The future of AI is not one giant model at a center. It is millions of small, precise models deployed at the edge.
IEEE Spectrum — the flagship publication of the IEEE, the world’s largest technical professional organization — just published a feature on small AI and its growing role in global health care, agriculture, and development.
I was interviewed for the piece. My story opens the article. My words close it.
The feature, written by David Berreby, examines how small language models and edge-deployed AI are delivering life-saving services in environments where big AI cannot reach — places with unreliable power, limited connectivity, and no data center infrastructure.
The Story That Started It All
In 2019, I was in a Cape Town hotel room preparing to demonstrate our RxScanner to a government official. The system worked. It had been authenticating medicines in more than a dozen countries — Ghana, Kenya, Myanmar, Nigeria, and beyond. A pharmacist would scan a pill with our handheld spectrometer, and our AI model would identify whether the drug was authentic or counterfeit in seconds.
But that morning, the system did not work. Our server was in the United States. The round trip from Cape Town to Virginia and back took over five minutes for a single scan.
I called my engineers. Within two hours, they stripped the model down to the essential medication parameters and sent me a file I downloaded onto my Android phone. I ran the demo from my phone. No cloud. No server. No internet.
That morning created RxScanner Lite — a version of our drug authentication AI that runs entirely on a pharmacist’s phone, without any connection to the cloud.
Why This Matters
The World Bank reported that less than one percent of internet users in the world’s poorest countries have used ChatGPT. As World Bank President Ajay Banga said at Davos: outside the developed world, very few countries have the computing power, electricity, data, and skilled people that large language models require.
Small AI bridges that gap. Purpose-built models running on phones, drones, and low-power devices are authenticating medicines, detecting crop diseases, running electrocardiograms, and monitoring mosquito breeding grounds — all without a data center.
But small does not mean simple. As I told IEEE Spectrum: when my team compressed our model for edge deployment, the engineering challenge was harder, not easier. You cannot just remove parameters at random. You must know which ones matter for that specific use case, that specific user, that specific environment.
The Bigger Argument
The article positions small AI not as a compromise but as a design choice — and one that may ultimately reach more people than frontier models ever will.
I told Berreby: “If someone is not subsidizing it, most people will not be able to afford those models. So those of us who are said to be small-AI developers are the ones who will have to build for the majority of the world.”
At the same time, I cautioned that small AI is not a magic solution. It still requires infrastructure — reliable power for devices, periodic connectivity for model updates, and political leaders who understand that investing in the ecosystem around small AI is just as important as investing in the models themselves.
The article closes with my words: “It works, and many places will eventually need to use it. The question is whether or not the political actors are wise enough to invest in infrastructure to support it long term.”
Read the Full Article
The full IEEE Spectrum feature is live now:
“Small AI Models Gain Traction Around the World” https://spectrum.ieee.org/small-language-models-ai-pharmaceuticals
Onwards.
Adebayo Alonge is the Founder and Group CEO of RxAll, StorsApp, and Frontières Bay Energies. A Harvard Kennedy School Mason Fellow, Yale School of Management alumnus, and MIT Legatum Fellow, he builds AI-powered platforms that deliver healthcare, capital, and clean energy to underserved markets worldwide. He is a Fast Company World Changing Ideas 2025 honoree, Inc. 500 Founders 2025 honoree, and winner of the Hello Tomorrow DeepTech Prize.
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