整个2025年，我与无数企业领袖探讨了他们的AI战略，试图了解哪些措施有效，哪些构成了阻碍。随 着时间推移，我注意到有三个趋势在不同公司和行业中反复出现，它们决定了哪些企业能借助AI取得 成功，哪些会陷入困境。现将这些趋势汇总，分享来自AI转型一线的经验教训。 首先，AI在后端任务中的应用正在蓬勃发展，这表明真正能产生实际影响的往往是那些"枯燥"的工作。 第二个趋势与技术无关，而关乎人：企业如何对待员工，对其AI应用的成败至关重要。然而，或许最 能说明问题的趋势是关于初始战略和动机的：追逐AI技术本身的企业往往失败，而以解决问题为出发 点的企业则能取得成功。 当然，成功的因素远不止这些——从数据治理到安全与合规。但上述这些趋势，无论好坏，正在塑造企 业的AI实践。 摒弃"为AI而AI" 咨询公司韦斯特门罗（West Monroe）的AI与新兴技术负责人埃里克·布朗（Erik Brown）今年早些时候 告诉《财富》，他目睹了许多公司在概念验证未能达到预期后，陷入了"AI疲劳"。他指出，陷入此境地 的企业有一个共同点：要么选错了应用场景，要么误解了AI在该任务中可能（或不可能）发挥的作 用。更具体地说，他们的出发 ...

在麦肯锡有一个雷打不动的习惯：每年两次，团队会坐下来进行残酷而诚实的"照镜子"。围绕咨询顾问 的"核心技能（core skill）"问几个问题：你是否匹配或超越了职级要求？和上次比，有什么具体长进？ 由于这些进步，你为客户带来哪些改变，有哪些具体的实证？ 为什么麦肯锡这么激进地要求顾问提升核心技能？因为这些技能塑造了这家咨询机构的差异化竞争优 势。 在此刻重提医疗机构的"专业化管理"？ 科室经营助理，作为庞大医疗系统中的特殊群体，不拿手术刀，也不做床旁护理，但我们是科室主任 的"参谋长"，是学科发展的"大管家"。我们的每一个决策，都直接关联着临床的效率和患者的体验。 中国医院管理正在经历一场从"手工作坊"到"精密机器"的剧烈蜕变。在DRG/DIP支付改革和国考绩效的 双重倒逼下，粗放式的规模扩张已是明日黄花。医院不仅要"看病好"，也要"运营好"。 医疗行业当下正有前所未有的必要性和紧迫感，把专业管理提到重要高度，像打造学科能力一样，把管 理能力也作为自己的竞争优势来打造。 然后以量化的方式指导行动，设定"怎么去"的行动举措，然后用反馈的结果优化举措。 没有量化比较的"改善"，很可能只是运气的随机误差。 第二项 ...

Core Viewpoint - The article emphasizes that successful implementation of generative AI in organizations relies more on effective change management than on the technology itself. It highlights the importance of aligning AI with the organizational culture and capabilities to create value [2]. Group 1: Establishing a "North Star" Goal - Organizations should focus on outcomes rather than viewing generative AI merely as a tool. AI should be seen as a capability that enables seamless collaboration between humans and AI [3]. - A "North Star" goal must be clear and ambitious, guiding how generative AI can create value and competitive advantage while considering its impact on the talent lifecycle [3][4]. Group 2: Building Trust through Data and Governance - Establishing trust in generative AI within organizations is crucial for its widespread adoption. Companies that invest in trust-building activities are more likely to see significant revenue growth [5][8]. - Leaders must prioritize data accessibility and governance as key components of change management, ensuring that AI outputs are reliable and trustworthy [8][9]. Group 3: Redesigning Workflows and Teams - Generative AI should be integrated into workflows rather than treated as a standalone tool. This requires a collaborative approach between business and technical teams to redefine work processes [10]. - The transformation can occur in three stages, from using AI for discrete tasks to fully autonomous AI clusters operating as minimal viable organizations [11][12]. Group 4: Restructuring Organizational Architecture - Different departments may require different structural adjustments, with some evolving into minimal viable organizations while others maintain enhanced human teams [15][16]. - Organizations must invest in AI operations and monitoring systems to ensure the efficient functioning of these new structures [16]. Group 5: Empowering Employees as Change Agents - Employee participation is vital for the success of generative AI integration. Higher employee involvement correlates with better transformation outcomes [17]. - Companies should encourage employees to become advocates for AI, fostering a culture of learning and adaptation [18][19].

Group 1 - The core viewpoint is that the biggest bottleneck in AI development lies in organizational culture rather than technology or application scenarios [2][3] - Successful AI transformation must be driven by CEOs and business needs, focusing on profit rather than just application scenarios [3] - Recent years have seen a strong increase in investment and innovation in AI, with approximately $90 billion in venture capital received by AI companies in Q2 2025 [2] Group 2 - Chinese companies need to learn to compete in new "trade corridors" including Southeast Asia, the Middle East, Latin America, Eastern Europe, and Africa [3] - The globalization process of Chinese enterprises is divided into three stages: reliance on low-cost manufacturing, overseas mergers and acquisitions, and achieving sustainable development as global corporate citizens [4] - Currently, only 12 out of the top 100 global brands in 2024 are from China, compared to 61 from the United States, indicating a need for improvement in global brand presence [3][4]