NEW YORK — Big Tech’s biggest names have watched hundreds of billions of dollars evaporate from their market values in early 2026 as investors reconsider how quickly the AI boom can translate into profits, while Taiwan Semiconductor Manufacturing Co., Samsung Electronics and Walmart have gained ground instead. The shift reflects a growing demand for near-term earnings visibility as major tech companies pour money into data centers, chips and energy-hungry infrastructure, Feb. 17, 2026.
Market-cap data compiled by Reuters shows the pullback has been sharpest in some of the most widely held megacap tech names — a reminder that the AI trade is no longer just about growth stories, but about cash flows, margins and timelines.
Big Tech’s AI bill comes due
Through the close Friday, Feb. 13, investors had marked down several leaders even as they doubled down on AI infrastructure:
Microsoft: down about 17% year-to-date amid concerns about its AI business and intensifying competition from Google’s latest Gemini model and Anthropic’s Claude Cowork AI agent, wiping roughly $613 billion off its market value to about $2.98 trillion, according to Reuters data.
Amazon: down about 13.85%, erasing about $343 billion and leaving it valued around $2.13 trillion. Amazon has said it expects capital spending to jump more than 50% this year, Reuters reported.
Apple, Nvidia and Alphabet: market values down $256.44 billion, $89.67 billion and $87.96 billion, respectively, since the start of 2026, according to Reuters.
Part of the unease is that Big Tech has asked investors to underwrite an expensive “build now, monetize later” phase — and the patience trade is thinning. “We see this as a ‘prove it’ year for AI. We need to start seeing some return on investments,” said Jack Herr, a primary investment analyst at GuideStone Funds, in a Reuters report on a recent tech-led market drop.
That “prove it” framing is showing up in how investors model today’s biggest AI spenders: higher depreciation from data-center spending, rising power and networking costs, and more scrutiny of whether AI features can lift revenue enough to offset those bills.
Why TSMC, Samsung Electronics and Walmart are moving the opposite direction
The valuation reset does not mean the AI boom is over. Instead, the market is drawing a sharper line between Big Tech’s uncertain payback period and companies that can capture AI demand more directly — by selling the chips, memory, foundry capacity and logistics that AI systems need right now.
In Reuters’ market-cap snapshot, TSMC, Samsung Electronics and Walmart together added more than $700 billion in value in 2026. TSMC, Samsung and Walmart added $293.89 billion, $272.88 billion and $179.17 billion in market value, respectively, lifting their valuations to $1.58 trillion, $817 billion and $1.07 trillion.
TSMC, the world’s main producer of advanced AI chips, has framed demand as an “AI mega trend.” In January, the company posted a forecast-smashing fourth-quarter profit jump and projected 2026 revenue growth of close to 30%, while forecasting capital spending of $52 billion to $56 billion, according to a Reuters report on TSMC’s outlook. Investors have treated that visibility as a hedge against the slower, more uncertain path to AI profits for platform companies.
Samsung Electronics has also benefited from the market’s focus on the supply chain. Industry sources told Yonhap News Agency that Samsung will begin mass production of HBM4, a sixth-generation high-bandwidth memory used in AI systems, later this month, with shipments expected to start shortly after the Lunar New Year holiday.
Walmart has become an unlikely symbol of the rotation away from pure platform bets. The retailer hit a $1 trillion market valuation Feb. 3 and joined a club dominated by tech giants after a yearlong rally fueled by faster delivery, advertising growth and aggressive investment in AI-driven supply-chain automation, according to Reuters reporting on Walmart’s milestone. Its story also fits the market’s preference for near-term execution: using AI to cut costs and improve operations rather than spending tens of billions to build new models from scratch.
What Big Tech needs to prove next
For Big Tech, the valuation reset is less about whether AI matters and more about whether AI can be monetized faster than the industry can spend. Investors are now pushing for clearer answers to a few questions:
Revenue clarity: Which AI products are driving incremental sales versus repackaging existing services?
Margin math: How quickly can Big Tech shift from heavy capital expenditures to operating leverage as utilization rises?
Competitive moat: Will the biggest platforms keep pricing power as rivals release new models and features?
Big Tech is still profitable at scale, and many of its businesses — cloud, ads, devices and enterprise software — throw off enormous cash. But the market is increasingly reluctant to treat every dollar of AI spending as automatically value-creating. Until Big Tech can show durable AI revenue streams and disciplined spending, investors may keep trimming valuation multiples.
How we got here: Big Tech’s boom, then the reset
The current selloff follows a period when Big Tech’s dominance looked almost unshakable. In late 2023, investors debated whether the “Magnificent Seven” could keep powering U.S. stocks after a year in which AI excitement helped propel megacaps and narrowed market breadth, as detailed in a Reuters look back at the Magnificent Seven trade.
By late 2024, however, Big Tech’s AI buildout was already colliding with margin questions. Microsoft, Meta, Alphabet and Amazon were stepping up spending on AI data centers, and investors openly worried about how long it would take to see returns, according to a Reuters report from the 2024 earnings season.
In 2025, strategists began arguing the rally needed to broaden beyond megacaps and encouraged diversification — a theme that now looks prescient as leadership falters and investors hunt for different kinds of AI exposure, including suppliers and “real economy” adopters, in a Reuters analysis on market participation.
For now, the message is that Big Tech is no longer being priced solely on promise. The companies that can pair AI ambition with measurable, near-term returns — or that sell the tools powering the boom — are taking the lead.
