IBM beat all its large-cap tech peers in 2022 as investors shunned growth for safety
IBM CEO Arvind Krishna speaks at an IBM facility in Poughkeepsie, New York, on Oct. 6, 2022. IBM announced $20 billion in investments during President Biden’s visit that will go toward research and development and the manufacturing of semiconductors, mainframe technology, artificial intelligence and quantum computing in the Hudson Valley.
Dana Ullman | Bloomberg | Getty Images
IBM isn’t often described as a hot company. But in a year that saw investors abandon all major tech stocks, Big Blue was in the green.
The Nasdaq is closing out its worst year since 2008. High gas prices, soaring inflation and the Federal Reserve’s steady pace of rate increases have punished growth stocks and favored more mature, less volatile names that are viewed as more recession-resistant.
Tech names that thrived during the Covid days suffered the most as the economy reopened and consumers returned to many of their old habits.
Among U.S. tech companies valued at $50 billion or more, IBM was one of only two to generate positive returns in 2022. As of Friday’s close, the stock was up 6% for the year. The other gainer is VMware, which is up 5% because it agreed in May to be acquired by Broadcom for $61 billion.
While Meta, Amazon and Tesla have been pummeled, investors turned to 111-year-old IBM, betting on its stable earnings, alongside energy stocks such as Exxon Mobil, health-care names including Merck and industrials Northrop Grumman and Lockheed Martin.
IBM beats Big Tech in 2022
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IBM is “trading well above its historical range,” Bernstein Research analysts wrote in a Dec. 20 note to clients. The firm has a hold rating on the stock.
Nobody will mistake IBM for a growth stock. Expansion is consistently in the single digits, and last year the company spun off Kyndryl, its managed infrastructure services business, into a separate publicly traded entity. That cut head count by about 90,000.
But IBM generated $752 million in free cash flow in the latest quarter, up 25% from a year earlier, and paid out $1.5 billion in dividends. Third-quarter earnings and revenue both topped estimates, and the company raised its forecast for the full year.
Crawford Investment Counsel in Atlanta, which focuses on income and dividends, looked at IBM in 2016 and concluded that it would be too early for a major investment, said Aaron Foresman, an equity analyst at the firm.
‘Much closer to their vision’
Crawford’s thesis changed in 2019, after IBM bought faster-growing Red Hat for $34 billion. The firm, which today has $6.7 billion under management, boosted its IBM stake from $2 million to $30 million and kept buying until its holdings reached $109 million.
IBM took a hybrid approach to the cloud under CEO Arvind Krishna, who succeeded Ginni Rometty at the helm in 2020. After struggling to gain scale as a cloud infrastructure provider, the company bet that enterprises would use on-premises data center infrastructure as well as the public cloud, rather than relying entirely on one approach or the other.
“Three years later, it’s much closer to their vision than everything on public cloud,” Foresman said. His firm sold 3% of its shares in the second and third quarter of this year.
Consulting remains a huge part of IBM’s business, accounting for one-third of revenue. In that realm, IBM partners with the big cloud providers, rather than strictly competing with them. The company has a backlog of business with Microsoft worth more than $1 billion, and an even bigger one with Amazon, Krishna said in a conversation with RBC CEO Dave McKay in November.
IBM also made technological advances in 2022, introducing the z16 mainframe computer. When a new mainframe hits, many clients upgrade. That leads to greater hardware revenue and highly profitable transaction processing software to run on the machines. IBM’s prior mainframe boom cycle started in September 2019.
While IBM stayed away from any splashy high-priced acquisitions this year, it announced some smaller deals to enhance certain capabilities. Earlier this month, IBM agreed to buy Octo, a consulting company based in Virginia that targets government agencies. Terms weren’t disclosed. It also absorbed consulting companies Dialexa and Sentaca this year.
Foresman described the purchases as an appropriate use of capital and “so small that they’re not necessarily disclosing transaction multiples.”
Still, Krishna recognizes that the economic backdrop isn’t ideal. He said in October that higher prices have led to “some caution creeping into the conversations” in Europe, where the company has to prepare for a downturn. In the Americas, where IBM gets about 53% of revenue, the business climate is “very robust,” he said.
The Bernstein analysts said the stock’s direction from here might simply ride on the state of the economy, rather than any major catalyst inside the company.
“Given its defensive characteristics and historical performance, we believe that IBM is likely to fare well if we continue to have pressured markets, and likely to lag major indices if we enter a recovery period,” they wrote.
IBM’s model through 2024 calls for mid-single-digit revenue growth, translating into free cash flow growth in the high single digits.
That’s good enough for investors who look for safety in their equity bets.
“Combined with mid-single-digit revenue growth, a couple points better than that on EPS and a 5% dividend yield is — you know, that’s not a home run, but it’s well within our expectations for what we’re trying to accomplish,” Foresman said.
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Nvidia CEO Jensen Huang introduces new products as he delivers the keynote address at the GTC AI Conference in San Jose, California, on March 18, 2025.
Josh Edelson | AFP | Getty Images
At the end of Nvidia CEO Jensen Huang’s unscripted two-hour keynote on Tuesday, his message was clear: Get the fastest chips that the company makes.
Speaking at Nvidia’s GTC conference, Huang said that questions clients have about the cost and return on investment the company’s graphics processors, or GPUs, will go away with faster chips that can be digitally sliced and used to serve artificial intelligence to millions of people at the same time.
“Over the next 10 years, because we could see improving performance so dramatically, speed is the best cost-reduction system,” Huang said in a meeting with journalists shortly after his GTC keynote.
The company dedicated 10 minutes during Huang’s speech to explain the economics of faster chips for cloud providers, complete with Huang doing envelope math out loud on each chip’s cost-per-token, a measure of how much it costs to create one unit of AI output.
Huang told reporters that he presented the math because that’s what’s on the mind of hyperscale cloud and AI companies.
The company’s Blackwell Ultra systems, coming out this year, could provide data centers 50 times more revenue than its Hopper systems because it’s so much faster at serving AI to multiple users, Nvidia says.
Investors worry about whether the four major cloud providers — Microsoft, Google, Amazon and Oracle — could slow down their torrid pace of capital expenditures centered around pricey AI chips. Nvidia doesn’t reveal prices for its AI chips, but analysts say Blackwell can cost $40,000 per GPU.
Already, the four largest cloud providers have bought 3.6 million Blackwell GPUs, under Nvidia’s new convention that counts each Blackwell as 2 GPUs. That’s up from 1.3 million Hopper GPUs, Blackwell’s predecessor, Nvidia said Tuesday.
The company decided to announce its roadmap for 2027’s Rubin Next and 2028’s Feynman AI chips, Huang said, because cloud customers are already planning expensive data centers and want to know the broad strokes of Nvidia’s plans.
“We know right now, as we speak, in a couple of years, several hundred billion dollars of AI infrastructure” will be built, Huang said. “You’ve got the budget approved. You got the power approved. You got the land.”
Huang dismissed the notion that custom chips from cloud providers could challenge Nvidia’s GPUs, arguing they’re not flexible enough for fast-moving AI algorithms. He also expressed doubt that many of the recently announced custom AI chips, known within the industry as ASICs, would make it to market.
“A lot of ASICs get canceled,” Huang said. “The ASIC still has to be better than the best.”
Huang said his is focus on making sure those big projects use the latest and greatest Nvidia systems.
“So the question is, what do you want for several $100 billion?” Huang said.
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