美股软件股持续下跌，市值蒸发超万亿美元

Group 1 - The software sector in the US has seen a market value decline of over $1 trillion since late January 2026, driven by investor fears that traditional software business models may be fundamentally disrupted by AI [2] - The iShares Expanded Tech-Software Sector ETF (IGV) dropped 2.19% on February 17, 2026, closing at $80.96, with a cumulative decline of over 23% since the beginning of 2026, significantly underperforming the broader market [2] - Concerns about AI replacing existing software functionalities have been growing since the second half of 2025, leading to a reevaluation of the sector [2] Group 2 - A conservative earnings guidance from several SaaS companies in January 2026 highlighted extended sales cycles and customer evaluations of AI's impact, serving as a catalyst for the market downturn [2] - The introduction of Anthropic's Claude model and its industry plugins on January 12, 2026, was seen as a direct challenge to the traditional SaaS subscription model [2] - Following this, the narrative shifted from "AI empowering all industries" to "AI reshaping industry competition," leading to a significant sell-off in the software and services sector [3] Group 3 - By January 29, 2026, the IGV experienced a single-day drop of 5.4%, marking a more than 20% decline from recent highs and officially entering a bear market [3] - The S&P Software and Services Index experienced extreme volatility, with a single-day drop exceeding 7% during early February 2026 [3] - Comparisons have been made between the software industry and the newspaper industry, which faced erosion of its business model due to the internet [3] Group 4 - Concerns regarding the disruptive potential of large language models (LLMs) have been amplified, with warnings that software companies failing to adapt may face long-term decline [4] - Deloitte's 2026 global software industry outlook suggests that AI's impact may create new market opportunities, predicting that AI-based solutions could capture 60% of the software market by 2030 [4] - The speed and extent of AI disruption will be significantly influenced by regulatory environments and industry characteristics, particularly in highly regulated sectors like finance [4]