Hi! I’m so glad you’re here. |
I’m Jemimah Orevaoghene, an early-stage investor in the venture arm of one of Wall Street’s top investment banks. I started angel investing in African startups as a Yale sophomore, working a $17/hr job and saving $1,000 each semester to invest. During holiday breaks back home in Accra and Lagos, I hustled to find more founders for my next investments —no nepo baby funds, no old money or new money support system, just grit, hard work, networking, and Grace. My mission is to equip you weekly with all the information and tools I needed when I started my journey many moons ago. I’m very active on socials, so feel free to connect there and lets grow this community. Hope you like it here! |
A Dilemma
For most of the last decade, the global AI conversation has revolved around three places: Silicon Valley, China, and more recently Europe.
Africa, when mentioned at all, is framed as a future opportunity. A testing ground. A market to be unlocked later.
That framing is outdated and strategically wrong.
In the age of AI, Africa’s relevance is not about catching up. It’s about what happens when intelligence simultaneously collides with constraint, informality, and scale.
And that collision is producing something the rest of the world should be paying closer attention to.
Read to the end to find a practical call to action for professional in the Diaspora looking to contribute to the African AI ecosystem.
1.Africa Is Turning Messy Reality Into Structured Intelligence
Africa’s advantage in AI is not clean data. It’s the opposite.
Healthcare records are fragmented. Transactions are informal. Workflows are manual. Languages are diverse. Systems are inconsistent.
That chaos is exactly where applied AI thrives.
Companies like Helium Health are digitizing hospitals and layering intelligence on top of handwritten, incomplete clinical records, thereby improving operational efficiency and decision-making in environments where “perfect data” has never existed.
In fintech, Zest Africa and Moniepoint are underwriting credit without traditional credit bureaus by using behavioral, transactional, and alternative data to assess risk for SMEs banks have historically ignored.
This is not theoretical AI.
This is AI forced to deal with reality and still work.
2. Constraint Is Forcing Better AI, Not Weaker AI
Africa does not have the luxury of bloated solutions.
In agriculture, companies like Zenvus and Crop2Cash apply AI to optimize yield, pricing, and financing for smallholder farmers often using low-cost sensors, basic smartphones, and intermittent connectivity.
These systems are:
Offline-first
Compute-efficient
Built for unreliable infrastructure
As global enterprises begin questioning AI cost structures and ROI, solutions forged under African constraints look less like edge cases and more like blueprints.
3. African AI Is Voice-First Because It Has To Be
While the West debates copilots and dashboards, Africa is building AI for people who don’t type.
Intron Health is developing speech recognition and clinical documentation tools trained on African accents and dialects, thus solving a problem global models routinely fail at.
Viamo delivers voice-based AI services across healthcare and public information systems, reaching users regardless of literacy or device quality.
This is not a workaround.
It’s a preview of where global AI interfaces are heading.
“Young people are building AI language models in Swahili, Zulu, and Yoruba… Much of Africa’s knowledge isn’t digitized yet. Let’s fix that. That’s opportunity!
4. Solving for Informality Is a Global Unlock
Africa’s economies run on informality: no addresses, no receipts, no standardized logistics.
Companies like Leta and Kobo360 use machine learning to optimize logistics in environments where GPS data is unreliable and routes change daily—learning from partial signals like driver behavior, delivery patterns, and fuel usage.
As global supply chains become more volatile, these capabilities stop being “emerging market” features and start becoming resilience infrastructure.
5. Talent Close to the Problem Is Building the Most Defensible AI
African AI founders are not optimizing benchmarks. They are solving problems they personally live with.
Whether it’s:
Fraud detection in mobile money
Diagnostics in understaffed hospitals
Credit access for informal traders
Education without enough teachers
Companies like uLesson use AI-driven personalization to adapt learning content to student performance through low-bandwidth devices, at national scale.
This is applied intelligence.
And applied intelligence compounds.
Africa as an AI Stress Test
Africa is not racing to build the largest foundation models. That race is capital-heavy and crowded.
Its edge is elsewhere:
AI that works with bad data
AI that survives infrastructure failure
AI that delivers ROI, not demos
Africa is becoming the place where AI must earn its keep.
The systems that survive here will not stay here.
They will travel.
A Practical Call to Action for the Diaspora
If you’re a professional in the diaspora—working in tech, finance, law, data, product, or operations—your most valuable contribution is not capital.
It’s leverage.
Here’s how to use it.
1. Lend Credibility, Not Advice
Make warm introductions to enterprise buyers and institutional partners
Support founders in navigating procurement and compliance processes
Join critical sales calls as an advisor or credibility anchor
One trusted introduction can save a year.
2. Provide Legal and Regulatory Support Before It’s Urgent
If you work in law, compliance, or risk:
Help with data privacy, IP structure, and cross-border compliance
Prepare companies for GDPR, SOC2, HIPAA before investors demand it
Act as fractional counsel or governance advisor
This is non-dilutive, high-impact support.
3. Reduce Infrastructure and Software Costs
Secure cloud credits through employer or partner networks
Advise on compute-efficient architecture and tooling
Negotiate better pricing on AI infrastructure and MLOps stacks
Lower burn equals longer runway.
4. Be a Distribution Partner
If your company could pilot, integrate, or test a product:
Sponsor internal pilots
Push for paid proofs of concept
Help land global reference customers
Revenue beats mentorship—every time.
African AI Companies to Watch (Growth Stage)
Credible, venture-backed companies building real AI infrastructure:
Helium Health – Healthcare systems and intelligence
Intron Health – Speech and clinical AI for underrepresented accents
Leta – AI-powered logistics optimization
uLesson – Personalized education at scale
Zest Africa – AI-driven SME credit underwriting
Kobo360 – Data-driven freight and logistics infrastructure
These are not experiments. They are platforms.
Final Thought
Africa does not need sympathy or saviors.
It needs system builders.
If you’re in the diaspora, stop asking how to help—and start asking where your skills remove friction at scale.
That’s how Africa’s AI moment becomes inevitable, not aspirational.
