爱分析：2026年企业AI落地趋势研究报告

Core Insights - The report emphasizes the transition of AI from a system tool to a digital employee, with 76% of global executives recognizing AI as capable of independently creating business value [1][12][14] - The evolution of digital employees is categorized into three levels: assistant, collaborator, and autonomous employee, with increasing decision-making capabilities and task complexity at each level [1][15][19] - The assessment framework for AI is shifting from technical metrics to business value indicators, focusing on per capita productivity as a core measure of AI's value [1][19][20] Group 1: Cognitive Shift - The recognition of AI as a digital employee rather than a mere tool is crucial for unlocking large-scale applications [12][14] - This cognitive shift influences technology development trends, application scenarios, and budget allocation priorities [21][22] - The report outlines a complete implementation framework for integrating digital employees into business processes, aiming for a significant productivity leap by 2026 [12][22] Group 2: Technological Trends - Digital employees are expected to achieve breakthroughs in three key capabilities: general capabilities for complex tasks, specialized capabilities for specific problems, and organizational capabilities for team collaboration [23][24] - By the end of 2026, foundational models will be able to complete complex tasks equivalent to an 8-hour workday, significantly enhancing productivity [24][26] - The multi-modal understanding ability of digital employees is projected to improve, enabling them to process longer video content and complex multimedia information [29][32] Group 3: Application Scenarios - Digital employees are increasingly embedded in core business functions, moving beyond simple data analysis to more complex operational tasks [42][43] - The methodology for identifying AI application scenarios has evolved from a focus on process optimization to task decomposition, allowing for greater efficiency and productivity [43][45] - A case study in aluminum production illustrates how digital employees can assist in optimizing production processes, enhancing overall quality and efficiency [48][49] Group 4: Budget Allocation - The overall IT budget for enterprises is expected to remain stable, while the proportion of AI budgets is significantly increasing, indicating a shift towards comprehensive AI deployment [50][51] - Approximately 80% of enterprises plan to allocate at least 10% of their IT budget to AI, with nearly half expecting AI budgets to account for 20-30% of total IT spending [52][53] - This budgetary shift reflects growing confidence in AI's potential to drive business value and efficiency [50][52]