Core Insights - Morgan Stanley predicts a differentiated landscape for global AI technology development by 2026, with significant growth in computing power demand surpassing supply capabilities, and strong policy initiatives from the Trump administration [2][3][4]. Group 1: AI Technology Development - The report anticipates a leap in capabilities for leading AI models in the U.S. by mid-2026, while competitors in other regions will struggle to achieve similar advancements, creating a "two worlds" scenario in AI development [5]. - Market sentiment regarding AI adoption is expected to shift from concerns in early 2026 to optimism later in the year, driven by non-linear growth in AI capabilities [5]. Group 2: Computing Power Demand - The proliferation of AI applications and increasing complexity of use cases will lead to an exponential growth in computing power demand, which will outpace supply growth [6]. Group 3: Policy Initiatives - The Trump administration is predicted to implement stronger policies than expected, focusing on ensuring domestic supply of critical minerals, uranium, and metals, supporting manufacturing return, increasing military spending, and lowering consumer costs [7]. Group 4: AI Technology Transfer - There will be increasing pressure for AI technology transfer globally, as disparities in national AI capabilities may affect trade dynamics, with countries pursuing self-sufficiency and enhancing "domestic intelligence" [8]. Group 5: Energy Costs and Policies - Rising global energy costs will trigger a backlash against data center growth, leading to the introduction of low-cost energy support policies and encouraging data center projects to adopt off-grid power strategies [9]. Group 6: Integration of Energy Infrastructure - Major AI companies will accelerate the integration of energy infrastructure to control their energy destiny, secure the most reliable and cost-effective energy sources, and enhance energy efficiency through AI [11]. Group 7: Global Manufacturing Landscape - China is expected to increase its share in key technology-intensive industries, while the U.S. manufacturing balance will tilt towards domestic production as technology diffusion diminishes the advantage of low-cost labor [12]. Group 8: Investment Cycle in Latin America - Policy shifts, geopolitical changes, and peak interest rates will drive Latin America into a new investment cycle, characterized by investment-led growth rather than consumption [13]. Group 9: Retraining Initiatives - Companies and governments will launch extensive retraining programs to address employment changes driven by AI, with political sensitivity around perceived job losses prompting various policy interventions [14]. Group 10: Transformative AI Impact - By the second half of 2026, transformative AI is expected to lead to early signs of rapid price declines across multiple sectors, exacerbating wage inequality, increasing capital expenditures, and putting upward pressure on interest rates, thereby reshaping national competitiveness [15].