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    Home » Sections » Banking » How agentic AI is reshaping banking in South Africa

    How agentic AI is reshaping banking in South Africa

    Agentic AI is already reshaping South African banking, writes Absa Business Banking CIO Lindelani Ramukumba.
    By Lindelani Ramukumba5 April 2026
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    How AI agents are reshaping banking in South Africa - Lindelani Ramukumba, Absa
    The author, Absa’s Lindelani Ramukumba

    Rewind just a few years and large language models and generative AI were barely on the public radar. Yet the technology has already evolved into its next iteration: agentic AI, a new breed of systems that are semi- or fully autonomous and able to reason and act on their own. And adoption has skyrocketed, particularly over the past year.

    According to a recent PwC survey, 79% of senior executives globally say AI agents are already being adopted in their organisations in one form or another, which is a striking level of uptake for such a nascent technology.

    One might assume that agentic AI has not yet reached South African shores, but it is already being implemented at scale, particularly in the financial services sector, where early deployments are delivering measurable gains in efficiency and productivity.

    Many banks have already begun investing in these technologies, particularly in business-critical operations

    For customers, it means faster service, more personalised interactions, quicker resolution of everyday banking needs and less time spent navigating routine processes.

    Take the customer acquisition stage as an example. Onboarding a small or medium-sized business has traditionally taken several hours spread across multiple days, with relationship managers collecting documents, verifying business registration, conducting “know your customer” (KYC) checks, assessing credit risk and configuring products across different systems. That level of manual work drives up the cost of acquiring each customer, which in turn limits how widely banks can serve the market, often forcing them to prioritise larger, higher-value clients over smaller businesses.

    Enterprise agentic AI

    Now imagine compressing that process into 20 minutes through automation, using tools such as biometric identity verification, automated CIPC lookups, real-time credit bureau integration and instant KYC orchestration. Suddenly the economics change and banks can serve segments that were previously not viable at scale, expanding their addressable market and opening the door to far broader financial inclusion. For the SME owner, it means being able to open a business banking account in minutes rather than days, with far less time spent navigating paperwork and administrative processes.

    Many banks across South Africa have already begun investing in these technologies, particularly in business-critical operations, and their application across other areas of the banking value chain is expected to expand considerably through the rest of 2026.

    Read: The real reason Absa wrote off R2.4-billion in software

    In September last year, Absa, for example, partnered with cloud-based CRM platform Salesforce to bring its enterprise agentic AI solution, Agentforce, into Africa for the first time, a development that carries important implications for the banking industry.

    As part of this, three autonomous AI agents are being tested within the bank:

    • The first is a copilot designed to support relationship managers. Historically, much of their time was spent preparing for meetings rather than engaging customers, with as much as 75% of the workday going into reviewing customer data across multiple systems, analysing recent transactions, identifying potential opportunities and compiling engagement notes. Only about 25% of their time was spent actually interacting with customers. The AI agent now automates much of that preparation by generating pre-meeting briefs, pulling together customer information from multiple systems, highlighting relevant transaction patterns, and capturing notes after engagements. This has effectively flipped that ratio, with administrative time reduced by between 75% and 90%, allowing relationship managers to spend far more of their time focused on customers.
    • Another agent focuses on customer enquiries. It operates as a multilingual support assistant capable of responding to common banking questions across 11 languages, including isiZulu, Sesotho, and isiXhosa. Early results show that around 40% of customer service queries are now resolved without human intervention, meaning four in 10 interactions can be handled instantly while maintaining response quality. In many cases, responses that once took customers up to 30 minutes to receive are now delivered immediately, with success rates of close to 99%.
    • The third agent focuses on monitoring and resolving technical issues across systems. Operating around the clock, it can detect and address many problems automatically, reducing the time it takes to restore services and allowing teams to focus less on operational troubleshooting and more on supporting customers. Since its introduction, the agent has already handled more than 6 400 internal support queries with a success rate of about 96%, meaning the vast majority of issues are resolved without needing to escalate to technical support teams.

    Quicker access

    These examples offer a glimpse of how agentic AI is beginning to change the way banks operate and, more importantly, what customers can expect in the near future.

    It is likely that more of this technology will be used to expand digital onboarding, allowing customers to open accounts or access services far more quickly and with less paperwork.

    Banks may also begin using AI to assess creditworthiness in new ways, analysing transaction patterns and cash flow behaviour rather than relying only on traditional balance sheet information. For small businesses in particular, this could mean quicker access to financing and more proactive offers when their financial activity shows they are able to support additional credit.

    At the same time, many routine banking interactions are likely to move into digital self-service channels, allowing customers to resolve simple requests instantly while still having access to human support when it is genuinely needed.

    Agentic AI is still in its early stages, but its direction of travel is already becoming clear.

    As these systems mature and banks become more comfortable deploying them in everyday operations, customers are likely to experience banking that is faster, more responsive and increasingly personalised. Much of this change may happen in the background, but over time it will transform how people interact with their banks.

    • The author, Lindelani Ramukumba, is CIO and interim chief digital officer of Absa Business Banking

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    Absa Lindelani Ramukumba PwC Salesforce
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