The financial services sector is emerging as one of the fastest adopters of artificial intelligence (AI), with implementation shifting from experimentation to operational deployment.
This is according to Yacob Berhane, COO and head of growth at Quill, speaking during a panel discussion at the Standard Bank Africa Unlocked 2026 conference in Cape Town.
He was joined by other panellistsCatherine Muraga, MD of the Microsoft Africa Development Centre; Nkemdilim Uwaje-Begho, CEO of Future Software; and Adam Ikdal, chief strategy officer at Standard Bank.
The discussion − titled: “AI in the engine room: deploying technology across African industries” − delved into AI early adoption and deployment in African industries, AI literacy at C-suite level, embedding AI in the organisation, change management and automation.
The panellists also highlighted AI’s practical applications and challenges.
Responding to the question of operational use of AI, Berhane pointed to financial services as the sector where adoption is moving fastest. “Being able to compute data, seeing what is fraud, what is a good borrower, what’s a good credit, what do I underwrite?
“The ability to assess someone and service them in a way that you wouldn’t before, because you were servicing people that were high-net worth individuals, because that’s where you made your money.
“You’re now being able to pull a lot more people into the financial ecosystem, giving them access to the things that effectively make the economy more robust.”
Detailing Standard Bank's AI journey and operational value to the business, Ikdal said the big-four bank started experimenting with generative AI last year.
“The bank's been using traditional AI for a long time, and it drives a lot of decisions that we’ve made historically in the bank. Generative AI is a new beast that we took on last year, and what we figured out was that generative AI can read documents very well.
“How we take the power of that capability to deliver faster services to our customers has been a key focus for us. What we discovered through the process was that it’s easy to build a prototype in a week, but it’s very hard to get it in production – it takes a few months at times. That forced us to go back to the drawing board in terms of how we build something that we can get everybody in Standard Bank to use, to build scalable AIeffectively. That’s the foundation’s work that we’ve been doing.
“What we’ve also discovered is that the cool stuff is easy, the boring stuff is hard, but getting the boring stuff right is extremely important for the scaling.”
On the importance of AI governance and risk management in large corporations, Ikdal added that it’s the brake needed to avoid crashing.
“Doing governance right is extremely important to make it work. Being in a fundamentally regulated industry, you’re forced to think about the implications of doing things before you do it, which really gives us the right thought process and approach to deliver innovation faster.”
Change management
The discussion also shifted to the potential impact of AI on job descriptions and the need for business leaders to understand AI’s role in productivity and task automation.
They also stressed the importance of basic literacy in AI, including understanding models, tokens and AI transformation, to avoid treating AI as a technology project.
Muraga said the fact that certain tasks will disappear and be replaced by AI calls for HR departments to have conversation around what is a job. “The same way COVID-19 forced us to think about what is work. ‘We used to say, I’m going to work. What is work today?’ AI will change, or has started changing the contents in our job descriptions.”
On the executive front, Uwaje-Begho said it needs to start with the basics, understanding the tools, AI transformation and building a strategy around that.
“If you just know what AI is, it’s very easy to hand it off to the technology guys and treat it as a technology project. A lot of the time your technology department doesn’t have enough business context, which means they can build technology, but if you just hand it to them, they’ll build what they think they need to build.
“With AI, it’s really understanding that the tool is one thing. The other thing is how to build a strategy around that. How do I bring the business context in, especially in a large organisation.”
She continued that the idea with real AI transformation is understanding that organisations are restructuring – looking at what is a job. “So, you bring in these agents, who do they report to? Do they report to IT? Who owns them, who does their performance management? What happens to the people that they replace? In a large organisation that’s really what the CEO should be thinking about.”
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