[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fTMfrdQo5nJd0mt8yFke1aj1UrM3QHXCQTsQOE7tk6ak":3},{"code":4,"msg":5,"data":6},200,"操作成功",{"id":7,"title":8,"content":9,"digest":10,"source":10,"coverPath":11,"thumbsCoverPath":12,"isTop":13,"isShow":14,"baseClick":13,"clickCount":15,"createTime":16,"typeId":17,"isNewest":18,"newsInfoTypeRespVo":19,"voiceUrl":22,"voiceSize":23,"taskId":24,"releaseTime":25,"titleEn":26,"contentEn":27,"voiceUrlEn":28,"taskIdEn":29,"voiceSizeEn":30},1280,"AI 明星的天价年薪，是竞争利器还是泡沫？","\u003Cp>\u003Cstrong class=\"ql-lineHeight-1-75\" style=\"font-size: 18px; color: rgb(255, 153, 0);\">你知道如今炙手可热的顶级AI人才的年薪有多高吗？这体现了企业之间什么样的竞争意图？对于企业的薪酬策略和绩效影响将如何？中欧国际工商学院管理学教授、中欧首席人力资源官（CHRO）课程-课程主任韩践透过AI顶级人才天价年薪的表象，刨析人才争夺战的历史演进和对企业管理带来的影响，并从长期主义的角度，提出更具现实意义的人才管理建议。\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F08\u002F9cf81e258882419d9e665f351d67588e\u002F784d5e96ab384697b64f7c0a02b8a6fa.webp\" width=\"536\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">据海外媒体报道，Meta、OpenAI等科技巨头正以数百万美元的薪资争夺AI领域的顶尖研究员。近期，OpenAI有员工跳槽，引发了公司高层的担忧。OpenAI首席研究官Mark Chen在内部信中批评Meta趁OpenAI放假期间挖人，称：“感觉有人闯进家里偷了东西。”他还表示，OpenAI正在调整薪酬结构和奖励制度，以留住人才。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">从薪酬数据来看，高级AI科学家的年薪普遍在300万~700万美元，个别甚至超过1000万美元，较2022年上涨约50%。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">薪酬数据追踪网站Levels.fyi显示：Meta的AI工程师薪酬中位数为56万美元，最高可达350万美元以上；OpenAI的工程师薪酬中位数为87万美元，高级工程师的薪酬可达134万美元；而普通软件工程师的薪酬中位数为18.5万美元，大多数人的薪资仅在13万~36万美元，远低于AI岗位。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">人才争夺战也反映了科技巨头们的竞争意图。例如，Meta的大语言模型Llama 4因推理和编程能力表现不佳而受到批评，这促使Meta在AI招聘和投入上紧急转向。为此，Meta投资148亿美元入股Scale AI，并邀请其创始人Alexandr Wang加入，组建“超级智能”团队。科技巨头之间的人才争夺战进一步升级。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">01 人才争夺战的起源和演进\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">“人才争夺战”这一概念并非最近才出现，它最早由麦肯锡公司在1997年的一份研究报告《人才争夺战》（The War for Talent）中提出。这份报告基于对企业高管的深度访谈，指出在知识经济时代，人才是企业最稀缺、最关键的资源。麦肯锡的核心结论是：企业间的竞争，实质上是争夺人才的竞争。谁能赢得、培养并留住高潜力人才，谁就能在未来占据优势。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">这一观点迅速引发了全球管理界的关注。许多企业开始重视人才战略，将“人才吸引力”和“雇主品牌”提升为组织竞争力的重要组成部分，人才争夺战成为企业战略讨论中的高频词语。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">人才争夺战的概念还促使企业将招聘、晋升、培训、继任规划等要素系统集成到战略层面。此外，几乎所有咨询公司和智库的报告都指出，“未能吸引和留住顶尖人才”已成为全球CEO的首要关注问题，这一趋势也推动了高端人才薪酬水平的提升。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">20世纪90年代末到21世纪初，互联网经济迅速膨胀，网页设计师、程序员、和软件架构师等岗位变得炙手可热。初创公司通过提供高薪、期权和“联合创始人”头衔来吸引人才，市场上一度形成对明星工程师的狂热追捧。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">由于人才的薪资成本逐年上升，企业也加强了对人才的盘点和评估，例如将员工划分为A\u002FB\u002FC类，在高薪、期权、发展机会上显著偏向A类（明星）人才。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">然而，这种聚焦少数明星员工而忽略整体体系的方式，反而导致一些企业绩效下降。特别是当泡沫破裂后，企业开始反思过度投资和押注高端人才、过度英雄化个体而忽视组织支持的代价，并转向构建人才持续供给机制。企业开始从外部争抢人才转向内部培养，强调通过技能开发、岗位轮换、继任计划来建设人才梯队。许多优秀企业已将这一模式嵌入组织运行模式中。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">在接下来的近20年（2002—2019年）里，随着大数据、云计算、移动互联网的发展，新兴岗位如“数据科学家”“算法工程师”“流量增长经理”等再次成为企业争抢的热门资源。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">然而，在经历了新冠疫情和经济下行等不确定性后，企业更加重视自身的可持续发展，强调人才管理体系需与战略和业务需求相匹配，以及人才要与组织文化的契合。一些学者还提出了“按需供应人才”的理念，提倡根据企业发展阶段理性适配人才，同时加强组织整体能效，而非仅仅依靠一些外聘的高端员工。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">2022年以来，人才战争进入新的阶段。ChatGPT及大语言模型引爆AI热潮，使得AI科学家、自然语言工程师、机器学习工程师、和AI解决方案架构师等人才身价飙升。OpenAI、Anthropic、Google DeepMind、xAI等公司相继上演人才争夺战，而这一阶段人才争夺的本质，是行业巨头们在战略先发权和AI产业主导地位上的竞争。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">02 人才战争带来的管理弊端和争议\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">从过去数十年的历史看，尽管“人才战争”的概念激发了全球企业对人力资源管理的重视，甚至直接将核心人才管理提升到战略层面，但它也给企业带来了诸多管理弊端和风险。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">美国沃顿商学院的Peter Cappelli教授早在2008年就撰文提及，“人才战争”对于大多数企业来说，可能是个伪命题，甚至陷阱。他指出，很多企业所谓的人才短缺，往往是管理不善的结果。例如，企业设定了不切实际的招聘门槛，想雇用“即插即用”的员工；或者，企业在人才管理方面过于短视，对内部培训投入严重不足，过度依赖外部招聘，而非内部培养。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Cappelli教授敏锐地指出：“问题不在于劳动者缺乏技能，而在于雇主希望市场直接提供完美人才，却不愿花时间进行人才匹配和技能培训。”\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">从劳动经济学的视角来看，这是一种市场失灵现象：企业要求“完美匹配”，却不愿投资于匹配过程。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">劳动经济学领域的“搜索与匹配理论”模型（又称Diamond–Mortensen–Pissarides模型），是研究失业、职位空缺与劳动力匹配机制的一个核心理论框架。该模型指出，人岗匹配需要雇主和求职者双方投入资源以优化匹配过程，而企业常常试图“绕过”这一成本，以至于后期要付出人岗不匹配、员工离职以致组织涣散的代价。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">当然，这个现象也在很大程度上受到财务会计制度的局限。企业虽然宣称“人才是战略资源”，但实际上，人才被视为可变成本，培训费用被计为支出（expense），而非像机器或软件那样作为资产投资（asset）。因此，企业在面临竞争时，更倾向于“外部买入”，而非“内部育人”。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">这种短期导向弥漫人力资源管理的各个模块，而非仅在人才招聘环节。例如，企业在面对短期利润压力时，倾向于裁员、外包和削减员工培训。这些短期导向的举措通常会带来更高的员工流动率、文化不适配和绩效问题，为企业长期发展埋下隐患。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">此外，还需要了解为何劳动力市场的匹配需要额外的成本：这还是要从人的属性谈起。因为人类员工的效能供给具有黏性：员工不可能快速跨行业转岗或习得新技能，也无法立刻适应组织的社会环境；同时，工作能力和素质固然重要，但是人们的职业选择还受到价值观、身份认同、意义感等非金钱因素影响，这些都不能靠单纯的“能力—薪资”匹配所涵盖。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">因此，用“出高价买最牛的人”来解决企业的问题，常常是得不偿失且不可持续的。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">03 FoMO情绪和中小企业的焦虑\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">在AI时代，一些中小企业和初创公司出于FoMO（Fear of Missing Out，即害怕错过）情绪，盲目跟随大公司高薪抢人，这往往会导致薪酬体系失衡、人才流动加剧、组织文化紊乱等问题。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">FoMO是一种常见的心理情绪，指人们担心自己错过了他人正在经历的好机会、重要信息或有价值的活动，从而产生焦虑、急迫或从众行为。FoMO最初用于描述社交媒体时代人们对朋友圈动态的持续关注，但如今已被广泛应用于消费、投资、招聘、战略决策等领域。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">历史总是不断重演，无论是2000年前后的互联网泡沫时期，还是当下的AI热潮，这两个时代的人才争夺战呈现出高度相似的特征。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">首先，竞争态势让企业认为技术人才严重供不应求。为了抢人，企业竞相开出高薪、股权，还配上创始人亲邀、满足个性化需求、学术自由承诺等“定制化”激励措施。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">其次，人才的议价能力空前强大，顶尖员工的身价被大幅抬高。从当年的明星程序员到今天的AI研究员，有些核心人才年薪甚至高达数百万美元。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">此外，这两个时期都伴随着频繁的跳槽和创业潮，许多人才借此寻求更高期权或自主发展机会。资本市场也同步表现出极大热情，风投机构在强烈的FoMO情绪驱动下，争相为潜力团队提供高额融资，进一步推高了人才价值和市场竞争的激烈程度。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">在AI时代的人才大战中，中小企业尤其容易陷入由FoMO情绪驱动的决策误区。面对大型科技公司高薪争抢AI人才、频繁投资热点技术的举动，中小企业常担心自己错过风口或抢不到人，从而盲目跟进，以至于面临多重风险。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">首先，为了抢夺明星AI人才，小企业不得不打破原有的薪酬体系，造成内部员工公平感受损，严重时甚至引发原有核心成员离职。例如，明星员工的薪酬远高于创始团队成员的薪资水平，这会直接打击团队士气。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">其次，这类“抢来的人”往往受困于组织文化适配问题，高薪引入的明星人才未必能适应初创企业资源紧张、节奏快速的工作环境，最终难以发挥预期价值。此外，小企业资源有限，若过度押注在少数关键个体身上，可能忽视团队建设、产品开发与协同创新，形成对个人的依赖。一旦其离职或表现不佳，企业整体战略就会受挫。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">更严重的是，这种在FoMO情绪驱动下的“抢人”策略常常让企业偏离原本聚焦产品与客户的战略节奏，被迫卷入大企业设定的高成本竞争中，导致资金紧张、节奏紊乱，甚至陷入“招了人却无项目可做”的困境。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">最后，高薪抢人往往换来的是高流动率，这些人也更容易被下一家出价更高的公司挖走。小企业因缺乏薪资优势和文化吸附力，难以留住人才，最终只能为他人做嫁衣裳。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">在高度不确定的环境里，FoMO是常见的情绪性决策冲动。为了缓解高管层的FoMO情绪，中小企业需建立多层次的缓解机制。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">在高层认知和决策层面，可引入冷静期制度、反对意见机制或事前推演，避免冲动决策。管理团队应就企业战略和发展阶段达成人才规划的共识，不被外部动态牵着走，在引入高端人才的时候，要不断自问和评估：“我们是否真的需要？”，谨防落入“别人都在做，我们不做就落后”的陷阱。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">面向中层和基层管理者，则应强化围绕产品、客户与企业文化的决策原则。同时，组织应面向员工沟通战略和人才策略，坚定目标，缓解焦虑，使员工和管理层理解“不追风口”并非落后，而是资源配置的理性选择。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">核心管理者们，特别是创始人，如果有FoMO倾向，亦可通过认知行为训练、自我记录冲动行为与结果，提升情绪自觉性与长期判断力。如此，创始人和企业高管们在战略认知、组织能力和制度文化层面多管齐下，即可跳出“害怕错过”的短视心理陷阱，转向稳健、适配、自主的战略和人才布局。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">04 从人才争夺走向组织体系\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">在AI时代，行业巨头之间以千万年薪挖角顶尖研究员的现象虽引人注目，但这更多是少数企业在争夺极少数“超级个体”时采取的策略性动作，并非普遍适用的人才管理模式。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">事实上，这类高价挖角行为虽然在媒体上曝光度极高，却并不代表AI人才市场的主流现象。对大多数企业而言，这种做法不仅难以效仿，而且弊大于利：它抬高了整体市场对AI人才的薪资预期，却未必能带来相应的生产力提升，还更容易引发内部薪酬结构混乱与文化失衡。缺乏相应资源与研发体系的支持，即便中小企业抢到人，也难以真正发挥其潜力。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">因此，高价挖角并非破解AI人才短缺的通用办法。企业需要从自身业务需求出发，注重内部人才发展与系统性能力建设，而非盲目跟风参与明星人才的竞价战。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">随着AI技术的不断发展，人才争夺战仍将持续，但企业的竞争力将不再仅仅体现在“抢人快”，而在于是否具备构建稳定、适配、可持续人才生态的组织能力。未来的人才战略，将从单一的“争夺”逻辑转向更加长期主义的“吸引与培育”模式。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">这一转向体现在三个方面：一是选才逻辑的改变，企业不再盲目依赖学历与经验，而是聚焦实际工作技能和学习潜力，拓展多元人才来源。二是雇主吸引力的提升，组织更重视文化认同与价值共鸣，通过强化雇主品牌，吸引愿意共同成长的人才。三是内部人才机制的完善，通过灵活的内部流动与岗位成长路径，减少对外高成本招聘的依赖，稳步打造可持续的人才梯队。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">同时，AI技术也将成为关键工具，帮助企业更精准地进行人才评估、匹配和潜力预测，推动个性化培养计划的实施，从而提升整体人才运营效率，构建更具适应性的组织能力。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">从历史经验看，真正具备长期主义精神的企业，不会将高薪挖人作为核心竞争策略，而是致力于打造系统性的组织能力和人才管理机制。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">例如，近期数据表明，在全球供应链不确定性增加、汽车行业竞争激烈的环境下，2024年度丰田汽车财务表现坚韧。从外部看，这得益于其营销策略的精准执行、汇率变动的有利影响、严格的成本控制以及费用管理的优化。从组织能力看，这也得益于丰田长期专注于员工技能培养、持续改善的文化以及领先的生产与管理体系。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">此外，微软在云时代的成功转型，也不是靠堆砌“明星科学家”，而是基于对内部人才的再培训、文化驱动与组织协同能力。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">美的集团的与时俱进，也并非依赖于引进外部高端人才，而是在于其长期坚持科技领先、数智驱动和全球经营的战略，在组织内部形成动态竞争、激励创新的土壤，并通过人才轮岗与系统培养机制来稳步构建人才梯队。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">这些企业的共同点在于：以技能和价值观匹配为核心选才标准，以内部成长驱动绩效提升，并通过稳定的组织文化形成强大的吸引力。相比之下，单靠高薪挖人只能带来短期资源聚集，却难以构筑真正可持续的竞争优势。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">真正的人才战略，从来不只是快一步，而是走得远。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F08\u002Fbef179b14fe8462999cc3dc7cf2cefbd\u002Ffae0e5f665a546be879a031b7723e668.webp\" width=\"941\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">教授简介\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">韩践博士是中欧国际工商学院管理学教授、中欧组织成长与人才发展研究中心主任、首席人力资源官（CHRO）课程-课程主任、总经理课程AMP-联席课程主任。她在美国康奈尔大学（Cornell University）获得博士学位。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">韩教授的专业领域主要聚焦于通过组织和人才管理提升组织有效性与可持续发展力。她的学术成果发表于诸多国内外领先学术期刊，并有多个教学案例获得国内外奖项。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(187, 187, 187);\">【新闻来源】\u003C\u002Fspan>\u003Cspan style=\"color: rgb(187, 187, 187); background-color: rgb(56, 56, 56); font-size: 14px;\">经济观察报 编辑| 李钰婷 \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.sohu.com\u002Fa\u002F927553789_177801\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(187, 187, 187);\">https:\u002F\u002Fwww.sohu.com\u002Fa\u002F927553789_177801\u003C\u002Fa>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(187, 187, 187);\">（本网转发此文章，旨在为读者提供更多的信息资讯，所涉内容不构成投资、消费建议。文章事实如有疑问，请与有关方核实，文章观点非本网观点，仅供读者参考。）\u003C\u002Fspan>\u003C\u002Fp>","","https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F08\u002Fbe58a08250e649a2b972e874a640bd4c\u002FAI领域.jpg","https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F08\u002Fthumbs\u002Fbe58a08250e649a2b972e874a640bd4c\u002FAI领域.jpg",0,1,228,"2025-08-26 21:31",2,false,{"id":17,"name":20,"enName":21},"芯位视野","Xinwei Vision","https:\u002F\u002Fxinwei-dev-test.oss-cn-shenzhen.aliyuncs.com\u002Fintelligent\u002Faudio%3Ab1e4728d-acbe-4a6d-a879-5a737fffa766%3A0.wav?Expires=1756259844&OSSAccessKeyId=LTAI5tNvY2RkKjZw4LLWsrPK&Signature=hPoMVBlKscDTiQtmYbYhvZSR%2FiY%3D",28563706,"b1e4728d-acbe-4a6d-a879-5a737fffa766","2025-08-26 21:12","Are the high salaries of AI stars a competitive advantage or a bubble?","\u003Cp>\u003Cstrong class=\"ql-lineHeight-1-75\" style=\"font-size: 18px; color: rgb(255, 153, 0);\">Do you know how high the annual salary of top AI talents is today? What kind of competitive intent does this reflect between companies? How will it affect corporate compensation strategies and performance? Professor Han Jian from China Europe International Business School, Director of the CHRO Program, analyzes the historical evolution of the talent war and its impact on enterprise management through the surface of the exorbitant salaries of top AI talents, and proposes more practical talent management suggestions from a long-term perspective.\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F08\u002F9cf81e258882419d9e665f351d67588e\u002F784d5e96ab384697b64f7c0a02b8a6fa.webp\" width=\"536\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">According to overseas media reports, tech giants like Meta and OpenAI are competing for top AI researchers with salaries in the millions of dollars. Recently, an employee at OpenAI left, causing concern among the company's senior management. Mark Chen, OpenAI's Chief Research Officer, criticized Meta for poaching employees during OpenAI's vacation period in an internal letter, saying, \"It feels like someone broke into our house and stole something.\" He also said that OpenAI is adjusting its compensation structure and reward system to retain talent.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Looking at salary data, the annual salary of senior AI scientists generally ranges from 3 million to 7 million USD, with some even exceeding 10 million USD, which is about a 50% increase compared to 2022.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The salary tracking website Levels.fyi shows that Meta's median salary for AI engineers is 560,000 USD, with the highest reaching over 3.5 million USD; OpenAI's median salary for engineers is 870,000 USD, with senior engineers earning up to 1.34 million USD; while the median salary for regular software engineers is 185,000 USD, with most people's salaries ranging from 130,000 to 360,000 USD, far lower than AI positions.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The talent war also reflects the competitive intentions of tech giants. For example, Meta's large language model Llama 4 has faced criticism for poor reasoning and programming capabilities, prompting Meta to urgently shift its AI recruitment and investment strategies. To this end, Meta invested 1.48 billion USD in Scale AI and invited its founder Alexandr Wang to join, forming a \"super intelligent\" team. The talent war between tech giants has further escalated.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">01 Origin and Evolution of the Talent War\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The concept of \"talent war\" did not emerge recently; it was first introduced by McKinsey in a 1997 research report titled \"The War for Talent.\" Based on in-depth interviews with corporate executives, the report pointed out that in the knowledge economy era, talent is the most scarce and critical resource for enterprises. The core conclusion of McKinsey was that the competition between enterprises is essentially a competition for talent. Who can win, cultivate, and retain high-potential talent will gain an advantage in the future.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">This view quickly attracted attention from the global management community. Many companies began to value talent strategy, elevating \"talent attractiveness\" and \"employer brand\" to important components of organizational competitiveness, making the talent war a frequently discussed term in corporate strategy discussions.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The concept of the talent war also prompted companies to systematically integrate elements such as recruitment, promotion, training, and succession planning into strategic levels. In addition, almost all consulting firms and think tanks' reports point out that \"the inability to attract and retain top talent\" has become the primary concern for global CEOs, and this trend has also driven the rise in high-end talent compensation levels.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In the late 1990s to early 21st century, the internet economy rapidly expanded, making positions such as web designers, programmers, and software architects highly sought after. Startups attracted talent by offering high salaries, stock options, and \"co-founder\" titles, leading to a frenzy of enthusiasm for star engineers in the market.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Due to the rising cost of talent salaries year by year, companies have also strengthened their talent inventory and assessment, such as categorizing employees into A\u002FB\u002FC groups, significantly favoring A-group (star) talents in terms of high salaries, stock options, and development opportunities.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">However, this approach focusing on a few star employees while ignoring the overall system has led to performance declines in some companies. Especially after the bubble burst, companies began to reflect on the costs of excessive investment and betting on high-end talent, overemphasizing individuals while neglecting organizational support, and shifted towards building a sustainable talent supply mechanism. Companies began to move from external talent acquisition to internal cultivation, emphasizing the construction of talent pipelines through skill development, job rotation, and succession planning. Many outstanding companies have already embedded this model into their organizational operations.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In the next nearly 20 years (2002-2019), with the development of big data, cloud computing, and mobile internet, emerging positions such as \"data scientists,\" \"algorithm engineers,\" and \"traffic growth managers\" again became hot resources for companies to compete for.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">However, after experiencing the uncertainty of the COVID-19 pandemic and economic downturn, companies have placed greater emphasis on their sustainable development, emphasizing that the talent management system should align with strategic and business needs, and that talent should match the organizational culture. Some scholars have also proposed the concept of \"on-demand talent supply,\" advocating for a rational matching of talent according to the development stage of the enterprise, while strengthening the overall efficiency of the organization, rather than relying solely on externally hired high-level employees.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Since 2022, the talent war has entered a new phase. The popularity of ChatGPT and large language models has caused the salaries of AI scientists, natural language engineers, machine learning engineers, and AI solution architects to soar. Companies such as OpenAI, Anthropic, Google DeepMind, and xAI have successively engaged in a talent war, and the essence of this phase of the talent war is the competition between industry giants for strategic first-mover advantages and dominance in the AI industry.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">02 Management Drawbacks and Controversies of the Talent War\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">From the history of the past several decades, although the concept of \"talent war\" has sparked global attention to human resource management in enterprises, and even directly elevated core talent management to a strategic level, it has also brought many management drawbacks and risks to enterprises.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Professor Peter Cappelli from the Wharton School of the University of Pennsylvania mentioned as early as 2008 that the \"talent war\" might be a pseudo-proposition, or even a trap, for most enterprises. He pointed out that the so-called talent shortage of many enterprises is often the result of poor management. For example, enterprises set unrealistic hiring criteria, wanting to hire \"plug-and-play\" employees; or, enterprises are too short-sighted in talent management, investing seriously insufficiently in internal training, relying heavily on external recruitment rather than internal cultivation.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Professor Cappelli keenly pointed out: \"The problem is not that workers lack skills, but that employers want the market to provide perfect talents directly without investing time in talent matching and training.\"\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">From the perspective of labor economics, this is a case of market failure: enterprises require \"perfect matches,\" yet they are unwilling to invest in the matching process.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The \"search and matching theory\" model (also known as the Diamond-Mortensen-Pissarides model) in labor economics is a core theoretical framework for studying unemployment, job vacancies, and labor matching mechanisms. This model points out that person-job matching requires both employers and job seekers to invest resources to optimize the matching process, while enterprises often try to \"bypass\" this cost, leading to later costs of person-job mismatch, employee turnover, and organizational disintegration.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Of course, this phenomenon is also largely limited by the financial accounting system. Although enterprises claim that \"talent is a strategic resource,\" in reality, talent is regarded as a variable cost, and training expenses are recorded as expenditures (expense), not as assets (asset) like machines or software. Therefore, when facing competition, enterprises tend to \"buy externally\" rather than \"cultivate internally.\"\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">This short-term orientation permeates various modules of human resource management, not just in the talent recruitment process. For example, when enterprises face short-term profit pressure, they tend to lay off, outsource, and cut employee training. These short-term-oriented measures usually lead to higher employee turnover rates, cultural misalignment, and performance issues, posing hidden dangers for long-term development.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In addition, it is also necessary to understand why labor market matching requires additional costs: this again comes down to the attributes of humans. Because human employees have sticky productivity: employees cannot quickly switch industries or acquire new skills, nor can they immediately adapt to the social environment of the organization; at the same time, work ability and quality are important, but people's career choices are also influenced by non-monetary factors such as values, identity, and meaning, which cannot be covered by a simple \"ability-salary\" match.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Therefore, using \"high prices to buy the best people\" to solve enterprise problems is often costly and unsustainable.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">03 FoMO Emotion and Anxiety of Small and Medium Enterprises\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In the AI era, some small and medium-sized enterprises and startups, driven by FoMO (Fear of Missing Out) emotions, blindly follow large companies in offering high salaries to attract talent, which often leads to imbalanced compensation systems, increased talent mobility, and organizational cultural chaos.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">FoMO is a common psychological emotion, referring to people's anxiety, urgency, or herd behavior due to the fear of missing out on good opportunities, important information, or valuable activities that others are experiencing. FoMO was initially used to describe the continuous attention people pay to their social media circles, but it has now been widely applied in areas such as consumption, investment, recruitment, and strategic decision-making.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">History always repeats itself, whether in the Internet bubble period around the year 2000 or the current AI boom, the talent wars in these two eras show highly similar characteristics.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">First, the competitive situation makes companies believe that technical talents are severely in short supply. To compete for talent, companies are offering high salaries, equity, and customized incentives such as direct invitations from founders, meeting personalized needs, and promises of academic freedom.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Second, the bargaining power of talent is unprecedentedly strong, and the value of top employees has been greatly increased. From star programmers of the past to today's AI researchers, some key talents earn annual salaries of millions of dollars.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In addition, both periods are accompanied by frequent job-hopping and entrepreneurial waves, with many talents taking this opportunity to seek higher equity or independent development opportunities. The capital market has also shown great enthusiasm, with venture capital firms providing high financing to potential teams driven by strong FoMO emotions, further increasing the value of talent and the intensity of the competition.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In the talent war of the AI era, small and medium-sized enterprises are especially prone to decision-making mistakes driven by FoMO emotions. Faced with large technology companies' high-salary efforts to attract AI talent and frequent investments in hot technologies, small and medium-sized enterprises often worry about missing the风口 or failing to attract talent, thus blindly following, leading to multiple risks.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">First, in order to compete for star AI talents, small companies have to break their original compensation systems, causing damage to internal employees' sense of fairness, and in severe cases, even leading to the departure of original core members. For example, the salary of star employees is much higher than that of the founding team members, which directly undermines team morale.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Second, such \"hired people\" often face issues with organizational culture adaptation. High-salary recruited star talents may not be able to adapt to the resource-constrained and fast-paced working environment of start-ups, ultimately failing to deliver expected value. Additionally, small companies have limited resources, and if they overly rely on a few key individuals, they may neglect team building, product development, and collaborative innovation, creating dependency on individuals. If these individuals leave or perform poorly, the company's overall strategy will suffer.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">More seriously, the \"hiring\" strategy driven by FoMO emotions often causes companies to deviate from their original focus on products and customers, forcing them to get involved in high-cost competition set by large companies, leading to financial strain, chaotic rhythms, and even the dilemma of \"hiring people but having no projects to do.\"\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Finally, high-salary hiring often results in high turnover, and these people are also more likely to be lured away by companies offering higher salaries. Small companies, lacking salary advantages and cultural appeal, struggle to retain talent, ultimately serving as a means for others to benefit.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In a highly uncertain environment, FoMO is a common emotional decision-making impulse. To alleviate the FoMO emotions of senior executives, small and medium-sized enterprises need to establish multi-level mitigation mechanisms.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">At the senior cognitive and decision-making level, introducing a cooling-off system, an opposing opinion mechanism, or a pre-mortem analysis can prevent impulsive decisions. Management teams should reach consensus on the company's strategy and development stage regarding talent planning, avoiding being driven by external dynamics. When introducing high-end talent, they should constantly ask and evaluate: \"Do we really need it?\" to avoid falling into the trap of \"everyone else is doing it, so we must do it too.\"\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">For middle and grassroots managers, it is necessary to strengthen decision-making principles centered on products, customers, and corporate culture. At the same time, the organization should communicate its strategy and talent strategy to employees, firm up goals, and alleviate anxiety, so that employees and management understand that \"not chasing the wind\" is not backward, but a rational choice of resource allocation.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Core managers, especially founders, if they have FoMO tendencies, can also improve their emotional awareness and long-term judgment through cognitive behavioral training, self-recorded impulsive behaviors and results. In this way, founders and enterprise executives can break out of the short-sighted psychological trap of \"fear of missing out\" and shift towards a stable, suitable, and autonomous strategy and talent layout.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">04 From Talent Acquisition to Organizational Systems\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In the AI era, the phenomenon of industry giants digging up top researchers with millions of annual salaries is eye-catching, but this is more of a strategic move taken by a few companies to compete for a few \"super individuals,\" not a universally applicable talent management model.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In fact, such high-price poaching actions, although highly exposed in the media, do not represent the mainstream phenomenon of the AI talent market. For most enterprises, this approach is not only difficult to emulate but also has more disadvantages than benefits: it raises the overall salary expectations for AI talent in the market, but may not bring corresponding productivity improvements, and is more likely to cause internal salary structure confusion and cultural imbalance. Without the corresponding resources and R&D system support, even if small and medium-sized enterprises manage to attract talent, they may still fail to fully leverage their potential.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Therefore, high-price poaching is not a universal solution to the shortage of AI talent. Enterprises need to focus on internal talent development and system performance capability building based on their own business needs, rather than blindly following the bidding war for star talents.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">As AI technology continues to develop, the talent war will continue, but enterprise competitiveness will no longer be reflected merely in \"how fast you can poach,\" but in whether they have the organizational capabilities to build a stable, suitable, and sustainable talent ecosystem. Future talent strategies will shift from a single \"competition\" logic to a more long-term \"attract and cultivate\" model.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">This shift is reflected in three aspects: first, a change in the selection logic, where enterprises no longer blindly rely on degrees and experience, but focus on actual work skills and learning potential, expanding diverse sources of talent. Second, the enhancement of employer attractiveness, where organizations place greater emphasis on cultural alignment and value resonance, attracting talents willing to grow together through strengthening employer branding. Third, the improvement of internal talent mechanisms, reducing dependence on expensive external recruitment by implementing flexible internal mobility and career growth paths, steadily building a sustainable talent pipeline.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">At the same time, AI technology will also become a key tool to help enterprises conduct more accurate talent evaluation, matching, and potential prediction, promoting the implementation of personalized training programs, thereby improving overall talent operation efficiency and building more adaptable organizational capabilities.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">From historical experience, truly long-term-oriented enterprises do not make high-salary poaching a core competitive strategy, but instead focus on building systematic organizational capabilities and talent management mechanisms.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">For example, recent data shows that Toyota's financial performance remained resilient in 2024, despite increased global supply chain uncertainties and intense competition in the automotive industry. Externally, this was due to the precise execution of its marketing strategy, the favorable impact of exchange rate fluctuations, strict cost control, and optimized expense management. Internally, this was also due to Toyota's long-term focus on employee skill development, a culture of continuous improvement, and leading production and management systems.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In addition, Microsoft's successful transformation in the cloud era was not achieved by piling up \"star scientists,\" but rather by retraining internal talent, driving culture, and organizational collaboration capabilities.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Midea Group's progressiveness is not based on importing external high-level talents, but rather on its long-term commitment to technological leadership, digital intelligence drive, and global operations, creating a dynamic competition and innovation-inducing environment within the organization, and building a talent pipeline through talent rotation and systematic training mechanisms.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The common point of these enterprises lies in: selecting talent based on skill and value alignment, driving performance improvement through internal growth, and forming a strong attraction through a stable organizational culture. In contrast, relying solely on high salaries to poach talent can only bring short-term resource concentration, but cannot build a truly sustainable competitive advantage.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">True talent strategy is never just about moving faster, but about going further.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F08\u002Fbef179b14fe8462999cc3dc7cf2cefbd\u002Ffae0e5f665a546be879a031b7723e668.webp\" width=\"941\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cstrong style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Professor Introduction\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Dr. Han Jian is a professor of management at China Europe International Business School, Director of the Center for Organizational Growth and Talent Development at China Europe International Business School, Director of the CHRO Program, and Co-Director of the AMP Program. She earned her doctorate from Cornell University in the United States.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Her professional fields mainly focus on enhancing organizational effectiveness and sustainable development through organizational and talent management. Her academic achievements have been published in many domestic and foreign leading academic journals, and she has received awards for multiple teaching cases both domestically and internationally.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(187, 187, 187);\">[News Source]\u003C\u002Fspan>\u003Cspan style=\"color: rgb(187, 187, 187); background-color: rgb(56, 56, 56); font-size: 14px;\">Economic Observer, Editor | Li Yuting \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fwww.sohu.com\u002Fa\u002F927553789_177801\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(187, 187, 187);\">https:\u002F\u002Fwww.sohu.com\u002Fa\u002F927553789_177801\u003C\u002Fa>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(187, 187, 187);\">（This article is reprinted by this website to provide readers with more information, and the content does not constitute investment or consumer advice. If there are any doubts about the facts of the article, please verify with the relevant parties. The views of the article are not the views of this website, and are for reference only.）\u003C\u002Fspan>\u003C\u002Fp>","https:\u002F\u002Fxinwei-dev-test.oss-cn-shenzhen.aliyuncs.com\u002Fintelligent\u002Faudio%3A93b4bafb-1bbf-474d-9489-8817a7a2a171%3A0.wav?Expires=1774838485&OSSAccessKeyId=LTAI5tNvY2RkKjZw4LLWsrPK&Signature=c0QwsEROSaHf1IfIC2l33eTfEv8%3D","93b4bafb-1bbf-474d-9489-8817a7a2a171",17206612]