The financial world has, for over a year, been swept up in an intoxicating wave of artificial intelligence euphoria, largely viewing the AI boom as an unmitigated boon for asset prices. Even the typically optimistic analysts at Bank of America Research initially echoed this sentiment. However, a significant shift is now underway. BofA’s European equity strategy team, known for its more cautious stance, has issued a stark warning: the relentless optimism surrounding AI is officially beginning to crack, with early 2026 marking a pivotal turning point.
In a recent client note, BofA strategists declared that “doubts around the AI revolution are emerging.” The market narrative, once singularly focused on “upside-only” potential, is rapidly evolving into a more nuanced, and frankly, apprehensive view of AI as a “double-edged sword.” At the heart of these burgeoning fears is a sobering realization: AI may not universally elevate corporate profits; it could, in fact, actively erode them. BofA has pinpointed several substantial “downside risks” that are casting a shadow over the once-unquestioning AI trade, introducing a landscape fraught with “cannibalization,” capital expenditure cuts, and other AI-related market anxieties.
The Cannibalization Conundrum: Profits Under Threat
A glaring blind spot in current market expectations, according to BofA, is the widespread assumption of sustained, robust earnings growth. The prevailing sell-side consensus projects an astonishing 17% compound annualized earnings per share (EPS) growth for global equities over the next five years. This ambitious forecast, strategists argue, forms the core of what they term the “cannibalization paradox.”
Corporate profit margins are already hovering at historic highs, a factor that significantly complicates such a lofty 17% EPS growth projection. Historically, double-digit compound EPS growth has typically been achieved only during periods when margins were depressed, allowing ample room for expansion. These “optimistic” projections, therefore, implicitly assume that tech EPS growth driven by AI adoption will be both sustainable and, crucially, will not “cannibalize existing profit pools.”
It is precisely this assumption that investors are now “rethinking” most profoundly. Evidence of this shift is visible in the sharp declines experienced by sectors deemed vulnerable to AI disruption, such as software, insurance, and wealth management. Conversely, there’s a discernible flight to safer havens—sectors reliant on physical assets, including mining, utilities, and chemicals. This painful reality has already manifested in the market; SAP, once hailed as an AI beneficiary, saw its substantial rally abruptly reverse. The subsequent selloff in software-as-a-service (SaaS) stocks, wiping out over $2 trillion in a mere two weeks, was tellingly dubbed the “SaaSpocalypse.”
Labor Market Instability and Capex Concerns
Beyond the direct threat of business cannibalization, BofA’s analysis extends to the broader macroeconomic risks posed by the widespread rollout of AI. The U.S. labor market, for instance, is already flashing warning signs. Three-month payroll growth has dwindled to an anemic 0.1%—a level historically associated with the conclusion of past equity bull runs, notably in 2000 and 2007, periods marked by bursting bubbles and painful recessions.
BofA cautions that AI-driven productivity gains, while seemingly beneficial, could further depress corporate demand for labor, exacerbating this existing weakness. Ironically, a wave of significant job losses could boomerang back to harm the very tech giants fueling the AI boom. These “hyperscalers” heavily depend on consumer advertising revenues, which, by their nature, require a healthy, employed consumer base to thrive. Analysts contend that the implicit assumption within current market and earnings projections is that labor market weakness is merely a temporary blip, attributable to factors like trade dynamics, immigration policies, or post-pandemic over-hiring during the “Great Resignation.” But what if these foundational assumptions are flawed?
Furthermore, the debt-fueled AI investment spree is exhibiting clear signs of strain. For the first time in the history of BofA’s Global Fund Manager Survey, investors have indicated a belief that companies are overinvesting and should curtail capital expenditures (capex). This sentiment is underscored by tangible market indicators: corporate bond spreads for U.S. hyperscalers have reached a three-year high, and private credit platforms with significant exposure to software debt are buckling under pressure, exemplified by Blue Owl’s recent suspension of retail investor redemptions for one of its funds. BofA’s U.S. equity strategy team anticipates these accumulating headwinds will culminate in an “AI air pocket” later in 2026.
The Productivity Puzzle and Stretched Valuations
Adding to this increasingly gloomy outlook, BofA warns that the much-anticipated economic boom from AI may ultimately fail to materialize as widely expected. While equity markets are currently pricing in a robust near 3% U.S. productivity growth, more conservative forecasters, such as the Congressional Budget Office, project AI will contribute a modest 0.1% annually to productivity over the next decade. This discrepancy highlights a significant gap between market optimism and expert projections.
Recent economic data further reinforces this caution. Fresh figures revealed that the U.S. economy grew much less than anticipated in the fourth quarter of 2025, expanding by just 1.4% after surprising economists with stronger growth earlier in the year.
In light of this evolving landscape, BofA has cautioned that AI infrastructure providers—including sectors like semiconductors, capital goods, and construction materials—now appear dangerously “stretched.” These industries are trading at all-time-high relative prices and peak earnings expectations, rendering them highly vulnerable to any disappointments in AI capital expenditure. The search for “AI hiding places” is on, as investors seek refuge from the storm.
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