Would you hand over part of your business to Artificial Intelligence (AI)? For most African founders, the idea feels equal parts exciting and risky. AI promises to cut costs, speed up growth, and unlock new opportunities but it also raises questions of trust, affordability, and fit for our local context.
The truth is, it is not about building the next ChatGPT. It is about whether AI can make your startup run leaner, smarter, and faster today. And in a recent masterclass hosted by the Futuremakers Women in Tech Accelerator Program, founders and ecosystem leaders dug into exactly that: how to cut through the noise and make AI actually work for startups.
The $100B Opportunity Hiding in Plain Sight
Africa’s AI story is not speculative. A recent McKinsey report estimates that generative AI could add between $61 billion and $103 billion annually to Africa’s economy when deployed at scale.
Yet, that promise comes with a big “but”: most organizations worldwide have not gotten past pilot projects. McKinsey’s “Moving past gen-AI’s honeymoon phase” research found that only about 11% of companies have adopted generative AI at scale.
The disconnect between what AI could deliver and how little of it is being scaled tells us one thing: there is room for agile startups to lead where larger firms hesitate, and the ones that act early will capture the lion’s share of the value.
First Steps: Turning Potential into Practice
With such a wide gap between AI’s potential and its actual use, the masterclass conversations quickly shifted from billion-dollar projections to practical first steps. Founders wanted to know: “Okay, so what can I actually do with AI this week?”
One clear starting point was prototyping. Just a couple of years ago, a non-technical founder needed a developer to launch even the simplest demo. Now, AI-powered no-code tools can generate mock-ups or working versions in days. As Rhoda Kingori, Co-founder of Zydii, put it: “If you think it, you can prototype it.” That shift makes it possible to test customer interest before investing heavily in product development.
Another recurring theme was automation. Participants shared how simple tools were already cutting out repetitive work. One founder described setting up a WhatsApp bot to handle FAQs, freeing up the team for higher-value tasks. Others mentioned leaning on Canva’s AI features to design pitch decks and marketing assets, work that previously meant hiring freelancers.
Then came sales. Instead of spending hours on cold outreach, founders pointed to platforms like Apollo, which can help identify and qualify hundreds of leads every month. For a lean startup, that is like adding a sales team without the payroll.
The message landed clearly: “Lead with the solution, not the technology,” said Alfred Ongere, founder of AI Kenya. For founders, that means the first wins with AI won’t come from grand gestures but from small, practical shifts that make the business run leaner and smarter. And for women entrepreneurs in particular, those small shifts are proving to be powerful game-changers.
Why Women Founders Stand to Gain
For women-led startups, the promise of AI isn’t just efficiency, it’s leverage. Access to capital and technical talent remains one of the toughest hurdles. In 2024, female-founded startups represented nearly 18% of deals in Africa, yet secured only 7% of equity funding, according to Partech.
That funding reality is why AI felt so urgent in the masterclass. “Sometimes it’s really hard to find a technical founder because you don’t have money,” said Rhoda Kingori, Co-founder of Zydii. “But right now, you can deploy the first version of products for testing, create prototypes with no-code leveraging AI.” For women founders already balancing multiple roles, those shortcuts meant more time to focus on growth.
AI may not erase the funding gap, but, in an ecosystem where women consistently receive a fraction of available capital, it provides a way to move faster, show traction earlier, and compete on their own terms. And with that shift comes a bigger question, what challenges should founders be ready for as AI adoption deepens?
The Roadblocks No One Can Ignore
For all its promise, AI is not a silver bullet. The founders and experts in the masterclass were quick to flag the pitfalls that can trip up startups if adoption is rushed or unstructured.
Mindset matters. “Lead with the solution, not the technology,” reminded Alfred Ongere of AI Kenya. The temptation to market AI for its own sake is real, but it often backfires. Customers don’t care that your product runs on AI. They care that it works. For early-stage startups, the challenge is resisting the hype and staying laser-focused on solving real problems.
Data is everything. “It’s literally garbage in, garbage out,” warned Rhoda Kingori of Zydii. And she’s right: analysts note that if AI systems are trained on bad or incomplete data, the outputs will be unreliable at best and misleading at worst. In Africa, this problem is even sharper, where structured datasets are limited and data governance is still evolving. For founders, that means starting small, even if it’s just keeping clean, consistent customer records in a spreadsheet, before layering AI on top.
Teams need rethinking. The promise of efficiency can also create fear. As Jonathan Thuo of Crenovate Technologies pointed out, AI can automate up to 70% of repetitive tasks. That sounds efficient, but it also raises a leadership question: what happens to people when their old jobs disappear? Studies on AI in Africa warn that automation of routine tasks could threaten traditional employment patterns unless companies reskill and redeploy talent. For startups, the real opportunity is freeing people to focus on creative, relational, and strategic work.
Structural limits remain. Beyond the startup level, ecosystem constraints are still real. McKinsey warns that in Africa, AI adoption is slowed by bias, privacy concerns, and limited infrastructure. Without better connectivity, local datasets, and regulatory clarity, the risks of uneven adoption grow.
None of these are reasons to avoid AI. But they are a reminder: successful adoption is about building the discipline, systems, and culture to use it responsibly. And that raised a bigger theme in the masterclass: what does it look like to build AI for Africa’s reality, not just import solutions designed elsewhere?
Building for Africa’s Reality
One theme that ran through the masterclass was clear: Africa cannot simply copy-paste AI solutions built elsewhere. With countries that speak dozens of languages, unique cultural norms, and limited local datasets, context matters.
Panelists pointed out that mainstream AI systems often miss these nuances. McKinsey warns that bias and poor representation can be amplified in regions where data is sparse. For startups, this creates both a challenge and an opening: those who build with local data and cultural understanding can create products global platforms overlook.
As one participant summed it up: AI will only be truly valuable in Africa when it speaks our languages, reflects our realities, and solves problems people actually face.
The Bottom Line
At its core, the masterclass showed that adopting AI is about starting small, staying customer-focused, and building the systems that make the tools truly work.
For women founders, those lessons are even more urgent. In an ecosystem where access to funding and technical talent is still uneven, AI won’t erase barriers, but it does create faster routes to traction and growth.
AI is not the future of African startups. It’s already here. The challenge now is adapting it to Africa’s context and, in doing so, shaping solutions the world hasn’t seen before.