Poisoned At The Source: Securing Nigeria’s AI Supply Chain Against Data Poisoning

Nigerian technology businesses already understand guardrails. Fintechs build transaction limits, velocity checks, and fraud detection into their payment rails. Banks apply identity and onboarding checks. Health technology platforms restrict access to patient records. The familiar approach is to build a system, then place controls around it to detect misuse before harm reaches the user.

AI encourages the same instinct. Teams add content filters, moderation layers, and responsible AI policies. Those controls matter, but many operate at the input or output layer. Data poisoning starts earlier. It targets the information used to pre-train, fine-tune, align or otherwise adapt a model. By the time the model is deployed, the harmful pattern may already be embedded in its behaviour.