The AI Revolution Nobody Talks About: Beyond Spreadsheets and Into Context

AI’s promise dazzles us—chatbots, predictive analytics, autonomous systems. Yet much of the world remains stuck at the starting line: spreadsheets. In the Global South, outdated Excel files, paper records, and PDFs remain the default, acting as both backbone and barrier to progress.

At Amini, we’ve seen how widespread and deeply trusted Excel has become as core infrastructure. Businesses rely on it for pricing, forecasting, and reporting—not because it’s ideal, but because its formulas simply work. Yet the moment AI systems fail to interpret that logic, they fail to deliver. That trust in spreadsheet logic anchors many organizations in place.

And this anchoring has real-world consequences. The World Economic Forum describes it as an “AI divide,” a reflection of how innovation remains concentrated in the Global North while the Global South is systematically held back by persistent gaps in governance, infrastructure, and data systems. Meanwhile, a 2022 UNESCO assessment found that over 70% of African institutions lack digitized data governance systems, and fewer than 25% of African Union countries have formal AI strategies . These gaps persist in Latin America and Southeast Asia, where mobile data costs can consume up to 10% of a household’s income, and 60% of youth have never received formal digital training . It’s no wonder systems remain analogue; building digital infrastructure is the foundation for meaningful intelligence.

The Invisible Work Behind AI

This foundation work may not make headlines. There are no launch announcements when you standardize land-use spreadsheets or convert analog rainfall logs into machine-readable formats. Yet it is precisely this work that distinguishes superficial AI pilots from scalable data infrastructure. Without provenance, there is no trust. Without consistency, there can be no context. Without intentional structure, there can be no sovereignty. Digitization is digital sovereignty. When data lives in unstructured siloes or on foreign-managed servers, the sovereignty of analysis, insights, and policy evaporates. UNESCO’s recent work on data governance warns that without regional capacity and rights-based frameworks, data use continues to entrench global power imbalances. To reclaim agency, countries must treat digitization not as a precursor to AI, but as its bedrock.

Trust, Sovereignty, and Value

Once systems are digitized, the opportunity unfolds. AI can finally function on local terms—with models sensitive to local seasons and languages, whether anticipating the next infestation affecting crops, or forecasting disease outbreaks. Governments, research institutions, and communities can form accountable data-sharing partnerships that respect local ownership and promote public good.

This shift matters deeply. Numerous Global South governments—from Argentina, Brazil, Rwanda, to Kenya—have published AI strategies, but implementation stalls when data remains fragmented or offline . Ethical, regulated data ecosystems are essential for trust and transparency. We’ve seen this before. Kenya, led by Safaricom’s mobile network expansion, leapfrogged landline infrastructure entirely. Instead of investing in fixed telephone lines, the country embraced mobile networks—unlocking services like M-Pesa that transformed financial access across rural and urban areas. This mobile-first approach enabled Kenya to scale digital innovation on its own terms. Similarly, the next leap in AI across the Global South won’t come from retrofitted systems, but from investing in robust, context-aware data infrastructure from the start.

Where the data lives, the future begins.