站在新年的起点，2026年的投资大幕已拉开。回顾过去一年，A股市场在科技浪潮的推动下表现亮眼， 创业板指和科创50指数分别上涨49.57%和35.92%，成长风格独领风骚。随着2026年"十五五"开局之年 的到来，宏观经济与产业格局面临深度调整，市场的关注点从单纯的赛道炒作转向了更为务实的盈利兑 现。记者采访多位基金经理获悉，科技创新特别是AI产业的落地与变现将成为资金掘金的主战场，市 场风格预计将较2025年更加均衡，投资者需警惕赛道拥挤风险，理性构建投资组合。 科技创新确立增长引擎地位 2026年作为"十五五"规划的开局之年，经济发展质量的提升被置于首位。银河基金研究部总监王丝语指 出，新的规划更加强调因地制宜发展新质生产力，推动科技创新与产业创新深度融合。在招商基金研究 部首席经济学家李湛看来，中国经济增长模式已逐渐从地产拉动转向创新驱动，基建和高技术产业接棒 成为拉动经济增长的新动力。尽管在转型期间居民消费及投资可能因房产价格调整而趋于谨慎，但高新 技术产业创造高质量增长的能力已成为市场共识。 方正证券研究所副所长燕翔认为，高质量发展将成为贯穿2026年全年经济工作的主线。当前，我国高技 术制造业、绿 ...

Core Viewpoint - The AI investment cycle is transitioning from "investment" to "returns," but this does not imply a slowdown is a peak. Goldman Sachs indicates that despite a deceleration in growth, AI infrastructure investment will remain sustainable over the next 2-3 years, with cost benefits already being realized and stock prices not yet reflecting this structural change [1][2]. Group 1: AI Investment and Returns - Goldman Sachs categorizes AI value creation into three phases: cost reduction through automation (current phase), reinvestment and rebuilding, and revenue generation through incremental income [2][3]. - AI applications in customer service, sales, and IT are already yielding tangible benefits, with 43% of call centers adopting AI tools and achieving an average operational cost reduction of 30% [2][3]. Group 2: Cost Savings and Future Projections - By 2030, AI automation could save Fortune 500 companies approximately $935 billion, representing about 14% of their total costs, with a net present value return of around $780 billion against a cumulative investment of $350 billion [3][4]. - Major cloud service providers are the primary investors in AI infrastructure, focusing on long-term revenue growth opportunities rather than short-term cost savings, complicating ROI calculations [3][4]. Group 3: Infrastructure Spending and Demand - Concerns about whether infrastructure spending has peaked, particularly regarding training chip inventory and demand, are considered overstated by Goldman Sachs [4][5]. - Large tech companies like Microsoft, Amazon, Google, and Meta are expected to maintain their AI infrastructure investments without significantly compressing profit margins over the next 2-3 years [5][6]. Group 4: New Demand Drivers - Demand for "inference" computing from enterprise clients and government (sovereign AI) is emerging as a new spending driver, especially as small and medium enterprises rapidly expand their deployment of customized models or edge AI applications [6][7]. Group 5: Market Valuation and Stock Performance - The market has partially priced in strong demand expectations for Nvidia's next-generation GPUs, but there is still insufficient valuation for its expanding customer base and the potential explosion of AI inference business [8]. - Broadcom's stock price increase is attributed to clear guidance indicating AI revenue growth of 60% in FY25 and FY26, suggesting that the stock price rise reflects a clearer mid-term fundamental improvement path [8].

Group 1: AI Development and Trends - The pace of AI development and adoption is unprecedented, with OpenAI's ChatGPT reaching 800 million weekly active users by April 2025, achieving 90% of its user base outside North America within three years, compared to 23 years for the internet [5][8] - The report highlights a significant increase in user engagement, with the percentage of American adults using ChatGPT rising from 18% in July 2023 to 37% by January 2025, and daily usage time increasing by 202% in just 21 months [9] - The construction of data centers has surged, with private data center construction in the U.S. experiencing an annualized growth rate of 49% over the past two years, while global data center electricity consumption has grown at an average rate of 12% per year since 2017 [12] Group 2: Economic and Competitive Landscape - AI is witnessing unprecedented capital investment, with major AI companies like OpenAI projected to have revenues of $3.7 billion in 2024, while their computing-related expenses may reach approximately $5 billion [16] - The competition in the AI sector has intensified, with the number of large-scale multimodal models released increasing by 1150% over the past two years, and the performance of open-source models rapidly catching up to proprietary models [18][21] - The report draws parallels between the current AI investment frenzy and historical technology cycles, such as the 19th-century railroad boom and the internet bubble, highlighting the potential for market corrections [16][37] Group 3: Societal Impact and Workforce Transformation - AI is reshaping the workforce, with job postings related to AI increasing by 448% in the U.S. over the past seven years, while non-AI IT job postings have decreased by 9% [32] - The report emphasizes that while AI may automate certain jobs, it will also create new opportunities, requiring workers to adapt to new roles that involve supervising and collaborating with AI systems [32] - The influence of AI is extending beyond digital realms into physical applications, with autonomous vehicles like Tesla's FSD achieving significant mileage growth and AI-driven systems transforming various industries [22][25] Group 4: Geopolitical Dynamics - The race for AI supremacy has become a central focus of geopolitical competition, particularly between the U.S. and China, with AI technology now seen as a key component of national power [36] - China's rapid advancements in AI, including a significant increase in the number of large-scale AI systems, position it as a formidable competitor to the U.S. in the global AI landscape [21] - The report highlights the importance of intellectual property protection and technology security, noting that countries like China are actively working to absorb and replicate U.S. AI technologies [36]