Tan Su Shan, chief executive officer of DBS Group Holdings Ltd., speaking at the Singapore Fintech Festival in Singapore, on Nov. 12, 2025.
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SINGAPORE – Amid fears of an artificial intelligence bubble, much has been made of recent reports suggesting that AI has yet to generate returns for companies investing billions into adopting the tech.
But that’s not what the chief executive of Southeast Asia’s largest bank is seeing — she says her firm is already reaping the rewards of its AI initiatives, and it’s only just the beginning.
“It’s not hope. It’s now. It’s already happening. And it will get even better,” DBS CEO Tan Su Shan told CNBC on the sidelines of Singapore Fintech Week, when asked about the promise of AI adoption.
DBS has been working to implement artificial intelligence across its bank for over a decade, which helped prepare its internal data analytics for recent waves of generative and agentic AI.
Agentic AI is a type of artificial intelligence that relies on data to proactively make independent decisions, plan and execute tasks autonomously, with minimal human oversight.
Tan expectsAI adoption to bring DBS an overall revenue bump of more than 1 billion Singapore dollars (about $768 million) this year, compared to SG$750 million in 2024. That assessment is based on about 370 AI use cases powered by over 1,500 models throughout its business.
“The proliferation of generative AI has been transformative for us,” Tan said, adding that the company was experiencing a “snowballing effect” of benefits thanks to machine learning.
A major area in which DBS has applied AI is in its financial services to institutional clients, with AI used to collect and leverage data for clients in order to better contextualize and personalize offerings.
According to Tan, this has resulted in “faster and more resilient” teams. The CEO believes that these uses of AI have contributed to a recent uptick in the bank’s deposit growth as compared to competitors’.
The company also recently launched a newly enhanced AI-powered assistant for corporate clients known as “DBS Joy,” which assists clients with unique corporate banking queries around the clock.
ROI concerns
Despite Tan’s strong convictions about AI, recent evidence suggests that many companies are struggling to turn their AI investments into tangible profits.
MIT released a report in July that found 95% of 300 publicly disclosed AI initiatives, encompassing generative AI investments of $30–$40 billion, had failed to achieve real returns.
However, at least in the banking sector, there are signs that the tides are turning.
While DBS doesn’t differentiate spending in generative AI from other in-house investments, other major banks have recently offered this comparison.
JPMorgan Chase CEO Jamie Dimon stated in an interview with Bloomberg TV last month that the bank is already breaking even on its approximately $2 billion of annual investments in AI adoption. That represents “just the tip of the iceberg,” he added.
Those expectations are shared by DBS, which plans to continue to accelerate its AI development to become an AI-powered bank.
The ultimate goal, according to Tan, is for its generative AI to develop into a trusted financial advisor for clients, including retail users who are expected to interact with personalized AI agents through the DBS banking app.
The bank already has over 100 AI algorithms that analyze users’ data to provide them with personalized “nudges,” such as alerts on incoming shortfalls, product recommendations, and other insights.
Continued AI investments
While DBS may already be reaping rewards from its AI adoption, Tan acknowledged that it will require continued investments, not only in capital, but in the time needed to reskill employees.
The company has launched several AI reskilling initiatives across departments this year and has even deployed a generative AI-powered coaching tool to support these efforts.
This will help the company automate mundane work and refocus its staff on building and maintaining human-to-human relationships with customers, rather than reducing headcount, Tan said.
“We’re not freezing hiring, but it does mean reskilling. And that’s a journey. It’s a never-ending journey … a constant evolution.”
Nvidia President and CEO Jensen Huang speaks about NVIDIA Omniverse as he delivers the keynote address during the Nvidia GTC (GPU Technology Conference) at the Walter E. Washington Convention Center on Oct. 28, 2025 in Washington, DC.
Anna Moneymaker | Getty Images
As a handful of the world’s most valuable companies set out to spend $1 trillion over the next five years on data centers for artificial intelligence, one line item is on the minds of executives and investors: depreciation.
In accounting, depreciation is the act of allocating the cost of a hard asset over the course of its expected useful life. It’s an increasingly important concept in the tech industry, as companies predict how long the hundreds of thousands of Nvidia graphics processing units they’re purchasing will remain useful or retain their value.
Infrastructure giants like Google, Oracle and Microsoft have said their servers could be useful for up to six years. But they could also depreciate much sooner. Microsoft said in its latest annual filing that its computer equipment lasts two to six years.
That’s a lot to consider for the investors and lenders financing the giant AI buildouts, because the longer equipment remains valuable, the more years a company can stretch out depreciation and the less it hurts profits.
Read more CNBC reporting on AI
AI GPUs represent a particular challenge because they’re still relatively new to the market. Nvidia’s first AI-focused processors for the data center came out around 2018. The current AI boom started with the launch of ChatGPT in late 2022. Since then Nvidia’s annual data center revenue has jumped from $15 billion to $115 billion in the year that ended in January.
There’s no real track record for how long GPUs last when compared with other types of heavy equipment that businesses have been using for decades, said Haim Zaltzman, vice chair of Latham & Watkins’ emerging companies and growth practice.
“Is it three years, is it five, or is it seven?” said Zaltzman, who works on GPU financings, in an interview. “It’s a huge difference in terms of how successful it is for financing purposes.”
Some of Nvidia’s customers say AI chips will retain value for a long time and that customers will continue to pay for access to older processors because they’ll still be useful for other tasks. CoreWeave, which buys GPUs and rents them out to clients, has used six-year depreciation cycles for its infrastructure since 2023.
CoreWeave CEO Michael Intrator told CNBC this week, following quarterly earnings, that his company is being “data driven” about GPU shelf life.
Intrator said that CoreWeave’s Nvidia A100 chips, which were announced in 2020, are all fully booked. He also added that a batch of Nvidia H100 chips from 2022 became available because a contract expired, and they were immediately booked at 95% of their original price.
“All of the data points that I’m getting are telling me that the infrastructure retains value,” Intrator said.
CoreWeave CEO, Michael Intrator appears on CNBC on July 17, 2024.
CNBC
Still, CoreWeave shares plunged 16% after the earnings report as delays at a third-party data center developer hit full-year guidance. The stock is down 57% from its high reached in June, part of a broader selloff reflecting concerns about overspending in AI. Oracle shares have plummeted 34% from their record high in September.
Among the most vocal skeptics of the AI trade is short seller Michael Burry, who recently disclosed bets against Nvidia and Palantir.
Burry this week suggested that companies including Meta, Oracle, Microsoft, Google and Amazon are overstating the useful life of their AI chips, and understating depreciation. He pegs the actual useful life of server equipment at around two to three years, and said companies are inflating their earnings as a result.
Amazon and Microsoft declined to comment. Meta, Google and Oracle did not respond to requests for comment.
‘You couldn’t give Hoppers away’
There are a number of ways AI chips could depreciate before six years. They could wear out and break, or they could become obsolete as newer GPUs are released. They could still be useful for running certain workloads, but with much worse economics.
Nvidia CEO Jensen Huang has implied as much. When Nvidia announced a new Blackwell chip earlier this year, he joked that the value of its predecessor, the Hopper, would deteriorate.
“When Blackwell starts shipping in volume, you couldn’t give Hoppers away,” Huang said in March at Nvidia’s AI conference.
“There are circumstances where Hopper is fine,” he continued. “Not many.”
Nvidia now releases new AI chips on an annual basis, versus the two-year cadence it had before. Advanced Micro Devices, its closest GPU competitor, followed suit.
Nvidia reports quarterly results next week.
Amazon, in a February filing, said it decreased the useful life for a subset of its servers from six years to five years because it conducted a study that found “an increased pace of technology development, particularly in the area of artificial intelligence and machine learning.”
Meanwhile, other hyperscalers are extending their GPU useful life estimates for newer server equipment.
Microsoft Chairman and Chief Executive Officer Satya Nadella speaks during the Microsoft Build 2025, conference in Seattle, Washington, on May 19, 2025.
Jason Redmond | AFP | Getty Images
Although Microsoft plans to build AI infrastructure aggressively, CEO Satya Nadella said this week that his company is trying to space out its AI chip purchases and not overinvest in a single generation of processors. He added that the biggest competitor for any new Nvidia AI chip is its predecessor.
“One of the biggest learnings we had even with Nvidia is that their pace increased in terms of their migrations,” Nadella said. “That was a big factor. I didn’t want to go get stuck with four or five years of depreciation on one generation.”
Nvidia declined to comment.
Dustin Madsen, vice president of the Society of Depreciation Professionals and the founder of Emrydia Consulting, said depreciation is a financial estimate by management and that developments in a fast-moving industry like technology can change initial predictions.
Depreciation estimates, Madsen said, generally take into account assumptions such as technological obsolescence, maintenance, historical lifespans of similar equipment and internal engineering analysis.
“You’re going to have to convince an auditor that what you’re suggesting what its life will be is actually its life,” Madsen said. “They will look at all of those factors, like your engineering data that suggests that the life of these assets is approximately six years, and they will audit that at a very detailed level.”
In this photo illustration, the StubHub logo and webpage are displayed on a cell phone and computer monitor on April 17, 2024 in Los Angeles, California.
Mario Tama | Getty Images
StubHub‘s stock plummeted 24% on Friday after the company withheld financial guidance for the current quarter, citing a “long-term” focus.
StubHub CEO Eric Baker told investors on Thursday’s conference call that the timing of when tickets go on sale can shift from quarter to quarter, making it hard to predict consumer demand.
Baker reiterated that demand for live events is “phenomenal,” and added that the company plans to offer an outlook for 2026 when it reports fourth-quarter results.
“This year, we are observing some shifts in the timing of these on-sales,” CFO Connie James told investors on the call. “Several large tours that would typically go on sale in the fourth quarter occurred earlier in late September. It remains to be seen how this concert on-sale timing dynamic plays out in November and December.”
Wedbush analysts said in an investor note on Friday that they were “surprised” by StubHub executives’ decision not to offer any guidance.
“The lack of forward guidance will pressure shares, with investor concern building around lack of visibility over the near-term,” the analysts wrote. They have an outperform rating on StubHub stock.
The lack of guidance overshadowed the company’s stronger-than-expected results in its first earnings report as a public company. Third-quarter revenue grew 8% year over year to $468.1 million, topping the average analyst estimate of $452 million, according to LSEG.
Gross merchandise sales, which represent the total dollar value paid by ticket buyers, jumped 11% year over year to $2.43 billion. That surpassed Wall Street’s expected $2.36 billion, according to FactSet.
The ticket vendor posted a net loss of $1.33 billion, or a loss of $4.27 per share, due to one-time stock-based compensation charges related to its initial public offering in September.
Representation of Bitcoin cryptocurrency in this illustration taken Sept. 10, 2025.
Dado Ruvic | Reuters
Bitcoin dipped below $95,000 on Friday, pushing the world’s oldest cryptocurrency further into the red and continuing its four-day decline amid a broader artificial intelligence-linked stock pullback.
The digital asset was last trading at $94,896.03, down 3.5% on the day. Bitcoin was in the red most of this week, although it reclaimed $107,000 at one point on Tuesday before rolling over.
The largest crypto by market capitalization attracts many of the same investors that have poured funds into BigTech stocks, linking the two trades. Several of those stocks are falling this week amid a resurfacing of concerns over Silicon Valley giants’ astronomical spending on AI initiatives.