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IBM (IBM) has gained about 2.35% year to date, at the time of writing, Wednesday afternoon, Jan. 14. Meanwhile, SPY is up 1.74% in the same period. Not a bad start to the year for IBM.
The company has announced a preliminary release date for its Q4 2025 earnings report of January 28. After beating the S&P 500 by gaining about 39% in the past year compared to SPY’s 19% gain, investors must be wondering if the company will do it again, and what we can expect from IBM in 2026.
Bank of America analyst Wamsi Mohan and his team updated their opinions on IBM stock ahead of the company’s earnings.
Analysts said they don’t expect IBM stock to have as strong growth in fiscal 2026 as it did in 2025, as it will face several headwinds. They estimate a softer Q4 pre-tax income (PTI) margin due to workforce rebalancing initiatives, which will lead to fiscal year 2025 PTI margin expansion below the guidance of more than 100 basis points.
The team believes IBM will incur a workforce rebalancing expense of $400 million in Q4, resulting in 70 basis points of fiscal year 2025 year-over-year PTI margin expansion.
Mohan stated that for free cash flow (FCF), he estimates $14.0 billion for fiscal year 2025 and expects guidance of approximately $15 billion in fiscal year 2026, maintaining a 130% net income/FCF ratio.
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Analysts changed their estimates for revenue and non-GAAP EPS for fiscal year 2025, increasing revenue from $66.9 billion to $67.1 billion and lowering the non-GAAP EPS estimate from $11.38 to $11.32.
In a research note shared with me, Mohan reiterated a buy rating for IBM stock, and raised the target price from $315 to $335, based on 23 multiple his estimate for the enterprise value to FCF ratio for calendar year 2027.
He wrote: “Our target multiple for IBM exceeds the high end of the historical range 8-22x, with median 13x. We believe a multiple at the high end/exceeding the historical range is justified given the company’s improving growth and FCF trajectory with Red Hat.”
The last time Mohan raised the price for IBM stock was after its Q3 earnings report. For a reminder, read my article “Bank of America revamps IBM stock price after earnings.”
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Failure to execute on the company’s growth roadmap
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Inability to realize expected cost savings from restructuring
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Technology/competitor risk in hardware, software, and services
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Unforeseen currency impacts on revenue and profits
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Acquisition integration, given IBM’s acquisitive nature
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Increased concern of economic uncertainty and tightening corporate IT budgets
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Faster re-acceleration of topline
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Faster improvement in margins
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Better-than-expected accretion from M&A
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Delivery of upside to FCF
Datavault AI (DVLT), an instant data monetization and enterprise digital twins company, plans to deliver enterprise-grade AI performance at the edge in New York and Philadelphia through an expanded collaboration with IBM, using the SanQtum AI platform.
Datavault AI’s SanQtum AI fleet is operated by the company, which goes by the confusing name of “Available Infrastructure.” The fleet consists of synchronized micro edge data centers running IBM’s watsonx portfolio of AI products on a zero-trust network.
“By unifying speed, resilience, and trusted protection in a single platform, SanQtum AI provides a powerful new foundation for AI and computing safety, reliability, and performance,” stated Daniel Gregory, CEO of Available Infrastructure.
“Datavault AI’s deployment of this technology, in collaboration with IBM, will help bolster enterprise-grade AI in the Northeast in ways that we believe will set the bar higher than ever for others to follow.”
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Removing dependence on centralized cloud pipelines
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Eliminating lag between data creation and monetization
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Preventing tampering by keeping data inside a zero-trust local network
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Allowing enterprises to treat their data as instant, tradable digital
property
Related: Analysts drop verdicts on AMD, Intel, and ARM
This story was originally published by TheStreet on Jan 15, 2026, where it first appeared in the Investing section. Add TheStreet as a Preferred Source by clicking here.
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