Q3 Tech Earnings Preview: AI Trade Under Pressure

The tech sector heads into the second half of this earnings season on shaky ground. After roughly four years of strong earnings results amid the AI boom, the sector has shown some cracks in its armor in recent weeks, leading investors to rotate into more defensive and cyclical plays.

While demand for chips, chip equipment, and other AI infrastructure inputs remains robust, there are signs hyperscalers' spending growth is beginning to level off as their free cash flows (FCF) come under pressure. Meanwhile, the software industry's rebound has stalled, and some high-flying memory and storage stocks have stumbled.

Overall, tech earnings have been strong so far. The information technology sector reported a year-over-year blended earnings growth rate of 67.5% through October 30, according to data from FactSet. Still, investors are increasingly concerned about the tech sector's ability to turn its massive AI investments into sustainable profits. It's an environment that raises the stakes for upcoming earnings reports from tech leaders such as Nvidia (NVDA), Broadcom (AVGO), Oracle (ORCL), and Micron Technology (MU).

"Even though mega-cap tech and AI-related tech companies have mostly put up solid growth metrics, negative sentiment around debt, negative free cash flow, and future funding needs appears to be dominating investors' psychology, and the post-earnings reactions reflect that," said Nathan Peterson, director of derivatives research and strategy at the Schwab Center for Financial Research.

Record quarterly results just aren't enough anymore. That's been the main theme of this tech earnings season so far. Multiple Magnificent Seven giants, once red-hot memory makers, and leading software names have reported record revenues or profits—while surpassing lofty Wall Street forecasts—only to see their stocks decline.

With the AI boom maturing, tech investors seem more focused on the road ahead. They want to see strong guidance, sustainable demand, and clear evidence of AI monetization, not just solid quarterly results.

Intel (INTC) is one of the best examples of this trend. The chipmaker topped analysts' forecasts this quarter, as AI and data center revenue jumped 78% year over year to $7.3 billion. But that didn't stop its stock from nosediving more than 28% the day after it reported earnings. Investors fretted over weaker-than-expected guidance, which management blamed on softness in the PC market.

It was a similar story for Samsung (SSNLF). The company's surging chip and memory businesses drove another record quarter, but its shares slid after its guidance merely matched expectations.

For some companies, even strong guidance hasn't been enough to attract investors. Seagate Technology (STX), for example, plunged after reporting earnings, despite raising its guidance and topping analysts' forecasts. Investors appeared concerned that Seagate's total data-storage capacity shipped barely increased from the previous quarter, potentially signaling weaker underlying demand.

Hyperscalers have also struggled this earnings season amid concerns about declining FCFs, potential disruptions to their legacy businesses, and a deceleration in AI spending plans.

Alphabet (GOOGL) dropped sharply after reporting weaker-than-expected third-quarter results. Investors seemed particularly worried about AI disrupting its core search business. Even a 103% year-over-year jump in Google Cloud's revenue wasn't enough to reassure investors. The search giant also held its full-year capital expenditures (capex) guidance steady at $195 billion to $205 billion after routinely lifting its spending plans in recent quarters.

Amazon (AMZN) also sank after its earnings and revenues fell short of expectations. The company reported negative FCF of $42.4 billion on a trailing 12-month basis and left its full-year capex outlook unchanged at $220 billion.

Microsoft (MSFT) had a better showing, beating expectations as its cloud revenue surged. However, the company reduced its capex forecast for full year 2026 to $170 billion from $175 billion. Meta Platforms (META) also beat analysts' forecasts, but its stock retreated amid concerns about negative FCF and the longer-term return on investment (ROI) from its AI spending.

Not all tech stocks struggled, however. South Korean memory giant SK Hynix (SKHY) reported its sixth straight quarter of record revenues and profits, leading its shares to surge after earnings.

Taiwan Semiconductor Manufacturing Company (TSM) also posted a record profit for the sixth straight quarter. The world's largest contract chipmaker topped Wall Street's earnings estimates and noted that demand for its chips remains well above its supply capacity.

Although many leading tech firms have already reported this earnings season, there's still a packed calendar ahead. Here's what's on the menu.

Chip and chip-equipment makers are facing a challenging environment in the second half of this earnings season. For years now, hyperscalers' record AI infrastructure spending has driven demand for chips, data centers, and other AI-related products, but the days of consistent capex guidance increases appear to be coming to an end. Investors are also becoming more discerning about AI spending.

Last quarter, some tech giants were punished for raising their capex guidance amid FCF and AI ROI concerns. This quarter, as most hyperscalers kept their spending outlooks unchanged or trimmed them slightly, investors appear concerned that moderating spending growth could signal a slowdown in the AI boom.

Markets seemingly want a Goldilocks "not too hot, not too cold" AI buildout. But a slowdown in AI spending growth could eventually weigh on the semiconductor industry, even if this quarter's results are strong.

"Chip stocks are at the heart of the infrastructure buildout, and therefore any concerns around the ability to fully fund that buildout, or any potential changes to the pace of that buildout, have caused some investors to take a step back and participate elsewhere within tech, if at all," Peterson said.

At the same time, the AI boom is evolving, creating both challenges and opportunities. The rise of agentic AI is fueling compute demand, particularly for CPUs, which could provide a tailwind for chipmakers. But on the other side of the ledger, many Magnificent Seven companies have made strides with custom AI chips, which could challenge the dominance of general-purpose GPU makers such as Nvidia and Advanced Micro Devices (AMD).

Investors may also want to track other sources of chip demand this quarter. There have been signs that chip demand is recovering across a range of end markets beyond AI, including gaming, automotive, industrial, home appliances, and personal computers.

For example, chipmaker Texas Instruments (TXN) cited a continuing recovery in industrial chip demand as one of the reasons it offered upbeat guidance this quarter. Chip design software specialist Cadence Design Systems (CDNS) highlighted demand from EV manufacturers and major power and telecommunications companies in its earnings report. And NXP Semiconductors (NXPI) touted demand from the automotive industry and physical AI applications like robotics.

Key trends and indicators to watch:

• Revenue growth and order backlogs. Track data center revenue growth at Nvidia, AI semiconductor revenue growth at Broadcom, and chip equipment sales at companies such as Applied Materials (AMAT). Order backlogs and bookings may offer clues about future demand and whether AI infrastructure spending is set to slow.
• Supply chain updates. Monitor management commentary on chip manufacturing capacity and other supply constraints, such as high memory pricing, skilled labor shortages, and component shortages. Pay particular attention to whether these issues are slowing sales growth or increasing costs.
• Revenue mix. Compare sales growth across business segments and end markets at chip and chip-equipment makers. Improving revenue from industrial, automotive, and consumer markets could help buoy these companies if AI spending slows.
• Guidance and earnings calls. Watch forward guidance and listen to management commentary on earnings calls to see if there are signs of weakening demand as hyperscalers' spending growth moderates. Also listen for commentary about CPU and custom AI chip demand to see how the AI boom is evolving.
• Memory pricing. Track average selling prices, margins, and shipment volumes at Micron Technology for signs that the memory boom is beginning to slow. Weakening prices or shipment volumes could put pressure on future earnings.

After plunging in the first quarter due to AI disruption fears, the S&P North American Technology Software Index rebounded to near-record highs in early October as those fears were allayed by strong second-quarter results.

However, this earnings season hasn't been as kind to software stocks so far. For example, ServiceNow (NOW) plunged nearly 27% on October 29 after failing to meet Wall Street's earnings forecast. Weaker-than-expected backlog guidance spooked investors even as the software-as-a-service (SaaS) giant posted 20.5% year-over-year revenue growth and raised its full-year target for AI annual contract value to at least $1.7 billion.

Software investors have been pivoting between viewing AI as a growth opportunity and a business model disruptor for years, and lately there are signs they're leaning back toward the latter. The challenge for software companies is proving that new AI products can generate enough revenue to offset potential pressure on their traditional businesses. AI agents, for example, could reduce the need for software licenses by allowing fewer employees to accomplish the same amount of work. That could threaten the seat-based pricing models software companies have long relied on.

Looking ahead, software stocks—such as Oracle, Adobe (ADBE), and Salesforce (CRM)—will have a lot to prove. It may not be enough to top earnings forecasts; guidance, new pricing model adoption, and AI contract values will be in focus as many investors still fear AI disruption.

Key trends and indicators to watch:

• AI tool usage and revenues. Monitor customer adoption, usage rates, and revenue from AI-powered tools. At Salesforce, for example, track annual recurring revenue from Agentforce, its AI agent platform, to gauge whether AI tool adoption is translating into sales growth.
• Pricing model transition. Watch for developments in software companies' transition from seat-based pricing to consumption-based pricing. Management commentary and margins could offer clues about whether these new pricing models are proving effective.
• Customer retention. Look at attrition rates, subscription renewals, and remaining performance obligations, when disclosed. If software companies are struggling to hold onto customers, it may indicate some clients are switching to in-house tools built using AI or to smaller AI-based alternatives.

Cybersecurity stocks have been a bright spot for the software industry for much of this year, but this earnings season has been a different story so far. Fortinet (FTNT) dropped sharply even after topping analysts' forecasts in its third-quarter earnings report. Slowing product revenue growth and a reduction in service revenue guidance seemingly spooked investors. Fortinet's report sparked a broader sell-off in the industry, even though most major cybersecurity companies have yet to report their results.

Still, cybersecurity companies have been boosted by the threat of AI cyberattacks in recent years, and many businesses fear this is just the beginning. Attacks by AI-enabled adversaries spiked 89% year over year in 2025, according to a report from CrowdStrike (CRWD). And between March 2025 and February 2026, one in four "malicious" data breaches were AI-enabled, according to IBM's Cost of a Data Breach Report.

Cybersecurity companies are now leaning on AI to defend against these attacks, creating a technological arms race between attackers and defenders. This could present a significant growth opportunity for the cybersecurity industry. The question is whether that demand will translate into profits because cybersecurity companies could face higher costs to develop defensive tools capable of fending off increasingly sophisticated AI attacks.

Key trends and indicators to watch:

• The AI-on-AI cyber battle. Listen to management commentary about the growing use of AI in cyberattacks and demand for AI-powered security products. Look for evidence that companies are using the cybersecurity arms race to gain new customers, larger contracts, or additional revenue.
• Retention rates and annual recurring revenue (ARR). Track ARR, net new ARR, and net revenue retention to see whether customers are expanding their cybersecurity investments.
• Free cash flow and margins. Watch profitability metrics such as FCF and operating margins to see if cybersecurity companies can turn growing demand into higher profits, even as they invest in AI-powered defenses.

Tracking tech companies' ability to beat Wall Street's expectations is critical every earnings season. Here's a breakdown of analysts' consensus* earnings per share (EPS) and revenue estimates for some major tech stocks set to report.

*Note: Average analyst earnings and revenue estimates are as of November 4, 2026, courtesy of Schwab.com, and are subject to change.

Tech companies face a high bar heading into the second half of earnings season. Strong quarterly results alone may not be enough to satisfy investors, who are increasingly focused on forward guidance, sustainable AI demand, and profitability. With expectations elevated, upcoming earnings reports could help determine whether the AI trade regains its momentum or faces more pressure.