A recent panel discussion at AI Everything MEA in Cairo shed light on the importance of trust, transparency, and accountability in AI. As the only operator on stage, I shared my experience building systems that process over 100 billion transactions across Nigeria and the UK. The key takeaway: governance is not a compliance cost, but an engineering discipline that makes everything else possible.
The conversation started with a question on what investors should look for when evaluating AI companies. While investors offered valuable insights on governance frameworks and founder credibility, I decided to share a story about the impact of SMS charges on computing Monthly Active Users (MAU). At Moniepoint, we've learned that if your definition of 'monthly active user' is 'any customer with at least one transaction,' those customers show up as active, even if they didn't open the app or make a purchase.
This highlights a critical issue in AI: if you build churn prediction, credit scoring, or personalization on top of confused data, the AI inherits the confusion. It's not a model problem, but a governance problem. At Moniepoint, we've built a maker-checker system to ensure that the person uploading a statement cannot be the approver. This principle has carried through everything we've built, establishing a full chain of custody for every transaction.
Our experience has shown that governance is what makes AI possible. Without it, you have a black box processing billions of transactions. With it, you have an auditable, explainable system that regulators, investors, or auditors can interrogate. We've also learned that building a conversational analytics interface only works because the governance layer exists underneath, providing canonical definitions, data lineage, and a shared vocabulary.
To evaluate an AI company, investors should ask three key questions: the 'Triangulation' Test, the 'Semantic' Test, and the 'Post-Mortem' Test. These questions will tell you more about the company's viability than any accuracy benchmark. Governance is not overhead; it's the engine that makes everything else possible. Companies that build this into their architecture from day one don't just avoid regulatory risk; they move faster than everyone else when it's time to deploy AI.
Cet article a été rédigé avec l'assistance de l'IA.
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