Morgan Stanley's Global Head of Thematic Research, Stephen C Byrd, has released a market outlook for 2026, outlining ten key predictions across four major themes: AI technology proliferation, the future of energy, a multipolar world, and social transformation, charting an evolution path for the technology-driven market landscape for investors. The investment bank anticipates that leading-edge U.S. large language models will achieve a significant leap in capability in the first half of 2026, while competitors in the rest of the world will struggle to match this progress in the near term. Concurrently, the exponential growth in computing power demand is expected to outpace the rate of supply expansion, fundamentally altering the economics of data centers. Morgan Stanley emphasizes that thematic investing has proven to be a robust source of alpha. In 2025, the firm's thematic equity portfolio outperformed the MSCI World Index by an average of 16 percentage points and surpassed the S&P 500 by 27 percentage points. The top three performing categories were all driven by dynamics within the multipolar world. These predictions span multiple dimensions including technology, energy, geopolitics, and labor markets, highlighting the profound impact of AI proliferation on the global economic structure and the consequent reshaping of national competitiveness. Prediction One: A Divergent Global AI Development Landscape Morgan Stanley forecasts that leading U.S. large language models will achieve a step-function improvement in capability during the first half of 2026, while competitors from other regions will find it difficult to achieve comparable breakthroughs within the same timeframe. This technological gap will create a "two-world" structure for AI development. At the application level, market sentiment is expected to undergo a significant shift. Concerns about AI adoption rates in the first half of 2026 will transition to optimism in the latter half, fueled by the non-linear growth of AI capabilities, with the scale of AI application benefits becoming increasingly evident. Prediction Two: Exponential Compute Demand Outstrips Supply Capacity The widespread adoption of AI applications and increasing complexity of use cases will drive an exponential surge in computing power demand, a pace that supply growth will struggle to match. Morgan Stanley has introduced a new "Intelligent Factory" model to help investors gain deeper insights into the data center-level economics for major model developers, with the report underscoring the attractiveness of these economic benefits. Prediction Three: A Robust Policy Agenda from the Trump Administration Morgan Stanley predicts that a Trump administration will pursue a more forceful action agenda than anticipated, focusing on securing domestic supplies of critical minerals, uranium, and metals; supporting manufacturing repatriation; increasing military spending with an emphasis on innovation; and reducing consumer costs. Prediction Four: Pressure for AI Tech Transfer and National Self-Sufficiency In response to the aforementioned trends, global pressure for AI technology transfer will intensify. Disparities in national-level AI capabilities are likely to influence trade dynamics, fueling a stronger pursuit of national self-sufficiency and enhancing "Gross Domestic Intelligence." Prediction Five: Rising Energy Costs Trigger Policy Backlash and Adaptation Increasing global energy costs will provoke a backlash against data center growth, prompting policies that support low-cost energy and driving data center projects to adopt "off-grid" power strategies. This politicized issue is set to reshape the development trajectory of data centers. Prediction Six: AI Giants Accelerate Integration of Energy Infrastructure Major AI firms will take steps to strengthen their control over energy infrastructure, aiming to master their own destiny, secure the lowest-cost and most reliable energy swiftly, shield other electricity customers from the impact of AI growth, and leverage AI to enhance energy and electrical efficiency, leading to a significant deepening of the AI-energy fusion. Prediction Seven: Reshaping of the Global Manufacturing Map China is expected to increase its global manufacturing market share in key technology-intensive industries. Simultaneously, as technology diffusion diminishes the advantage of low-cost labor, the U.S. manufacturing scale will tilt towards domestic production. Regions with high-cost structures, stringent regulations, and low AI adoption will lose market share. Prediction Eight: Latin America Enters a New Investment Cycle Driven by Triple Transformation Policy shifts, geopolitical changes, and peaking interest rates are projected to propel Latin America into a new investment cycle, with this bull market being driven by investment rather than consumption. Prediction Nine: Corporations and Governments Launch Large-Scale Reskilling Initiatives Businesses and governments will roll out extensive reskilling programs to address AI-driven employment changes. Political sensitivity surrounding real or perceived job losses due to AI application will trigger a series of policy interventions. Prediction Ten: Transformative AI Reshapes Economics and Asset Valuations Morgan Stanley expects early signs to emerge in the second half of 2026 of transformative AI driving rapid price declines across multiple sectors. This will further lead to intensified wage inequality, increased capital expenditure, risks of upward pressure on interest rates, and a rise in the value of assets that cannot be "replicated" by AI, collectively reshaping the landscape of national competitiveness.