AI, Clean Energy & Health Stocks: The Big Winners in a Multipolar 2026
ZACKS·2026-02-20 20:01

Economic Overview - Global GDP growth is projected at 2.7–2.8% for 2026, below pre-COVID averages, with advanced economies growing modestly and Asia-Pacific, particularly India, showing resilience with a growth rate of approximately 6.6% [1] - The IMF forecasts advanced economies to grow around 1.8%, while emerging markets and developing economies are expected to exceed 4% growth in 2026, indicating a widening economic gap [2] Market Polarization - Equity markets are experiencing polarization, driven by significant capital flows into megatrends such as AI investment, clean energy, and healthcare [3] - Artificial intelligence investment is identified as the primary driver of market polarization in 2026, with major technology companies significantly increasing capital expenditures [4] AI Investment - Major technology firms, including Amazon, Alphabet, Microsoft, and Meta, are projected to spend approximately $650 billion on AI-related infrastructure in 2026, marking a 67% increase from 2025 [5] - Semiconductor foundries are expanding, with Taiwan Semiconductor (TSM) raising its 2026 capex target to $52-$56 billion, reflecting strong demand for AI [7] Sector Analysis AI & Technology Infrastructure - Companies involved in AI infrastructure, such as NVIDIA (NVDA) and Vertiv Holdings (VRT), are positioned to benefit from the AI capital-expenditure cycle, with NVDA expected to report earnings growth of 57.7% in fiscal 2027 and VRT projected to grow earnings by 46.9% in 2026 [9] Renewable Energy & Battery Materials - The energy transition is accelerating, with Albemarle (ALB) expected to benefit from rising lithium demand linked to electric vehicles and stationary storage, projecting an earnings growth of 855.7% in 2026 [10] Healthcare & Biotech - The healthcare sector is supported by demographic trends and technological innovations, with Axsome Therapeutics (AXSM) expected to achieve 109% earnings growth in 2026, driven by advancements in AI-assisted drug discovery [11]