Across sectors such as banking, telecommunications, government services and retail, organisations are exploring AI to improve customer engagement, reduce operational costs and automate routine processes.
However, adoption across Africa comes with unique challenges, including fragmented systems, multiple languages, data protection concerns and limited local infrastructure.
Against this backdrop, a growing number of African technology companies are attempting to build AI solutions that reflect the continent’s realities rather than simply adapting technologies created for other markets.
One of those companies is BimpeAI, a startup developing enterprise AI agents designed to help organisations handle customer interactions and complete business workflows while maintaining human oversight.
Unlike conventional chatbots that mainly respond to questions, the company’s technology focuses on enabling AI systems to understand requests, connect with business platforms and take action within controlled environments.
In a recent interview with Business Insider Africa, Samuel Adekunle, founder of BimpeAI, explained how his experience across global technology organisations shaped his decision to build an AI company focused on practical business applications for African institutions.
From global technology companies to building for Africa
Before launching BimpeAI, the entrepreneur worked across product development, startup programmes, enterprise technology and developer ecosystems, including roles connected to Meta, Turing, Deloitte and Datamellon.
Those experiences exposed him to both the scale of global technology platforms and the difficulties businesses face when trying to convert emerging technologies into measurable value.
“Before BimpeAI, I worked across product, startup programmes, enterprise technology, and developer ecosystems, including roles connected to Meta, Turing, Deloitte, and Datamellon,” Adekunle said.
“Those experiences gave me a useful mix of perspectives. I saw how large technology platforms are built and scaled. I also saw how startups and enterprises can struggle to turn new technology into real operational value.”
His interest in artificial intelligence deepened after observing the gap between impressive demonstrations and solutions that address everyday business challenges.
“What pulled me deeper into AI was the practical side of it. My co-founder had also worked closely with enterprises, training teams on how to apply AI in customer operations,” he said.
“That pushed us to ask more practical questions: could AI help companies serve customers faster? Could it connect to existing systems? Could it reduce manual work? Could it move beyond demos into real business workflows? Those questions eventually shaped BimpeAI.”
Moving beyond chatbots to enterprise AI agents
While many businesses have experimented with chatbots, the BimpeAI founder believes the next stage of enterprise artificial intelligence will involve systems capable of completing tasks rather than simply providing responses.
The company was created after identifying a common problem: businesses interact with customers through several platforms, but those conversations often remain disconnected from the systems required to resolve requests.
“The problem we set out to solve was simple: we noticed that businesses were already speaking to customers across SMS, WhatsApp, Instagram, phone calls, and websites, but those conversations were disconnected from the systems where actual work happened,” he said.
“A chatbot can answer a question. That is useful, but it is not enough.”
For the startup executive, enterprise AI agents must go further by understanding customer needs, accessing approved systems, following workflows and completing tasks while leaving a clear record of their actions.
“An enterprise AI agent needs to go further. It should understand the customer’s request, check the right system, follow the right workflow, update a record, escalate when needed, and leave a clear audit of what happened,” Adekunle said.
“That is why we chose agents over conventional chatbots. The future is not just AI that replies to queries, we want AI to be able to safely execute and resolve those queries in business operations.”
Building AI for African business realities
Beyond the technology itself, Africa presents a distinct environment for AI adoption. Many organisations operate across multiple languages, rely heavily on voice communication and serve customers with different levels of digital access.
For BimpeAI, the focus is on developing systems that can function within these conditions while meeting enterprise requirements.
“We are building human grade AI agents that help organisations use AI inside controlled workflows or operations,” the founder said.
“When a customer calls or sends a message, the agent can understand the request, check the approved business system, follow the right workflow, update the record and either complete the task or escalate it to a human.”
However, he stressed that enterprise AI cannot focus only on intelligence. Security, accountability and governance are equally important, particularly in regulated industries such as finance and public services.
“In enterprise environments, especially financial services and public-facing institutions, the agent cannot just be intelligent. It has to be governed.”
“That means clear permissions, audit trails, escalation rules, approval boundaries and human-in-the-loop controls. The AI should know what data it can access, what actions it can take and when it must hand it over to a person.”
According to the technology executive, this approach is what makes AI suitable for African institutions dealing with large customer volumes and sensitive information.
“Many organisations here deal with high customer volumes, voice-heavy engagement, revenue follow ups, multilingual users and sensitive data. The opportunity is not just automation. It is automation with governance, local context and operational control.”
Scaling through partnerships and enterprise adoption
As the company moves from development into wider deployment, BimpeAI is seeking to expand its infrastructure and partnerships across the continent.
The founder said the company is raising capital to accelerate growth while building relationships in telecommunications, cloud infrastructure and enterprise distribution.
“We are currently raising to scale what we have already validated in the market,” he said.
“At this stage, we are not publicly announcing all investor or partner names, but the important point is that our support is not only financial. We are also building with strategic partners across telecoms infrastructure, voice connectivity, cloud and data infrastructure, and enterprise distribution in Africa.”
The funding will support enterprise deployments, voice AI infrastructure and controlled deployment options for regulated customers.
“The funding we are raising will support three main milestones: scaling enterprise deployments, deepening our voice AI infrastructure, and strengthening our on-premise and controlled deployment options for regulated customers.”
Already, the company is working with organisations across financial services, public service revenue collection, examination-related workflows and other customer-facing operations.
The entrepreneur said demand is coming from institutions that want AI adoption but also require strong controls around security and customer data.
“Regulated institutions want AI, but they want it deployed with governance, auditability, and control over where customer data sits.”
Africa’s opportunity to shape the AI future
As global competition for artificial intelligence leadership grows, the BimpeAI founder believes Africa must move beyond being only a consumer of technology developed elsewhere.
“A genuinely African AI ecosystem means we are not only users of AI. We are also builders of the models, datasets, infrastructure, and governance standards that reflect how our markets work,” he said.
Language, he added, will be a major factor in creating systems that work effectively across the continent.
“AI in Africa has to understand our accents, our English, our local languages, our slang, and the way people switch between languages in one conversation.”
He also highlighted the importance of infrastructure, talent development and cooperation between governments, universities and businesses.
“This does not mean Africa should reject global AI platforms. It means we should not depend on them completely. We need to build the local layer that makes AI useful and safe for our own markets.”
However, the executive warned that AI adoption must be guided by responsible policies.
“The biggest risk is not AI itself. The biggest risk is adopting AI without governance.”
He said governments should create clear rules while supporting local innovators, businesses should adopt AI responsibly, and universities should strengthen technical training.
“Africa should not wait for the AI future to arrive from outside. We have to build part of it ourselves.”
