Every Thursday at noon (WAT), Delve Into AI will provide nuanced insights on how the continent’s AI trajectory is shaping up. In this column, we examine how AI influences culture, policy, businesses, and vice versa. Read to get smarter about the people, projects, and questions shaping Africa’s AI future.
For years, Sam*, a product manager at a Tier-1 Nigerian commercial bank, spent over two hours scrolling X to compile feedback about their latest bank app features. Now, he spends less than 10 minutes on this task, thanks to Grok, an AI assistant integrated with X.
He simply types a prompt: “Summarise the top customer complaints on X for our bank app for the last two weeks.” A few seconds later, a summary of complaints and recent posts outlining real user discontent is displayed.
“It’s like you have someone beside you who you can dig deep for you, present the data, and help you draw insights to make valuable decisions,” he said.
Sam, who asked to go only by his first name, is part of a growing list of commercial bank employees who are increasingly relying on AI tools to help automate and speed up their daily tasks. Whether these banks’ leadership is open to embracing these tools internally remains an open question.
Over the past decade, commercial banks have mainly restricted their AI innovation to customer-facing virtual assistants and chatbots, particularly due to factors such as regulatory uncertainty, cost concerns, and a lack of internal infrastructure. In 2018, United Bank for Africa (UBA) released Leo, an AI-supported virtual banking assistant. Three years later, Zenith Bank launched Ziva, an AI-powered chatbot tool accessible via WhatsApp.
But while these banking industry’s embrace of these customer-facing generative AI tools is forward-thinking, the reception from the public hasn’t been promising so far. According to a KPMG 2024 survey, 73% of retail banking customers in Nigeria rarely engage with these chatbots, raising more questions about their long-term value. This is causing a rethink in AI strategy at various commercial banks.
“Before, it was: ‘How can we integrate this fun, interesting tool into our systems?’ But now, there’s a thought process around: ‘How can AI drive tomorrow’s sense of what banking should be?’” said Dr.Olumide Okubadejo, an AI strategist for commercial banks.
With the rise of popular generative AI platforms, such as Grok and ChatGPT, there has been an increasing interest in redefining ways to adopt AI in the banking space. In December 2024, Bello Hassan, the head of the Nigeria Deposit Insurance Corporation (NDIC), encouraged banks to adopt AI tools to strengthen their fraud detection approaches.
For some bank executives, there is a growing concern that delays in strategic AI adoption may leave them falling behind. At the Innovate AI conference in February 2024, Abubakar Suleiman, Managing Director of Sterling Bank, warned; “If we fail to pay attention to artificial intelligence, all our efforts at ease of doing business will come to nought.” He added; “Companies that fail to embrace AI will become less competitive and they will die.”
Some banks are now exploring the practical applications beyond customer-facing tools. Banks are starting to look within and identify opportunities for internal adoption and workflow efficiency. One UBA staff member who preferred to remain anonymous noted that in the Q1 of 2025, the bank renamed its internal “Advanced Analytics” team to “Artificial Intelligence & Advanced Analytics,” signalling more serious investment in the space. Similarly, a staff at Wema Bank disclosed that they receive emails and communications frequently from bank leadership focused on highlighting various ways to integrate AI tools into their daily workflow.
“We received a direct mandate from the Group Managing Director to push the AI buzz to drive operational efficiency. Together with our Chief AI Officer, we’ve been aggressively driving AI awareness across [UBA] bank,” the same UBA staff member who preferred to remain anonymous told . “The response so far has been very positive; teams are curious, engaged, and increasingly open to experimenting.”
Experimentation in practice
I spoke with half a dozen staff members from Tier 1 and Tier 2 banks, including UBA, Zenith Bank, Access Bank, and Wema Bank. While AI adoption is still in its early stages, staff across departments are already experimenting with generative AI tools to streamline their daily tasks.
“We deal with a lot of corporate accounts, so we can’t afford to make mistakes,” said one employee at the customer data maintenance service (CDMS) unit of a Tier-1 bank. “Before, it could take 20 minutes to process an application, especially when reviewing legal-heavy documents. Not everyone went to law school. I use AI to break down those complex terms quickly,” the staff said.
In spite of the adoption, some remain sceptical of the AI ‘buzz’. “In marketing, the bank has different products that we need to go from one place to another and market to customers,” said a staff at Access Bank. “AI cannot do that. I don’t think it will have that effect on marketing.”
Marketing staff at other banks are finding ways to incorporate the tools into their workflow regardless. “I use them for prospecting, when mapping out new areas, environments, and companies that you could explore in terms of onboarding new clients to your bank profile,” said a Zenith Bank employee, adding that he uses tools like ChatGPT to create tailored cold emails for potential clients to save time.
Several bank staff I interviewed also mentioned using these tools to respond to internal emails, saving a significant amount of time on constant back-and-forth communication. These employees also mentioned using tools like Microsoft Co-Pilot to take minutes of meetings, allowing them to have notes to refer back to later.
UBA Bank and Wema Bank staff members said they had received some level of training on the ethical use of these applications. At Access Bank, however, two employees I spoke with claim they have not received any formal communication on how to incorporate these tools into their work properly.
Bank staff continue to experiment with AI, whether through custom-built tools or popular platforms like ChatGPT. There is a need for bank leadership to think beyond casual usage and start thinking more strategically about upskilling training for staff, especially to maintain strict compliance with the Nigeria Data Protection Regulation (NDPR).
Okubadejo believes proper training of bank staff could go a long way. “It becomes a question of prompt engineering,” he said. “How do we train our people in such a way that they understand how to ask AI tools the right questions without the use of personal customer data and still get the right information necessary?”
The opportunity
Internal teams, such as UBA’s AI and Advanced Analytics unit, are working on in-house solutions, including small language models, that can support compliance and fraud detection efforts within the bank. While in-house solutions are being developed, startups are also eager to explore the rising opportunities to drive AI adoption in legacy companies like commercial banks.
Nigerian AI startup Lumnic aims to build enterprise tools primarily for supporting back-office operations. Its core offering is an enterprise search platform that enables staff to retrieve and query internal data more effectively. In comparison to other global players like OpenAI, Lumnic aims to create more localised, secure offerings that are trained on local data, which is particularly relevant for specific sectors such as banks in Nigeria, according to co-founder Nnamdi Ehirim.
“The companies that will win are those that invest completely in modelling localised data, and in understanding the nuances of that data, within the financial sector and beyond,” Okubadejo noted.
Still, technology alone is not all it takes. Ultimately, the success of AI integration into the banking sector will also depend on bank employees’s ability to embrace its use.
One UBA staff member recalls a question frequently used by the bank’s leadership to staff members. “Do you really have 10 years of experience, or is it just one year repeated 10 times?” It is a call to action. A pointed way to challenge employees to embrace AI tools or risk getting left behind.
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