Governments across Africa are increasingly integrating AI systems into public services, yet a critical question looms: who maintains control over these systems once deployed? This issue is not merely theoretical; it poses operational risks that could impact governance and public trust.
While systems may comply with procurement standards and come equipped with technical assurances, the real challenge emerges post-deployment. Governments must grapple with whether they can access, manage, or withdraw from these systems should circumstances change. This necessity underscores the importance of effective AI governance.
In nations like Nigeria, Kenya, Rwanda, and South Africa, significant strides have been made in establishing data protection laws and digital strategies. The African Union is also advocating for broader adoption of AI technologies across the continent. However, the ongoing challenge lies in whether these governments can enforce their regulations when the AI systems they adopt are often developed and maintained by foreign entities.
The procurement process is pivotal, shaping not just the technology purchased but also the framework of relationships surrounding it. When a government acquires an AI system, it enters into an agreement that determines access, support, infrastructure reliance, and potential modifications over time. The underlying issue is whether the government maintains genuine control over these systems.
Recent international partnerships illustrate this dynamic. In March 2025, Microsoft announced a ZAR 5.4 billion investment to bolster its cloud and AI infrastructure in South Africa, aimed at assisting government agencies and organizations with Azure services. Such deals are often labeled as capacity-building initiatives, but they simultaneously consolidate control, as essential infrastructure and system updates may remain outside of governmental ownership.
Moreover, in February 2026, the African Union Commission and Google entered a partnership to enhance Africa’s AI and digital capabilities, aligning with the AU’s broader strategic goals. These collaborations are becoming more prevalent across various countries and providers, posing a fundamental question: when critical systems depend on external infrastructure and support, who ultimately dictates their functionality?
Governments are evolving their procurement considerations, probing into who has access to the systems, the infrastructure that supports them, and the consequences of any changes post-adoption. These inquiries are not merely technical details but crucial governance decisions. For instance, the United States is proactively shaping its AI landscape through procurement, embedding conditions in contracts that demand disclosure, auditability, oversight, and clarity on system dependencies. Such strategic choices influence vendor behavior and signal to the market the governance features that are becoming essential.
This raises a vital lesson for African nations: procurement can serve as a governance mechanism, allowing governments to establish terms surrounding access and oversight before systems are put into use. The risk of exposure is immediate, but dependency poses a long-term constraint on operational flexibility.
As governments adopt AI systems, they may find themselves increasingly reliant on them, complicating the process of replacement. The accumulation of data and adaptation of workflows around these systems make it challenging to pivot when necessary. Consequently, the questions shift from merely assessing security to evaluating the feasibility of changing course.
Thus, procurement decisions are emerging as the most effective governance tools available to many African governments in the near term. Through procurement, they can mandate visibility, set access expectations, and retain the ability to respond to shifting risks. Without such leverage, governance risks becoming an abstract concept rather than a functional practice.
This issue extends beyond procurement; it encompasses cross-border data flows, downstream service dependencies, and the governance terms that accompany imported AI systems. However, procurement remains the initial point where these concerns materialize, allowing governments to assert what they are willing to rely on.
When procurement is approached as a governance strategy, governments are not merely purchasing technology; they are actively shaping authority within the adopted systems. The decisions made during procurement establish who has the capability to act, observe, and intervene in these systems, transforming governance from a theoretical framework into a practical reality.
As the landscape of AI governance evolves, the pressing question for African governments is not whether they will implement governance structures, but whether they will retain the authority to manage those systems once adopted.
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