Africa must develop AI systems with local control to protect critical infrastructure such as mobile money networks from growing AI-powered cyberthreats.

Jane Munga is a fellow in the Africa Program at the Carnegie Endowment for International Peace, where she leads research on technology policy.

Imagine that it is 6 a.m. in the wholesale markets of Nairobi. Merchants are delivering vegetables from up-country farms to the retailers who sell to the city’s households. Everyone is using M-Pesa, Safaricom’s mobile money platform, when suddenly, the system crashes, bringing the market to a standstill. Imagine that across the continent in Accra, MTN’s MoMo has also crashed, and business in Makola Market has all but stopped.

With the growing number of cyberattacks caused by artificial intelligence, these are highly plausible scenarios. In both these cases, Safaricom, MTN, and the Kenyan and Ghanaian governments need an off switch, or the technical ability and know-how to stop a rogue AI agent from executing its code on their payment systems.

The distinction that will ultimately matter is … whether AI can serve its purpose and be controlled locally.

S. , open versus closed models, and who will dominate the AI race. But in Africa’s capitals, the distinction that will ultimately matter is not whose product was used to build a system, or who dominates whom, but rather whether AI can serve its purpose and be controlled locally. So how can Africa build with agency, and with control over the code and makeup of its own systems, even though they are built on foreign technology?

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