Africa’s AI Builders:
207 Startups, Three Years,
One Continent’s Bet
An overview of the continent’s artificial intelligence startup ecosystem: who is building, where they are building, what they are building for, and how many are still standing.
In an earlier report, we worked through a definition of what an African AI startup actually is: a company in which AI is not merely a feature but the primary mechanism through which the business creates and delivers value, whether through predictive modelling, intelligent automation, or data-driven decision tools built on locally relevant datasets. The question of definition matters more than it sounds, because how you define a thing determines whether it gets counted, and whether it gets counted determines whether it gets funded.
Today, we are able to put some data behind that conversation. Working from a publicly available dataset compiled by Dr Chinasa T. Okolo, we have reviewed 207 AI startups operating across Africa in 2025, benchmarked against 104 companies tracked in 2022. The list is not exhaustive, (it excludes the outlier startup Instadeep, for example,) but it is among the most rigorous open-source efforts to map this ecosystem, and it gives us a real foundation for understanding what is being built on the continent and where. We are grateful to Dr Okolo for making this data available.
A note before we begin: sector labels in this dataset are inconsistent in granularity, and some companies carry multiple classifications. We have used primary sector designations throughout, and readers should treat directional trends as more reliable than precise counts. With that said, let us dig in.
The Ecosystem Has Nearly Doubled in Three Years
In 2022, this dataset tracked 104 AI startups across Africa. By 2025, that number had grown to 207, a 99% increase. Of the 104 companies catalogued in 2022, 76 appear in the 2025 dataset, meaning roughly 73% survived to be counted three years later. A further 131 entirely new companies have joined the ecosystem since then.
Twenty-eight companies that appeared in 2022 have since dropped out, either defunct, acquired, or simply no longer tracked. That churn may speak to the natural lifecycle of early-stage ventures more than any systemic failure of the ecosystem.
131 new AI startups entered the dataset between 2022 and 2025, more new entrants than the entire 2022 cohort combined.
Founding Wave: The 2016–2019 Boom
The most common founding year in this dataset is 2018 (27 startups), followed closely by 2016 and 2017. The 2016–2020 cohort accounts for 110 startups, 53% of the entire dataset, suggesting Africa’s AI startup surge predates the global generative AI wave and has been compounding for nearly a decade.
The 2021–2025 cohort contributes 73 companies, with a notable rebound in 2024 (20 new startups) and an already-strong 2025 class of 16, indicating continued founding momentum into the current year.
The Big Three Still Lead, But the Map Is Expanding
Nigeria (50), South Africa (49), and Kenya (31) remain Africa’s dominant AI hubs, together accounting for 63% of all tracked startups. This mirrors the broader African tech ecosystem, where established funding infrastructure, technical talent pools, and developer communities tend to concentrate activity.
The more instructive story is geographic diversification. Egypt grew from just 3 startups in 2022 to 11 in 2025, a 267% increase, and has emerged as a credible fourth hub. Tunisia (11) and Ghana (13) have consolidated notable clusters. Rwanda, Ethiopia, Zambia, Côte d’Ivoire, Morocco, and Senegal all now carry meaningful representation where they had almost none three years ago.
Regional Dynamics
West Africa leads all regions with 71 startups, ahead of Southern Africa (53) and East Africa (50). North Africa, though smaller in absolute terms at 26 startups, is growing at a faster clip: Egypt and Tunisia are building distinct clusters, with strengths in enterprise software and research-oriented AI respectively.
East Africa is the most growth-stage-heavy region proportionally: 40% of East African startups are at Growth Stage, compared to 30% in Southern Africa and 22% in West Africa. Kenya in particular skews the regional average upward, suggesting its companies are more mature on average despite the region’s smaller total count.
Software Development Dominates, But Vertical AI Is the Story
Software Development is the most common primary sector designation (48 startups, 23%), though this functions partly as a catch-all label. The more revealing picture emerges from vertical AI (applications and models specifically developed, trained, and fine-tuned for a particular industry, niche, or specialized workflow): Agriculture (20), Finance (22), Healthcare (20), and Education (14) together account for 76 startups, 37% of the total, representing deep sector bets on the problems most acute to African contexts.
Sector Shift Since 2022
The most significant sectoral shift between 2022 and 2025 is the rise of Education AI, from 2 companies to 14, and the emergence of Legal AI as a distinct category, going from zero to 6 companies. Finance held its top position from 2022, while Healthcare and Agriculture both grew from already-strong bases. Software Development expanded substantially from 8 to 48 primary designations, reflecting both real growth and the reclassification of companies building horizontal AI tools.
The relative decline of Surveillance and Facial Recognition as named categories is worth noting. Both carried 4 companies each in 2022 and appear diminished in 2025. Whether this reflects rebranding, consolidation, or growing sensitivity around these technologies is difficult to determine from the data alone.
Legal AI went from zero to six companies in three years, perhaps Africa’s most quietly emerging vertical.
Country-Sector Specialisation
Nigeria leads in Healthcare (7), Software Development (10), and Finance (6), and is the clear home for Legal AI (3 companies). South Africa concentrates in Finance (7) and Software Development (11), and accounts for most of the continent’s Insurance AI activity. Kenya is notably balanced across Software Dev (7), Healthcare (4), Agriculture (4), Education (3), and Customer Service (3), suggesting a broadly diversified ecosystem rather than a single sector bet. Egypt shows a pronounced tilt toward retail-facing and software development companies.
The Stage Pyramid: Mostly Early, With a Healthy Middle
Of 207 startups, 139 (67%) are at Early Stage, 60 (29%) are at Growth Stage, and just 8 (4%) have reached Maturity. This pyramid is expected for an ecosystem still in formation, but the 29% Growth Stage cohort is a meaningful signal of real depth beyond the founding layer.
Survival Rates Are Broadly Similar Across Stages
Active rates are nearly identical across Early Stage (85.6%) and Growth Stage (85.0%), with all 8 Mature companies still operational. This uniformity is somewhat counterintuitive; typically, early-stage companies carry significantly higher failure risk. It likely reflects survivorship bias in the dataset, whereby only the more visible and funded early-stage companies get tracked, rather than any special resilience of the cohort as a whole.
Of the 18 confirmed defunct companies, 17 (94%) were at Early Stage, and 12 of those 18 were founded in 2018 or 2019, suggesting a specific cohort, built at the peak of the previous boom, that struggled to find product-market fit through COVID and its economic fallout.
Growth Stage Geography
Kenya leads Growth Stage counts (13), narrowly ahead of South Africa (12) and Nigeria (10). Given Kenya’s smaller overall footprint, this makes it proportionally the most mature ecosystem of the three: 42% of Kenyan startups are at Growth Stage, compared to 25% for Nigeria and 24% for South Africa.
Exits Are Rare But Real: 18 Gone, 3 Acquired
Only three companies in the dataset have been acquired: InfiniLink (Egypt, Hardware), Libryo (South Africa, Business Intelligence), and Safiyo AI / Survey54 (South Africa, Market Research). All three were at Growth Stage, suggesting acquirers are targeting companies with demonstrated traction rather than making early bets. The exit market for African AI is thin, but it exists.
| Company | Country | Sector | Status |
|---|---|---|---|
| InfiniLink | Egypt | Hardware | Acquired |
| Libryo | South Africa | Business Intelligence | Acquired |
| Safiyo AI (Survey54) | South Africa | Market Research | Acquired |
The 18 Defunct: A Harsh Reality
Agriculture (4 defunct) and Healthcare (3 defunct), the sectors with the strongest vertical AI ambitions, also account for the most failures. This may point to the structural difficulty of building mission-critical AI in sectors with long sales cycles, regulatory complexity, and infrastructure constraints across most African markets.
The 2018 founding cohort stands out: 8 of the 18 defunct companies were founded that year. Building at the top of a hype cycle, entering market during a pandemic, and running out of runway before the 2021 to 2022 funding surge could reach them, this cohort faced a particularly difficult sequence of circumstances. Notable names include Gro Intelligence (Kenya, AgriAI), which had attracted significant global attention before shutting down, and Tambua Health and Sophie Bot, both Kenyan health AI startups that did not survive.
The New Guard: 36 Startups Founded in 2024 and 2025
The most recent cohort is, as expected given its youth, 100% active. Nigeria dominates with 14 new startups in this period, but the geographic spread is notable. Rwanda (4), Kenya (4), Tunisia (4), and Egypt (3) all have meaningful new-entrant cohorts.
The 2024 to 2025 class is concentrated in Software Development, Business Intelligence, Finance, and Education, reflecting the availability of foundation models that have lowered the barrier to building AI-powered B2B tools. Legal AI also has three new entrants from Nigeria alone in this window, reinforcing its status as an emerging vertical to watch.
The presence of companies like Yamify (Democratic Republic of Congo) and SenMixMaster (Senegal) signals expansion into markets that have historically been underrepresented. The next wave of African AI may push further into Francophone Africa than most ecosystem maps currently suggest.
We Will Follow With a Funding Breakdown
This analysis has focused on the ecosystem in breadth: how many companies, where, in what sectors, and at what stage. In a follow-up piece, we will look at the funding dimension: how much capital has flowed into African AI startups, from which sources, and how it maps against the sector and geographic distribution charted here.
In the meantime, if you are interested in how capital has been moving across African tech more broadly, our climate tech data brief is a useful companion read: Africa’s Climatetech Capital: Inflection Point — What the 2025/2026 Funding Data Reveals.
About This Data
Dataset and Methodology
This analysis draws on data compiled by Dr Chinasa T. Okolo of the Brookings Institution, published via Harvard Dataverse. The dataset covers AI startups operating across Africa and has been updated across multiple periods.
Full citation: Okolo, Chinasa T. 2022. “AI Startups in Africa.” Harvard Dataverse. doi:10.7910/DVN/Z0PKGO
We used three sheets: the primary 2025 tracker (207 companies), an enriched adjusted 2025 sheet with customer and team metadata, and a 2022 baseline of 104 companies for longitudinal comparison. Sector classifications vary in granularity and should be treated as directional.
Customer Segments (Adjusted Data)
Based on subset with complete customer data
- Businesses (general) — 26 startups. Largest segment; reflects B2B-heavy ecosystem.
- Financial Institutions — 16 startups. Second-largest, underscoring fintech AI density.
- Patients / Healthcare Facilities — 13 startups. Strong healthcare vertical with both B2B and B2C approaches.
- Farmers / Agri Businesses — 11 startups. Africa-specific focus on smallholder and commercial agriculture.
- AI/ML Practitioners — 9 startups. Infrastructure and tooling layer is growing.
Cohort Tracking: 2022 → 2025
Key Watch Areas for the Story
- Legal AI in Nigeria: 3 startups in 2024–25 alone. Possible new breakout vertical.
- Egypt’s ascent: From 3 to 11 companies (+267%). North Africa’s AI flag-bearer.
- 2018 cohort mortality: 8 of 18 defunct companies were founded in 2018. A cautionary data point.
- Infrastructure/tooling layer: 9 companies serving AI/ML practitioners — the “picks and shovels” play is real.
- Kenya’s maturity premium: 42% of Kenyan startups at Growth Stage vs 25% for Nigeria.
- Francophone expansion: Rwanda, Senegal, DRC, Togo, Cameroon all gaining representation.
- All 3 acquisitions are Growth Stage: Exit market is thin but targets proven companies.
Stage vs. Survival Rate
Active rate by stage. Notably uniform — likely reflects survivorship bias in dataset composition.
The Defunct 18 — Sector Breakdown
94% of defunct companies were at Early Stage. 44% founded in 2018.
