According to Bloomberg Business, the upcoming earnings reports from BI’s Global Bellwethers—133 of the world’s largest companies across markets and sectors—will test whether AI can continue driving market performance. Despite earnings and sales estimates climbing over the past three months, forecasts remain below start-of-year levels due to persistent trade tensions. Tech sector earnings are projected to grow 24.6% in 2025 after 27% in 2024, then ease to 20.5% in 2026, while AI bellwether margins are expected to surge 222 basis points from 2024 to 2026 compared to just 51 basis points for non-AI firms. The analysis shows US margins extending their lead through 2026, projected to reach 18.8% next year, while emerging markets may slip 13 basis points to 16.7%. This critical earnings season will determine whether AI’s market leadership can persist as expectations rise.
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The AI Expectations Trap
What Bloomberg’s analysis reveals—but doesn’t explicitly state—is that we’re witnessing a classic artificial intelligence expectations trap. The very success of AI companies in beating lowered Q2 expectations has created a dangerous dynamic where the bar keeps rising while fundamental economic headwinds persist. Markets rewarded AI stocks for clearing low hurdles, but now face the reality that Q3 forecasts are higher and the easy comparisons are disappearing. This creates a scenario where even strong absolute performance might disappoint if it doesn’t exceed increasingly optimistic projections. The margin expansion story has been powerful, but as AI adoption matures, sustaining 200+ basis point margin improvements becomes increasingly challenging without corresponding revenue acceleration.
Trade War Reality Check
The narrowing US growth premium versus emerging markets—now back to pre-trade war levels—suggests the initial tariff benefits may have been overstated. While trade tensions initially boosted US forecasts, the reality is that protectionism typically creates winners and losers within economies rather than delivering broad-based advantages. The US margin leadership, while impressive, masks vulnerability: high-margin AI exposure is offsetting tariff headwinds, but this balancing act becomes increasingly precarious as AI growth moderates. The developed ex-US markets, still heavily reliant on American demand, face particular risk if global growth stumbles amid ongoing trade uncertainty. This creates a fragile foundation for the projected 2026 convergence between AI and non-AI earnings growth.
Sector Rotation Implications
The projected sector performance shifts for 2026 represent more than just statistical reversion—they signal potential major portfolio rotations. Discretionary’s expected flip from -5.4% contraction to 16.8% growth suggests markets are pricing in a consumer recovery that may or may not materialize. More importantly, the narrowing growth gap between tech and other sectors creates a dangerous assumption that traditional sectors can seamlessly pick up the slack as AI moderates. In reality, the capital investment cycles, professional services adoption curves, and productivity gains driving AI’s outperformance aren’t easily replicated in consumer staples or industrials. The risk is that markets are extrapolating current trends without accounting for the structural advantages that have concentrated benefits in the technology sector.
Margin Compression Risks
The projected margin expansion for AI bellwethers faces multiple threats that Bloomberg’s analysis underweights. First, the AI infrastructure arms race is becoming increasingly capital-intensive, with rising costs for talent, compute resources, and data acquisition. Second, regulatory scrutiny is intensifying globally, which could force platform changes and compliance costs that compress margins. Third, the very success of AI companies in achieving 26.9% margins invites competitive response and customer pushback on pricing. While financial data providers can track these metrics, they can’t capture the strategic shifts that might be necessary to defend such elevated profitability in the face of growing competition and regulatory pressure.
Investment Strategy Conclusions
The most significant insight for investors isn’t the projected numbers themselves, but the convergence narrative they support. Markets appear to be preparing for a soft landing where AI gracefully hands off leadership to broader market participation. However, this assumes near-perfect execution across multiple sectors facing different challenges. The discretionary rebound depends on consumer resilience despite potential economic slowing. The materials steadiness assumes construction and industrial demand holds. The financial acceleration requires stable interest rates and credit conditions. Any one of these assumptions failing could leave markets overly reliant on AI companies continuing to beat elevated expectations—precisely when their comparables are becoming most challenging.
