Standard Bank Prioritizes AI Governance and Data in Organizational Shift

Margaret Nienaber, COO of Standard Bank Group. Standard Bank Group is shifting its artificial intelligence (AI) strategy from experimenting with individual tools and use cases, to embedding AI as a core organisational capability. According to the bank, as access to leading AI models becomes increasingly widespread, competitive advantage will depend less on access to the latest AI models and more on how organisations combine those models with trusted data , governance, skilled employees and knowledge of their customers and markets. More than 39 000 Standard Bank employees, representing 72% of the group's workforce, are now active users of generative AI, according to the bank. Around one-third of its technology employees are also using AI-enabled coding tools, with early use cases delivering productivity improvements of about 20%. Margaret Nienaber, COO of Standard Bank Group, says the bank is moving from simply providing employees with AI tools, towards fundamentally changing how the organisation operates. “We are transitioning from simply using AI tools to becoming an AI-enabled organisation. That is a fundamentally bigger ambition. The winners in AI will not necessarily be the organisations with access to the newest technology, because increasingly many organisations will have access to similar models and tools. “The real differentiator will be how effectively you combine that technology with trusted data, strong governance, the right skills and deep knowledge of your clients and markets. AI is becoming a core long-term competitive capability rather than simply a technology capability. Our focus is on embedding it into how we serve clients, how we support our people and how we run the group, creating a foundation for long-term growth,” notes Nienaber. SA’s major banks First National Bank, Absa, Capitec and Nedbank previously told ITWeb they are also entering a new phase in AI in 2026, shifting from pilot projects and isolated experiments, to large-scale deployment across core operations. After years of testing machine learning and data-driven tools, the banks are now accelerating investment and integration of AI into fraud detection, customer service, risk management and digital platforms, signalling the technology is becoming central to competitiveness in the financial sector. Research by McKinsey shows AI can help banks reduce costs, improve productivity, strengthen risk management and deliver more personalised customer experiences. The consultancy estimates generative AI could add $200 billion to $340 billion in value annually to the global banking sector, largely through increased productivity. Standard Bank uses an iceberg analogy to describe its AI strategy. The visible portion represents the AI tools employees use, client-facing experiences and individual use cases. Beneath the surface are the less visible foundations needed to scale those initiatives, including trusted data, technology infrastructure, AI models, security controls, risk management, responsible governance, skills and organisational culture. The bank argues that without these foundations, AI risks remaining a collection of disconnected experiments rather than becoming an enterprise-wide capability. Its enterprise AI platform, built on Amazon Bedrock, follows a multi-model approach. This allows the bank to evaluate and deploy different open and closed models, while maintaining common security, governance and operational controls. Nienaber points out that Standard Bank has identified four “lighthouse” areas for its initial AI focus: relationship management, servicing, payments and lending. “In relationship management, AI is being used to reduce the time bankers spend searching for information, allowing them to devote more time to clients. Servicing is focused on simplifying interactions across digital channels, contact centres and branches, while allowing employees to concentrate on more complex customer requirements. In payments, AI is being applied to op