面对老板对AI的高期望、高要求，CIO如何破？

Core Insights - The article discusses the challenges faced by companies in implementing AI technologies, particularly the disconnect between high expectations from leadership and the practical limitations of AI applications [1][3][5]. Group 1: AI Implementation Challenges - Companies are experiencing "AI anxiety," where leadership has high expectations for immediate results from AI applications, leading to pressure on CIOs to deliver [1][3]. - There is a lack of integration in AI application scenarios, resulting in fragmented functionality and value, making it difficult for traditional enterprises to achieve systematic breakthroughs [2][4]. - The overhyped perception of AI as a universal solution has led to unrealistic expectations, with leaders often overlooking the complexities involved in AI implementation [3][5]. Group 2: Root Causes of AI Value Realization Issues - Cognitive biases among leadership lead to inflated expectations of AI's capabilities, causing projects to get stuck in a "high but not achievable" dilemma [5][6]. - Organizational challenges include the absence of a dedicated technical team and a lack of cross-departmental collaboration, resulting in AI projects being disconnected from actual business needs [6][7]. - The foundational issues encompass inadequate technical, management, and data infrastructure, as well as insufficient funding for sustained AI initiatives [7][8]. Group 3: Recommendations for Overcoming AI Implementation Barriers - Companies should learn from industry benchmarks by conducting field research on successful AI applications, focusing on real implementation paths and lessons learned [9]. - It is essential to engage in deep communication with business departments to clarify AI implementation goals and develop a strategic path that aligns with business needs [9]. - Starting with small-scale pilot projects can help validate technical paths and business value, avoiding the pitfalls of overextending resources at the outset [9].