Is the AI Selloff Overdone?
A little over three years ago, OpenAI launched ChatGPT, and it quickly became the fastest-growing software application ever. Its explosive adoption set off an AI arms race, with the world’s largest companies pouring hundreds of billions of dollars into new infrastructure and development.
Investors took notice. The market value of many early beneficiaries soared as enthusiasm around AI’s potential grew. Still, skeptics have been warning about a possible bubble.
Lately, investors seem concerned about two things at once. They worry AI could disrupt existing business models, and they question whether companies spending billions on AI will actually earn strong returns. Together, those concerns have fueled extreme market volatility.
Will AI Eat Software Companies?
Back in 2011, venture capitalist Marc Andreessen wrote a Wall Street Journal column titled, Why Software Is Eating the World, praising the durability of recurring revenue models. Now some investors are asking whether AI might end up eating software.
Fears about disruption have weighed heavily on software stocks. The IGV Software Index has been sliding for months, and the drop accelerated after Anthropic released new AI tools. The index is now down -27% year to date.
Companies such as Salesforce, ServiceNow, Adobe, Workday, and Intuit have all taken hits. Private credit firms that lent to software companies have also faced selling pressure, as some investors speculate that AI could replace certain enterprise tools.
In a sell first, ask questions later mood, investors have dumped shares across a wide range of industries, including data providers, insurance brokers, wealth managers, cybersecurity firms, and trucking companies.
It is unlikely that AI-generated code will handle complex, highly specialized software tasks anytime soon. Many companies will adapt by building AI into their products, though some will inevitably fall behind.
Big Tech’s Massive AI Bets Face Scrutiny
Several of the world’s largest companies recently reported excellent earnings, yet investors were unimpressed. The focus has shifted toward AI spending and the returns those investments will produce.
Microsoft, Google, Amazon, and Meta Platforms are projected to spend a combined $660 billion this year on AI, about 65% more than they spent in 2025. Shareholders now want clear proof that these enormous outlays will pay off.
These companies remain highly profitable and financially strong. Still, the scale of their spending is quietly making them more capital intensive than investors are used to. Some concerns are emerging about rising debt issuance, especially at firms such as Oracle.
More . . .
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Is AI So Good It Becomes a Problem?
Markets dropped sharply Monday after a viral report from Citrini Research titled, The 2028 Global Intelligence Crisis, was published. The report described a hypothetical scenario in which unemployment climbs above +10% and the stock market falls -38% from its October 2026 peak.
The authors argued that for most of modern history, human intelligence was the scarce resource, but that advantage may be fading as machine intelligence improves rapidly across many tasks.
One of the report’s coauthors said in a Bloomberg TV interview that companies tied to the AI ecosystem, including semiconductor firms, materials suppliers, foundation model developers, and certain tech companies, could be the biggest winners.
Why Dot-com Comparisons Fall Short
Some critics point to circular deal structures among AI firms and compare them to vendor financing during the dot-com era. Others liken NVIDIA’s rise to Cisco’s surge around March 2000, when Cisco briefly became the world’s most valuable company before losing about 80% of its value the following year.
There is a key difference today. The leading players in the race toward artificial general intelligence are profitable, cash-rich giants investing massive sums to stay ahead. For them, the bigger risk is underinvesting and losing ground, not overspending.
Most data center spending is funded through operating cash flow because the companies leading the AI push generate substantial profits from diversified operations. Some are issuing debt simply because they can. Earlier this month, Google raised about $32 billion through a bond sale that included a rare 100-year bond with a 6.125% coupon. Institutional investors showed strong demand.
On earnings calls, CEOs consistently emphasize unusually strong demand for AI computing power. While pockets of the market do look overheated, valuations for many AI beneficiaries remain below the extremes seen during the dot-com bubble.
Why the AI Panic May Be Overblown
History suggests that major technological shifts, from steam power to electricity to the internet, reshape industries rather than wipe them out. AI will automate certain tasks, but it is more likely to enhance human work, increase productivity, and create new kinds of jobs. Some roles will disappear, though others will emerge.
What It All Means for Investors
AI enthusiasm has fueled the market rally over the past three years, yet adoption is still in its early stages. As use cases expand and cost savings become clearer, enterprise spending on AI should keep rising. The next phase is broader integration across industries, which could support earnings growth well beyond the biggest tech companies.
At the same time, policy uncertainty and high valuations raise the risk of market pullbacks. I expect markets to be as volatile in 2026 as we saw last year, if not more. For long-term investors, those corrections may offer opportunities to add positions in high-quality companies, ignoring short-term noise and headlines. Diversification is becoming more important as uncertainty grows.
The AI boom is still young. As adoption spreads and spending increases, new avenues for growth should open across the tech sector and beyond. Like every major technological wave, it will produce both winners and losers.
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Neena Mishra, CFA, FRM, is the Director of ETF Research for Zacks Investment Research. She manages the Zacks ETF Investor portfolio and hosts the ETF Spotlight podcast.
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