MIT科技评论发布的最新报告指出，全球AI投资规模正在快速扩张，预计2026年将达到2.5万亿美元，同比增长44%1。然而，尽管投资持续增加，大多数企业仍未能通过AI实现收入增长或根本改变其运营方式1。
报告强调，企业AI发展的关键在于实现从工具应用向运营模式的转变，即"智能体转变"1。这一转变要求企业重新审视其基础设施建设策略。数据就绪性而非数据充丰度成为决定AI可叠加性的核心条件1。企业需要重建数据基础设施以确保可访问性，而不是单纯关注数据量的增加1。为了应对日益加剧的AI碎片化问题，企业应当采用可组合架构并重视AI主权1。
MIT Technology Review has released a report indicating that enterprise artificial intelligence has entered a phase of widespread operational deployment.1 The report projects global AI investment will reach $2.5 trillion by 2026, representing a 44% year-over-year increase.1
However, the report reveals a significant gap between investment and impact: most enterprises have yet to achieve revenue growth or fundamentally transform their operations through AI.1 The core challenge facing organizations is fragmentation across their AI deployments, necessitating a shift from viewing AI primarily as a collection of discrete tools to embracing it as an integrated operational model.1 This transition, which the report terms the "agentic shift," represents a fundamental reorientation in how enterprises approach and implement artificial intelligence systems.
The report identifies critical factors for successful enterprise AI transformation.1 Data readiness—rather than data abundance alone—emerges as the essential condition for making AI systems composable and scalable across an organization.1 Enterprises must rebuild their data infrastructure to ensure accessibility, moving beyond a focus on sheer data volume.1 Additionally, the report emphasizes the importance of composable architecture and AI sovereignty in enabling organizations to develop autonomous, integrated intelligence capabilities.
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