic is similar. Container tracking, automated cranes, and coordinated logistics benefit from deterministic networks.

Public safety is another area where performance is not optional. Emergency communications require priority handling and resilience under stress. Here, private and hybrid networks offer governments more control, but they also demand long term operational commitment.

Across these sectors, the common thread is not novelty. It is reliability under constraint. Africa’s digital economy grows where systems work consistently, not where demos impress.

Energy realities and the limits of ambition

Energy remains the hardest constraint to ignore. Africa has the opportunity to build networks alongside renewable energy from the outset. Solar powered base stations and hybrid systems are already common. AI can optimise their use, but it cannot replace missing infrastructure.

Decisions about where to process data, how to power networks, and how to finance long term operations will shape outcomes more than any single technology. Ericsson’s stated goal of net zero emissions intersects with operator economics in complex ways. Efficiency saves money. Capital investment still requires confidence in returns.

Where Africa’s digital economy could settle

The most plausible path forward is uneven but functional. Advanced networks concentrated around economic nodes. Consumer coverage expanding steadily, but not uniformly. AI embedded deeply in operations, mostly invisible to users. Private networks becoming normal in heavy industry and logistics.

Africa’s digital economy will not mirror Europe or Asia. It will evolve under different constraints and with different priorities. Vendors like Ericsson are positioning themselves as long term partners in that process, not just equipment suppliers.

The outcome will depend less on grand visions and more on whether networks can keep working when power dips, traffic spikes, or skills are thin on the ground. In Africa, durability is the real measure of progress.

Go to TECHTRENDSKE.co.ke for more tech and business news from the African continent.

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