The era of just experimenting with AI in African banking is over. Banks are now focused on getting real, measurable results. In partnership with African Banker Magazine, we surveyed 277 banking leaders across 37 countries to see where the industry stands. We found a clear divide. Banks that build AI into their core systems are winning, while banks that treat AI as a side project are hitting walls. Our findings highlight three key areas where banks are separating themselves from the pack: → Measuring results: 85% of banks that actually track their AI performance are hitting their targets. → Old tech barriers: Half of executives say their legacy systems are the main thing slowing down their AI progress. → The power of partners: Banks that use outside AI frameworks are twice as likely to track their returns compared to banks trying to build everything in-house. Ambition is great, but it is hard to deliver if your systems are disconnected. Read the full findings in our new report: https://lnkd.in/e86WggP9

African banking is no longer experimenting with AI it's delivering results. Some key takeaways from the report: • Track AI performance to measure impact. • Legacy systems are still the biggest roadblock. • The right technology partners can accelerate success. AI is only as powerful as the foundation behind it. Read the full report below!

AI in banking isn't just about relying on the most powerful models. The real advantage comes from building the right data and infrastructure foundation. Watch the full film to discover why. https://cnb.cx/44ulKe7 Paid post by Huawei

One stat from nCino's new AI in Banking Benchmark stuck with me: 93% of banking executives cite at least one data governance challenge, yet AI adoption is accelerating across the board. There's a real gap between moving fast and moving with accountability, and this report gets into why. Worth a look if you're in financial services: https://lnkd.in/eeNZJzDz

Nordic banking leaders from Danske Bank, S-Pankki, and Nordea got candid with us about AI at an event we hosted in the spring. The most underrated first step they found was mapping processes that lived only in people’s heads, long before choosing any model. Read the article and learn more about AI in banking: https://hubs.li/Q04mCX-Z0

How can middle market companies prepare for the next phase of AI adoption? Capital One Commercial Bank’s Head of Digital Banking Catherine Parker shares her perspective. i.capitalone.com/GW3ZbM3a9

In a time where AI can be overwhelming, we are extremely focused in our Digital Banking team on two outcomes: 1. B2B data linkages enabling better client outcomes and models 2. Agent ready infrastructure If you want to read more about where we are heading and what we have learned, click below! 👇

Banks are moving beyond AI pilots and focusing on production‑scale impact. This upcoming webinar explores how agentic AI platforms are being deployed across core banking operations—with governance, workforce transformation, and measurable outcomes front and center. John Emmert Saket Sinha Julie Aguirre Jeffrey Torres https://lnkd.in/g5RercMs

Customer expectations in banking are changing fast. People want every interaction to feel relevant, connected and personal. But many banks are still working with fragmented data and siloed systems, making it harder to deliver the experiences that build trust. The Kyndryl Agentic AI Framework helps bring those pieces together. By connecting AI agents across systems, banks can turn disconnected data into insights that relationship managers can actually use in the moment. The result: more meaningful conversations, with transparency, governance and human oversight built in. See how Agentic AI is helping banks transform customer experience: http://ms.spr.ly/6041vNBbX #TheHeartOfProgress

Banks are deploying agents into an operating model that was never designed to govern them, and this is becoming one of the most under examined problems in banking AI. Backbase CEO Jouk Pleiter wrote an article for Financial IT about this structural mismatch, and why it's resulting in friction with compliance and regulation, and ultimately causing AI to be stuck in pilot mode. Banks have been solving the same kind of problem for decades; they just haven't applied the same logic to agents yet. Jouk's piece lays out the framework, which he calls Know Your Agent. He also talks about the role of a governance layer as the foundation for banks that scale agentic capability. To learn more, read the full piece [Link in the comments].