AI don make software development cheaper, but African investors say startups need more than AI features to attract funding. Local-language technology, strong customer relationships, proprietary data, and clear ways to make money fit determine which businesses stand out.
AI Don Make Building Software Easier, But Funding Still Get Rules
Artificial intelligence don change how people dey build technology businesses, and Africa no dey outside the movement.
From AI-powered customer service to automated financial services and educational tools, founders dey explore different ways to use the technology solve problems across the continent.
But as more startups begin enter the market, one important question don emerge: wetin go make investors choose one AI startup over another?
According to interviews TechCabal conducted with six African investors between April and September 2026, the answer go beyond the AI model wey a startup dey use.
The investors include Babacar Seck of Askya Investment Partners, Eloho Omame of TLcom Capital, Emmanuel Adegboye of Madica, Magnifique Ishimwe of the Development Bank of Rwanda, Husein Merchant of Village Capital, and Benjamin Toulouze of AXIAN Investment.
Their message get one common theme: using AI no automatically make a startup worth investing in.
As access to foundational AI models becomes easier, startups need to show what makes their businesses difficult to copy, how dem fit attract and retain customers, and how dem plan to generate revenue.
African Languages Fit Become a Major AI Opportunity
One of the biggest opportunities investors identify na voice AI built around African languages.
For many people across Africa, English, French, or Portuguese no be the language wey dem dey use most comfortably for everyday conversations.
This creates an opportunity for AI products wey fit communicate with users in languages dem already understand.
Emmanuel Adegboye, head of Madica, highlights the example of somebody for a rural community wey speaks only Wolof.
For such a person, voice technology wey delivers useful information in Wolof fit make digital services more accessible without requiring the person to first learn English.
The same opportunity dey for Nigeria, where products wey understand Yoruba, Igbo, Hausa, and Nigerian-accented English fit help more people interact with digital services.
Babacar Seck of Askya Investment Partners also sees voice AI as an opportunity to connect businesses with customers through their preferred languages.
The idea no be simply to translate existing applications. E involve building technology wey fit understand how people speak, process their requests, and provide useful responses within their local context.
For example, a bank fit use voice AI to communicate with customers who struggle with text-heavy applications. A business fit automate customer support, while a government agency fit make important information accessible to people who prefer speaking their local language.
However, building this kind technology no easy.
African-language speech data remains limited, and creating reliable voice systems requires relevant datasets, testing, and continuous improvement.
Investors see this challenge as an opportunity because startups wey successfully build strong language datasets and useful products fit develop advantages wey competitors may struggle to replicate.
Local Knowledge Fit Give Startups an Advantage
Another important lesson from the investors na the value of understanding local problems.
A startup fit use the same foundational AI model as thousands of competitors around the world. But the way e applies that technology to a specific African problem fit make the difference.
The article identifies examples such as Pewbeam AI, wey builds software to project Bible verses during live church services, and YarnGPT, wey develops speech technology for Nigerian-accented English and local languages.
These examples show how founders fit apply AI to particular audiences instead of building generic products wey attempt to serve everybody.
The number of African AI startups also dey increase.
According to TechCabal Insights figures cited in the article, the organisation tracked 207 African AI startups across 17 countries in 2025, compared with 104 in 2022.
That represents roughly a doubling over the period.
Most of the newer startups operate in areas such as software development, business intelligence, finance, and education, where readily available AI models have reduced some barriers to building products.
But more startups also mean more competition.
Eloho Omame of TLcom Capital explains say when technology makes products cheaper to build, companies need other ways to defend their positions.
These advantages fit include a trusted brand, strong customer relationships, network effects, proprietary data, or switching costs.
In simple terms, if another founder fit build a similar product within a short period, wetin go make customers stay with your own?
Na the kind question investors dey ask.
The Strongest Advantage Fit Be How Deeply Your Product Enters a Business
For some AI startups, the biggest competitive advantage no necessarily come from developing a new AI model.
E fit come from how deeply their software connects with the customer’s daily operations.
Omame gives an example of an application programming interface, or API, business wey integrates its fintech product into the software systems of other companies.
When one product becomes part of another company’s everyday operations, removing am fit require significant time, money, and technical work.
This creates what investors call switching costs.
AI fit make it easier for competitors to develop similar functionality, but replacing a system wey already works across thousands of customer relationships may be much harder.
The same integration can also help businesses improve revenue or reduce operating costs.
Omame says investors need to understand how AI makes a product cheaper to develop or deliver, and whether the startup captures some of the resulting financial benefit.
For instance, a company fit use AI to reduce the cost of customer support.
The business could pass the savings to customers through lower prices, retain the savings to improve its margins, or combine both approaches.
From an investor’s perspective, the important thing na to understand whether the technology creates a sustainable business advantage.
Revenue Still Matter Pass Fine AI Demo
Even when a startup has an interesting product and a strong technical team, investors still need to understand how the business go make money.
Magnifique Ishimwe of the Development Bank of Rwanda explains say building an application no necessarily be the hardest part of starting an AI company.
The real challenge na execution.
A startup fit build a chatbot, launch an application, and attract attention. But if customers no dey willing to pay for the service, the company fit struggle to sustain itself.
AI businesses also face costs associated with computing resources, engineering talent, and product development.
These expenses fit become serious problems when startups continue to spend money without generating enough revenue.
Ishimwe says some AI investment opportunities become difficult to evaluate when investors cannot see a clear path to profitability.
He also notes that investment decisions depend on the type of financial instrument being used. A business that requires years of spending before generating meaningful returns may not suit every investor.
This point important for African founders because funding strategies differ between investors.
Some investors may support companies wey need significant upfront capital to build infrastructure, while others may prefer businesses with clearer revenue opportunities and shorter paths to sustainability.
For founders, the lesson no be say every AI startup must become profitable immediately.
Rather, dem need to understand their cost structure, identify customers who will pay, and explain how the business can eventually generate sustainable returns.
Some Investors Still Want to Fund AI Infrastructure
Although many opportunities dey for AI applications, some investors also see value in building the underlying technology infrastructure.
Benjamin Toulouze of AXIAN Investment says the company is interested in AI infrastructure and has already made investments in the area.
One example highlighted in the article na WideBot AI, which develops large language model technology for Arabic speakers.
The article also identifies Nucleon Security, a Moroccan company focused on cybersecurity technologies.
For Toulouze, one important issue na data sovereignty.
This refers to the ability of countries and organisations to maintain appropriate control over their data and how it is processed.
Africa consists of 54 countries, each with different markets, languages, regulations, and technology needs.
Building AI infrastructure across these markets can be challenging, but investors also see opportunities for companies that address specific regional requirements.
Another example na ChipMango, a company involved in chip design.
According to the article, Madica joined the company’s $1.9 million seed funding round, led by Atlantica Ventures, in September 2026.
The company’s model involves working with Nigerian universities to recruit and train engineers before selling chip-design services to global customers.
These investments show that some African investors are willing to support businesses beyond the application layer.
However, infrastructure businesses can require different amounts of capital, technical expertise, and time to scale compared with software applications.
The appropriate investment strategy will depend on the company’s business model and the investors’ objectives.
Africa Risks Depending Too Much on Foreign AI Infrastructure
Another concern raised by investors na the possibility that Africa could become heavily dependent on AI infrastructure built and controlled elsewhere.
Emmanuel Adegboye says global investment in AI is concentrating around a relatively small number of funds and startups, particularly companies developing infrastructure.
He also points out that much of the funding entering Africa comes from outside the continent.
This creates a potential challenge: if African investors concentrate only on consumer-facing AI applications, the deeper infrastructure powering those products may remain owned and controlled by companies elsewhere.
Babacar Seck raises another issue involving data centres.
Although discussions about Africa’s technology future often highlight the need for more data-centre capacity, operators also need sufficient demand from customers to support their businesses.
Seck notes that some African startups and scale-ups spend substantial amounts on cloud infrastructure.
Connecting infrastructure providers with companies that need their services could help address the gap between available capacity and actual demand.
The talent pipeline presents another challenge.
Africa has institutions training AI engineers and researchers, but some graduates move abroad because local companies may not yet offer enough opportunities at the same scale.
Retaining talent will require more than education alone. Businesses also need the funding, customers, and technical opportunities to employ skilled people.
For African countries, the long-term question is how to support both the businesses using AI and the companies building the infrastructure underneath it.
Wetin African AI Founders Need to Understand
The investors’ comments point towards several practical lessons for founders.
First, solve a real problem. No build an AI product simply because the technology dey popular. Identify a customer problem and demonstrate how your product solves am.
Second, develop something competitors cannot easily copy. This fit include proprietary data, deep integration with customer systems, specialised language capabilities, or strong distribution.
Third, understand your revenue model. Know who go pay for your product, how much dem fit pay, and whether the revenue can cover your operating costs as the business grows.
Fourth, use local context as an advantage. African languages, market conditions, business practices, and customer needs can create opportunities for products designed specifically for the continent.
Finally, choose the right investors. Different investors have different expectations, funding structures, and timelines. Founders need to understand whether their business model matches the type of capital they are seeking.
The Bottom Line
AI is making it easier for African founders to build software, experiment with new ideas, and launch products.
But as access to the technology becomes more widespread, the ability to use AI alone may no longer be enough to stand out.
The strongest opportunities may lie with companies that combine AI with deep local knowledge, proprietary data, valuable customer relationships, and a sustainable business model.
Voice AI for African languages offers one example of how founders can address problems that global products may overlook.
Meanwhile, infrastructure investments, specialised talent, and data sovereignty remain important considerations for the continent’s long-term AI development.
The real opportunity no be simply to build another AI startup. Na to build a business wey uses AI to solve a problem people care about, and does am in a way competitors cannot easily copy.
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