U.S. stocks closed sharply lower on Tuesday as investors weighed the risk that an expanding Middle East conflict could push energy prices higher for longer, reigniting inflation pressures and complicating the policy path for the Federal Reserve.

Selling was broad-based across sectors, with the Cboe Volatility Index, widely known as the VIX, climbing to its highest closing level since November — a signal that demand for downside protection has intensified. Major indexes, however, finished well off their intraday lows after staging a partial recovery in afternoon trading.

The Dow Jones Industrial Average fell 403.51 points, or 0.83%, to 48,501.27. The S&P 500 lost 64.99 points, or 0.94%, to 6,816.63, while the Nasdaq Composite declined 232.17 points, or 1.02%, to 22,516.69. Earlier in the session, the S&P 500 had been down more than 2%.

Investors are increasingly focused on the inflationary implications of the conflict, now in its fourth day, as oil prices extend sharp gains. Israeli and U.S. forces have struck targets across Iran, prompting retaliatory attacks around the Gulf and drawing Lebanon into the widening hostilities. The risk of sustained disruption to energy infrastructure has become a central market concern.

“There seems to be some notion that perhaps (the Iran war) will persist longer than people thought 24 hours ago, because it’s spreading and starting to potentially impact energy infrastructure,” said Chuck Carlson, chief executive officer of Horizon Investment Services in Hammond, Indiana.

Tehran’s threat to attack vessels attempting to transit the Strait of Hormuz — a chokepoint that carries roughly one-fifth of global oil consumption — has amplified fears of supply disruptions. Production halts by several Middle Eastern oil and gas producers have already pushed up global shipping rates and driven crude and natural gas prices higher.

In response, President Donald Trump said he had directed the U.S. International Development Finance Corporation to provide political risk insurance and financial guarantees for maritime trade in the Gulf. He added that the U.S. Navy could begin escorting oil tankers through the Strait of Hormuz if necessary. The comments underscore the strategic stakes for global energy markets and the administration’s attempt to reassure traders and shipping operators.

Higher oil prices present a direct challenge for inflation dynamics in the United States. Energy costs filter through transportation, manufacturing, and consumer prices, raising the prospect of renewed price pressures just as policymakers were attempting to stabilize inflation expectations following earlier tariff-driven increases. U.S. Treasury yields rose for a second consecutive session, reflecting market unease about the inflation outlook and the possibility that interest rates may need to remain elevated for longer.

In a potentially bearish technical signal, the S&P 500 closed below its 100-day moving average for the first time since November 20. Such breaches are often viewed by market participants as indications of weakening momentum and can trigger algorithmic selling or portfolio rebalancing.

“Investors are grappling with the volatility and the news, and they’re looking at their portfolios and saying, wow, this could get worse… This is the fear of it getting worse,” said Oliver Pursche, senior vice president and advisor at Wealthspire Advisors in Westport, Connecticut. “But our advice to clients is to take a step back and wait and see.”

Despite the losses, some analysts described the broader reaction as measured rather than panicked. Jed Ellerbroek, portfolio manager at Argent Capital, said the market’s response “so far is very tame,” suggesting risk appetite has not collapsed. He noted that software stocks, which had been under pressure in recent weeks, outperformed on Tuesday. The S&P 500 software and services index rose 1.6%, indicating selective buying even amid headline-driven volatility.

That rotation into software may reflect a search for earnings streams less exposed to commodity inputs and global shipping risks. Technology and digital services firms typically have lower direct sensitivity to oil prices compared with industrials or transportation companies, making them relatively safe havens during energy-driven shocks.

Still, market breadth painted a cautious picture. On the New York Stock Exchange, declining issues outnumbered advancers by a 4.1-to-1 ratio, with 137 new highs and 167 new lows. On the Nasdaq, 3,540 stocks fell compared with 1,262 gainers, a nearly 3-to-1 imbalance. The widespread nature of declines suggests institutional investors were trimming exposure rather than simply rotating within sectors.

Alternative asset managers were not immune. Shares of Blackstone dropped 3.8% after its flagship credit fund, BCRED, experienced a surge in redemption requests. The development highlights how geopolitical uncertainty can spill over into private credit markets, where liquidity management is critical during periods of stress.

The broader macro question confronting investors is whether the conflict will remain contained or evolve into a prolonged disruption to global energy flows. A sustained spike in oil could undermine consumer spending, weigh on corporate margins, and delay the Federal Reserve’s ability to ease monetary policy. At the same time, escalating military involvement raises the risk of further market shocks.

However, the pattern of sharp intraday declines followed by partial recoveries suggests that while fear is rising, outright capitulation has not taken hold. Much will depend on the trajectory of energy prices and whether diplomatic efforts or security measures stabilize shipping through the Strait of Hormuz in the coming days.

Until clarity emerges, volatility is likely to remain elevated, with markets balancing geopolitical risk against still-resilient corporate earnings and economic data.

Billionaire investor Ray Dalio says artificial intelligence is rapidly reshaping the global economy, but cautions that the companies at the center of the surge may not generate the profits investors are banking on.

In an episode of the All-In Podcast published Tuesday, the founder of Bridgewater Associates described AI as a force that is “eating everything,” while warning that the boom could also “eat itself” if financial returns do not justify the enormous capital being deployed.

Dalio framed his concern around a recurring market error: confusing a technological revolution with the success of the companies attempting to monetize it.

“The technologies will go on, but the companies won’t necessarily go on,” he said, adding that it is common during periods of innovation for many firms to fail to convert excitement into sustainable earnings.

His remarks arrive at a time when global technology firms are committing record sums to AI infrastructure — from advanced semiconductors to vast data centers — in what many analysts describe as the most capital-intensive phase of the digital era since the buildout of cloud computing.

Capital intensity versus cash flow

The AI buildout has been characterized by extraordinary upfront spending. Leading U.S. firms have earmarked tens of billions of dollars for chips, model training, energy supply agreements, and next-generation cloud infrastructure. The expectation is that generative AI will unlock new enterprise software markets, automate labor-intensive processes, and create entirely new revenue streams.

Dalio’s caution centers on whether the monetization curve will keep pace with the spending curve.

If companies invest heavily now but face pricing pressure later — whether from competition, commoditization, or open-source alternatives — profit margins could narrow. That dynamic has historical precedent. During the dot-com era, the internet permanently transformed commerce and communication, yet many early internet firms collapsed when revenues failed to cover operating costs and debt obligations.

The infrastructure endured. Equity valuations did not.

Dalio suggested that AI may follow a similar trajectory: technological inevitability combined with corporate fragility.

Competitive pressure from China

Another dimension of risk, Dalio noted, is geopolitical and cost-based competition. China has released increasingly capable AI systems at comparatively low cost, a development that could undercut pricing strategies of U.S. firms investing heavily in proprietary models.

If Chinese developers can deliver comparable functionality at lower cost, U.S. firms may struggle to recoup capital expenditures at projected margins. That would compress returns precisely as investors expect outsized gains.

The competitive dynamic also raises broader macroeconomic questions. A global AI race may intensify spending as companies and governments seek technological leadership. But a supply glut of capable AI models could drive down monetization potential.

Dalio’s comments coincide with renewed investor anxiety following a widely circulated February report by Citrini Research. The report, structured as a speculative look back from 2028, imagines a rapid acceleration in AI adoption that ultimately destabilizes the broader economy.

In Citrini’s hypothetical timeline, AI-driven automation sharply reduces white-collar employment. As companies automate tasks previously performed by professionals, income growth slows, consumer spending weakens, and economic expansion falters. The scenario culminates in a stock market crash, even as AI technology itself continues advancing.

“By the end of 2027, it threatened every business model predicated on intermediation. Swaths of companies built on monetizing friction for humans disintegrated,” the report stated.

The analysis unsettled some investors, particularly in sectors exposed to automation risk, and contributed to a bout of equity market volatility.

Several economists and market strategists, however, have described the report as a worst-case thought experiment rather than a forecast. They argue that labor markets tend to adjust gradually, with job displacement offset by new categories of employment, productivity gains, and policy responses.

Valuation risks and historical cycles

AI-linked stocks have seen significant valuation expansion over the past two years. Investors are not only pricing in earnings growth but also structural transformation across industries, including finance, healthcare, logistics, and media.

Dalio’s warning touches on a core tension in such cycles: innovation can be transformative at the societal level while proving uneven for shareholders.

Railroads in the 19th century, electricity in the early 20th century, and the internet in the late 20th century each triggered waves of speculative capital. Overcapacity, misallocation, and unsustainable business models followed in several cases. Consolidation eventually left a smaller group of dominant players.

The question for today’s AI leaders is whether they will emerge as durable profit generators or casualties of capital overshoot.

Beyond corporate earnings, AI raises macroeconomic implications. Optimists believe that automation will boost productivity, reduce operational costs, and expand economic output. That view has been echoed by technology executives, including Elon Musk, who have predicted sweeping gains in efficiency and innovation.

However, skeptics caution that productivity gains may take time to materialize, while labor displacement could occur more quickly. If job losses in professional sectors outpace the creation of new roles, consumer demand could weaken — a risk highlighted in the Citrini scenario.

Dalio did not endorse that outcome as inevitable, but his remarks suggest concern about misalignment between technological progress and financial sustainability.

At the core of Dalio’s warning is a simple principle: valuation ultimately depends on cash flow.

If AI systems generate measurable productivity gains that translate into higher margins and new services, today’s investment wave could be justified. If revenue growth lags capital expenditure, however, markets may be forced to reassess.

However, AI remains the dominant narrative in global markets – at least for now. Corporate earnings calls frequently center on AI integration, and capital markets continue to reward firms perceived as leaders in the space.