DBS says AI push is paying off as it shifts from efficiency tool to growth engine

The time savings from the technology can be redeployed towards business expansion, says chief Tan Su Shan

Renald Yeo
Published Mon, Feb 9, 2026 · 03:39 PM
    • AT DBS, AI has compressed work that previously took months or even years into a matter of weeks.
    • AT DBS, AI has compressed work that previously took months or even years into a matter of weeks. PHOTO: TAY CHU YI, BT

    [SINGAPORE] Years of investment in artificial intelligence (AI) and machine learning helped to drive record deposit inflows, wealth growth and fee income for DBS in 2025, said chief executive officer Tan Su Shan.

    She said the bank’s use of AI-powered tools such as contextual nudges and automated customer engagement played a key role in attracting new-to-bank customers and driving volume growth.

    “This I can attribute to the hard work we’ve done over the years in using AI, using machine learning and contextual nudges to gather new-to-bank customers, to be customer-centric, to have our nudges automated and to use AI smartly,” she said at a results briefing on Monday (Feb 9).

    As AI becomes more deeply embedded into daily workflows, it will become harder to isolate the precise economic value it generates, but what “excites” DBS is its potential to free up employees for growth-oriented work, she added.

    “We might still try to capture the economic value (of AI) based on what we’ve been doing in the past, which is A/B testing, but I suspect there will be a lot more in terms of capacity building.”

    A/B testing is the comparison of outcomes between two groups – one that uses an AI-driven solution and another that does not – to measure the incremental impact of the technology.

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    Tan was responding to media queries at DBS’ fourth-quarter earnings call on the economic value that AI tools have delivered to South-east Asia’s largest bank. She noted that AI has compressed work that previously took months or even years into a matter of weeks, pointing to the area of technical debt – a term that refers to the maintenance or fixing of outdated systems and code – as an example.

    The time savings can then be redeployed towards business expansion, she said. “What excites us is the ability to use what we can harness from capacity (building) to then redeploy for growth.”

    More than 60 per cent of the lender’s staff are now “very actively” using its in-house generative AI tool, DBS GPT, Tan added.

    When the tool was rolled out last July, it was “not so good”, she acknowledged. But it has since got “better and better and better”, and is now being used across “myriad” applications.

    These include translation tasks, internal queries on the bank’s policies and procedures, as well as guidance on how employees should handle questions from both internal and external parties.

    In January, DBS told The Business Times that it recorded a one-third increase in economic value from its AI initiatives to S$1 billion in 2025, compared with S$750 million in 2024.

    The S$1 billion figure was derived by comparing outcomes between customers who were offered AI-driven solutions and those in a control group.

    Staff impact

    On workforce implications, DBS said in early 2025 that it would reduce about 4,000 contract and temporary roles over the next few years through natural attrition.

    For the lender, the interaction between humans and machines centres on training staff to use tools such as agentic AI safely, while leveraging the technology to expand capacity and shift employees into higher-order roles, said Tan.

    “We want people to feel safe, to learn and to use this new capacity – this new superpower – that you now have to do a higher-order role,” she added.

    For Q4 ended Dec 31, staff costs came in at S$1.38 billion, down from S$1.54 billion in the previous quarter.

    Part of the decline reflected lower bonuses accrued in Q4 compared with the stronger performance in Q3, chief financial officer Chng Sok Hui said at the same earnings call.

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