MTN Group has announced the appointment of Shoyinka Shodunke as Executive: IT Core Design and Delivery, effective March 1, 2026. In this role, the former Group CIO now carries group-wide responsibility for standardizing and modernizing MTN’s IT architecture, with a specific mandate to embed artificial intelligence into core systems across its African operations.

That announcement, while framed as an internal leadership move, carries wider implications for Africa’s digital infrastructure stack – from data centers and cloud platforms to energy systems, regulation, and capital allocation.

AI strategy is becoming an infrastructure strategy

Across global markets, AI has shifted from being a product-layer innovation to an infrastructure-led transformation. MTN’s decision to elevate IT core design to a group-level, AI-focused executive role reflects a similar recalibration in Africa. AI at scale is not deployed on fragmented legacy systems. It requires standardized architectures, predictable performance, resilient power, and proximity between compute, data, and networks.

For Africa’s data center sector, this is a critical signal. Large telecom operators are among the continent’s biggest generators of data and most demanding consumers of compute. As operators redesign their internal systems around AI-native architectures, demand will tilt further toward high-availability, low-latency, and energy-dense facilities. This favors carrier-neutral, interconnection-rich data centers capable of supporting hybrid workloads spanning private cloud, edge environments, and hyperscale platforms.

MTN’s internal AI push strengthens the business case for localized compute and interconnection. AI-driven network optimization, customer analytics, fraud detection, and predictive maintenance are latency-sensitive workloads. They perform better closer to users and networks, not across continents.

Cloud markets: from experimentation to core dependency

African cloud adoption has often been framed as an enterprise digitization story. Telecom operators may subtly reshape that narrative. When a group the size of MTN begins to treat cloud-native and AI-enabled architectures as core operating infrastructure, cloud demand becomes embedded in day-to-day operations rather than an optional service. This shift may also reflect a broader move toward the enterprise market, as operators expand converged offerings that combine colocation, cloud, connectivity, voice, and related digital services into integrated business solutions.

This has implications for both global hyperscalers and local cloud providers. Hyperscalers benefit from anchor tenants and predictable demand growth. Local and regional cloud players, meanwhile, gain relevance by offering compliance-aligned, low-latency, and locally interconnected environments that global platforms alone cannot fully replicate.

The deeper point is that AI workloads will accelerate hybrid cloud models in Africa. Operators will not place sensitive network, identity, or customer data entirely offshore. They will architect layered environments – local compute for latency and sovereignty, regional hubs for scale, and global clouds for advanced AI tooling. That architecture only works where data centers, IXPs, and cloud platforms are tightly coupled.

Energy becomes the binding constraint

AI infrastructure is power infrastructure. As telecom operators embed AI into core operations, their energy profiles change materially. Compute intensity rises, workloads become more continuous, and tolerance for outages narrows sharply.

This reality is now shaping policy debates globally. In the United States, President Donald Trump has proposed that data centers should bear a greater share of the cost of the power they consume, reflecting growing concern that AI-driven compute demand is straining grids and distorting energy economics. This move underscores the reality that AI infrastructure externalizes significant power costs, and governments are beginning to reassess who ultimately pays.

For African energy systems, this dynamic adds pressure but also creates opportunity. Data centers and AI-driven telecom infrastructure increasingly require dedicated, predictable power sources, including gas, solar-plus-storage, and hybrid on-site generation. These requirements align with emerging models in which data centers and large digital operators act as anchor off-takers, helping de-risk generation projects and unlock financing that would otherwise remain stalled.

Regulators and utilities will need to adapt quickly. Traditional grid planning, built around residential and light commercial demand, is poorly suited to compute-driven load growth that is dense, continuous, and highly sensitive to downtime. As AI adoption accelerates among large operators, earlier and more explicit conversations around embedded generation, wheeling frameworks, cost-reflective pricing, and flexible tariffs will become unavoidable. In the AI era, power policy must become central to digital infrastructure.

Policy shifts from access to competitiveness

For policymakers, MTN’s move reinforces a broader transition. The continent is moving beyond focusing primarily on broadband penetration. It is now about whether African markets can support AI-era infrastructure competitively.

That touches data localization, cloud regulation, energy policy, and spectrum management. AI-enabled telecom operations depend on data flows that are both compliant and efficient. Localization rules that do not support infrastructure risk raising costs and slowing deployment. Conversely, clear, infrastructure-aware policies can attract capital and accelerate build-out.

The lesson is that AI readiness is not achieved through policy declarations alone. It is built through coordinated regulation that aligns telecoms, energy, cloud, and data governance frameworks.

Capital follows architecture clarity

For investors, MTN’s appointment signals something else: architectural clarity precedes capital efficiency. When large operators standardize systems and commit to AI-native designs, capital deployment becomes more predictable. Data centers can size capacity with greater confidence. Energy developers can underwrite long-term demand. Cloud providers can plan regional investments with anchor customers in view.

Africa’s digital infrastructure challenge has long been one of fragmentation across systems, policies, and execution. Moves such as this point to a gradual shift toward consolidation and scale, driven less by ambition than by operational necessity. As the continent’s largest telecom operator, MTN is uniquely positioned to help bridge gaps across the ecosystem, working with regulators, infrastructure providers, and capital to accelerate progress on some of Africa’s most persistent digital infrastructure challenges.

Africa’s AI trajectory will not be decided at the application layer alone. It will be shaped by who can design, power, and interconnect the underlying infrastructure at scale. In that context, MTN’s move is less about an executive appointment than about signaling where the next phase of competition – and capital deployment – will be contested: in core architecture, energy alignment, and the physical foundations that determine whether AI systems can operate reliably across African markets.