Linet Kwamboka Nyang’au

Linet Kwamboka is the founder and Director of DataScience Ltd, a Kenyan data research and technology company that uses data to find practical, intelligent insight about people, products and services. She is also the Executive Director at the Datascience Impact Hub, a not-for-profit organization focused on developing Africa’s data infrastructure for emerging technologies. Trained as a computer scientist at the University of Nairobi and as a public policy analyst at the University of Bath, she has spent her career turning data from an administrative by-product into an instrument of public value.

Her work has repeatedly sat where government, technology and citizens meet. She helped coordinate the Kenya Open Data Initiative and Kenya’s participation in the Open Government Partnership, working with the Government of Kenya and the World Bank to publish public information in forms that journalists, researchers, developers and ordinary citizens could actually use. In 2025, she was the technology and team lead for the development of the Kenya AI Strategy (2025 – 2030). She has advised and built programmes across the continent.

Consulting for the UN Foundation (GPSDD), she led Africa programmes on COVID-19, AI, climate and health, and innovation, as well as the Data4Now initiative, helping national statistical offices and governments close the gap between the numbers they have and the numbers they need to track and achieve the Sustainable Development Goals. She has also served on the board of WeRobotics and NASA Lifelines.

Back at DataScience Ltd and the Datascience Impact Hub, her recent work applies AI to problems where the cost of bad data is measured in livelihoods — including Bluleaf, an AI-supported integrated pest management product built for Kenya’s horticulture and flower industry, where a single undetected infestation can erase a harvest. That work earned her recognition in Business Daily’s Top 40 Under 40 — 2026. She is also a certified data privacy practitioner (CDPSE), which shapes a consistent theme in her writing: capability and protection have to advance together.

Why she writes Economy of Data

Artificial intelligence is usually discussed as a story about models and compute. Economy of Data argues that the more decisive story is about inputs: the data that is collected, governed, priced, protected and — too often — never created at all. Those inputs decide who benefits from AI, and whether African countries participate as producers or only as consumers.

The essays here cover data governance and privacy, open data and accountability, national data systems and statistics, language and representation in datasets, the political economy of skills, and how AI is arriving in everyday work and life. Some pieces are written with collaborators.

How to read this site

The archive holds every essay in reverse-chronological order. Topics group the writing into recurring themes, and tags track narrower keywords. Every article keeps the web address it had on the original site, so old links, citations and bookmarks continue to work.

Get in touch

For talks, collaborations, corrections or commissions, see the contact page. She is also on LinkedIn.