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.
Four AI priorities
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 operational efficiency and fraud management, while the bank is also preparing for the emergence of AI agents in commerce,” she explains.
Lending is another priority, with AI being used to streamline processes spanning credit assessment, contracting and disbursement.
Nienaber states the objective is not simply to eliminate human work.
“AI can give our people time back, but what we do with that time is what really matters,” says Nienaber.
“We want to reinvest it in the things humans do particularly well: judgement, creativity, relationships, empathy and solving complex problems for clients. This is why we see AI as augmenting our people rather than simply automating work. Technology on its own is not the competitive advantage; the advantage comes from what our people are able to do with it.”
Cloud foundation
Standard Bank's AI expansion is being supported by its broader technology modernisation programme.
By the end of the first half of 2026, 78% of migratable compute had moved to the cloud, according to the bank. This provides the scalable infrastructure needed to deploy AI applications across the organisation, while maintaining consistent controls.
The group has also been building AI skills internally. Its 2025 sustainability disclosures reported that more than 9 000 employees had completed its Foundational AI Pathway, while more than 12 300 had used its integrated prompt guide and more than 1 000 leaders had participated in its Decision-Maker Pathway.
“The scale of current AI usage therefore represents a progression from earlier skills-building and experimentation towards broader enterprise adoption.”
For Standard Bank, the next stage of AI adoption is less about finding another AI use case and more about integrating AI into the operating model, Nienaber continues.
“Standard Bank's strategy places data, infrastructure, governance and people beneath the visible layer of AI applications, with the aim of turning those foundations into a repeatable capability that can be deployed across different parts of the group.”
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