人机协作 - 北美华人人力资源协会

人机协作

全球劳动力报告深度解读：AI时代最大的挑战，不是裁员，而是员工的工作已经改变，组织却还没有跟上人工智能究竟会取代多少工作？这是过去两年企业管理者、人力资源负责人和员工反复讨论的问题。但随着AI真正进入企业运营，一个更加现实、也更加复杂的问题正在浮现：即使员工没有失去工作，他们原来的工作是否已经发生了根本变化？如果岗位职责、技能要求和工作方式都在改变，企业现有的人才管理体系是否还能够支持员工持续成长？ 2026年10月5日，企业管理软件公司Workday发布最新《Global Workforce Report: The Adaptability Advantage》（全球劳动力报告：适应力优势）。报告基于Workday平台劳动力数据及全球员工和企业决策者调查，试图回答AI正在如何改变就业市场、岗位结构、招聘、员工技能和职业发展。报告最重要的一组数据是：40%的企业决策者预计AI将提高现有员工的生产力，34%预计工作内容或岗位结构发生变化，33%预计出现新的岗位或技能，而预计员工总数减少的比例为28%。这些数据并不意味着AI不会导致裁员，也不能据此断言未来就业规模一定保持稳定。事实上，受访企业对AI的预期可能同时包含生产力提升、岗位调整和人员减少。但至少在当前阶段，企业对AI的期待已经明显超越简单的人力成本削减，开始转向如何重新组织工作、配置技能和提高业务效率。对于北美华人人力资源管理者而言，这份报告揭示了一个值得高度重视的趋势：AI转型正在从技术部署进入组织重构阶段。真正考验HR专业能力的，不再只是帮助员工使用AI，而是帮助企业重新定义工作，并让员工在持续变化中找到自己的职业发展方向。一、员工没有换工作，但他们的工作已经变了 Workday副总裁Phil Willburn在报告中提出了一个非常具有代表性的观察：“Employees may not be changing jobs, but their jobs are changing around them.” 员工可能没有更换工作，但他们周围的工作正在发生变化。这句话揭示了当前劳动力市场一个容易被忽视的现象。从招聘、晋升和员工总数等传统指标来看，全球就业市场整体似乎处于相对停滞状态。企业没有大规模扩张招聘，内部晋升增长缓慢，员工流动也不像过去那样活跃。但是，企业内部发生的变化远比这些数字呈现的更加剧烈。 Workday调查发现，38%的员工在过去一年经历了企业重组或组织结构调整，32%表示企业存在空缺岗位长期不补充人员的情况，30%观察到新岗位被创造，23%的受访者所在组织经历了裁员或岗位冗余削减。也就是说，即使企业的员工总数没有明显变化，组织内部的工作分配、岗位职责和人员结构仍然可能经历大幅调整。例如，过去一名Recruiter可能需要大量时间筛选简历、安排面试和联系候选人。随着AI招聘工具投入使用，这些重复性工作可以部分自动化，Recruiter可能因此需要将更多精力投入人才评估、业务沟通和招聘策略。同样，对于HRBP而言，过去大量时间可能花在整理员工数据、生成报告和回答常规人事问题上；未来，这些任务可能越来越多地由AI辅助完成，而HRBP需要承担更多组织诊断、管理者支持和人才决策工作。这些变化不一定伴随着岗位名称的改变，却可能实质性改变岗位的价值和能力要求。从NACSHR的专业视角看，企业过去主要按照Job Title管理人才，但AI时代越来越需要从Task和Skills两个维度重新理解岗位。岗位是否存在是一回事，岗位内部究竟由哪些任务构成、哪些任务可以自动化、哪些能力必须由人承担，则是另一回事。未来企业HR不能只关注Headcount Planning，还必须开始关注Work Redesign。二、AI技能需求发生分化：会使用AI，正在成为基础能力 Workday报告中最值得关注的另一组数据，是基础AI技能需求下降25%，而应用型AI技能需求增长51%。根据Workday对554家企业岗位招聘数据的分析，从2025年9月至2026年7月，企业对AI技能的要求正在发生显著变化。基础AI技能，例如日常使用AI工具、Prompting和Copilot，相关岗位需求在2026年1月达到高峰后下降了25%。与此同时，Applied AI Skills持续增长，整体增幅达到51%。这些技能主要涉及Machine Learning、Workflow Automation、Large Language Models以及AI Engineering等实际应用能力。这里需要特别强调：基础AI技能在招聘信息中的需求下降，并不代表企业不再需要员工使用AI，也不意味着这些技能失去了实际价值。更合理的理解是，随着AI工具普及，基础使用能力正在逐渐成为许多岗位的默认要求，而不再总是需要被单独强调的专业技能。这与过去办公软件普及的过程有相似之处。当越来越多的知识工作者都能够使用Excel、PowerPoint或者其他办公系统时，企业真正重视的就不再只是员工会不会操作软件，而是能否利用工具解决实际业务问题。 AI也正在经历类似的变化。对于企业HR而言，这意味着培训策略需要升级。过去一年，很多企业的AI培训主要围绕如何使用ChatGPT、Microsoft Copilot或其他生成式AI工具展开。这些培训有其价值，但如果长期停留在工具介绍和Prompt技巧层面，就很难真正推动组织生产力变化。未来更有价值的学习发展体系，应当围绕实际业务场景展开。例如，招聘团队如何利用AI改善候选人匹配质量，HR Operations如何重新设计员工服务流程，Compensation团队如何提升数据分析能力，HRBP如何借助AI辅助组织诊断与劳动力规划。企业需要建立的不仅是AI Literacy，更是将AI转化为实际工作成果的能力。三、员工并不缺乏适应意愿，真正不足的是企业支持人力资源管理者在推动AI转型时，经常会面临一个问题：员工是否愿意接受变化？ Workday的调查结果提供了一个值得重新思考的答案。 65%的员工表示，如果未来岗位所需技能发生变化，他们有信心进行适应；79%的员工表示，自己知道未来取得成功需要哪些技能。但是，只有66%的员工认为，雇主真正帮助他们发展这些技能。这13个百分点的差距，反映出员工技能认知与组织发展支持之间存在明显落差。员工可能已经意识到AI正在改变工作，也愿意接受新技能培训，但他们未必知道企业究竟希望自己如何改变，更不确定完成学习之后能否获得新的发展机会。这种矛盾在AI重度使用者中更加明显。在几乎所有工作中使用AI的员工中，62%认为AI可能降低自己当前技能的市场价值，但同时有76%认为AI会创造新的职业发展机会。这意味着员工对AI的态度并不是简单的支持或反对，而是同时存在期待与担忧。他们看到了效率提升的机会，也意识到自己过去积累的某些专业能力可能正在发生贬值。对于北美华人HR而言，这一点尤其值得重视。许多企业拥有不同文化背景、不同年龄层和不同专业经历的员工，各类员工对AI转型的理解、接受程度和职业焦虑可能存在差异。对于跨国经营、团队分布在不同地区的企业，这种沟通与支持的复杂性还可能进一步增加。 HR不能仅仅通过一封邮件宣布公司开始采用AI，也不能把员工参加培训的次数当作转型成功的证明。企业更需要回答员工几个具体问题：我的岗位未来会如何变化？哪些任务将由AI承担？哪些技能仍然具有长期价值？公司是否提供学习资源？如果我掌握了新技能，是否能够看到明确的内部发展机会？ AI转型过程中，员工最需要的可能不是更多关于AI的口号，而是更清晰的职业发展预期。四、内部人才流动正在停滞，传统职业发展模式面临挑战 Workday报告显示，57%的企业内部横向岗位流动同比下降。全球员工的12个月滚动晋升率约为8.1%，整体基本没有明显增长。更值得注意的是员工为何无法实现内部流动。在尝试申请内部岗位的员工中，22%认为内部选拔程序不够公平，22%遇到岗位被暂停、撤销或改变的情况，17%表示经理不支持内部转岗。而在过去一年没有申请内部岗位的员工中，44%表示对当前岗位满意，但27%表示没有看到有吸引力的内部机会。这组数据揭示的问题可能比单纯的晋升率下降更加深刻。过去企业内部的职业发展路径相对清晰：员工通过积累经验、完成绩效目标、承担更多职责，逐步获得晋升或转岗机会。但随着AI改变工作内容、组织结构持续调整、部分企业控制新增岗位，传统依赖职位数量增长和管理层级扩张的职业发展模式正在受到挑战。员工可能持续学习新技能，却发现原来熟悉的晋升路径不再存在；企业可能不断要求员工提升适应能力，却没有同步建立新的岗位转换机制。如果企业不能解决这一矛盾，员工对学习和转型的积极性就可能逐渐下降。 Workday自身的案例提供了一种可能的解决方向。公司部署Fetch——HiredScore AI for Talent Mobility的一项能力——利用AI帮助招聘团队将内部人才与开放岗位进行匹配。部署后，Workday报告其内部人才流动同比增长45%。这一案例说明，内部人才发展不仅取决于有没有岗位，还取决于企业能否识别内部人才的能力，并让相关机会被员工和招聘团队看见。对于企业HR而言，这意味着Talent Marketplace、Skills Intelligence和Internal Mobility不应被视为几个相互独立的系统。真正有效的人才管理体系，应当将员工现有能力、岗位技能要求、学习发展资源和内部机会连接起来。尤其对于一些希望控制招聘成本、同时需要持续推进AI转型的企业，重新发现和配置已有员工的能力，可能比一味依靠外部招聘更加重要。五、AI让招聘申请量暴增，却没有真正解决人才匹配问题 AI正在改变招聘市场的另一端。 Workday调查发现，84%的求职者已经在求职过程中使用AI，其中47%利用AI撰写或修改简历、求职信等材料，34%利用AI准备面试或评估。在使用AI求职的人群中，42%表示AI增加了自己申请的岗位数量。随着AI降低申请成本，企业收到的申请数量明显增加。从2025年7月至2026年7月，企业每发出一个Offer对应的申请数量中位数，从58份增加到69份。其中，Technology & Media行业从147份增加到207份，同比增长40.4%；Financial Services行业从77份增加到98份，同比增长27.2%。但是，招聘申请量显著增加，并没有带来同等程度的招聘效率提升。报告显示，整体岗位填补周期仍然维持在约60天。 34%的招聘经理表示，岗位难以填补的主要原因是候选人缺乏所需技能；33%认为候选人对薪酬、工作地点或灵活性的期望与岗位要求不一致。这反映出一个值得HR关注的新问题：AI正在让候选人更容易申请工作，但并没有让企业更容易找到真正合适的人。对于Recruiter而言，未来的挑战可能不再是如何获得更多简历，而是如何从大量申请中准确识别真正具备岗位能力、学习潜力和业务适配度的人才。 Workday workplace psychologist Dr. Liz Pavese在报告中指出，传统招聘系统和思维模式过度依赖职位名称及固定候选人画像，招聘经理需要进一步识别候选人的Transferable Skills和Adjacent Capabilities。这意味着招聘评估需要逐步超越简历关键词和过去的Job Title，更多关注候选人的实际能力、问题解决方式和可迁移技能。对于北美华人HR，尤其是服务于科技企业、专业服务机构和跨国企业的招聘团队，这一变化具有直接的实践意义。当越来越多候选人使用AI优化简历和求职表达时，企业更应该提升结构化面试、工作样本评估和技能验证的质量。同时，在使用AI招聘工具时，也需要关注候选人隐私、评估公平性，以及所在地适用的就业和自动化决策相关要求，避免把效率提升建立在新的合规风险之上。六、员工暂时留下，不代表他们真正愿意留下当前劳动力市场还有一个容易让企业产生误判的现象：员工流动相对缓慢，但员工对组织的认同感并不一定同步提高。 Workday数据显示，典型企业的两年员工留任率从2024年7月的73.3%下降至2026年7月的70.5%。与此同时，27%的员工表示未来12个月可能寻找外部工作机会，而报告中的年度自愿离职率约为16%。这说明一部分员工虽然尚未离职，但已经开始考虑外部发展机会。特别是在招聘需求相对疲软、外部岗位竞争加剧的环境中，员工可能因为经济压力、职业风险或者缺乏合适机会而暂时留在现有企业。这种留任并不能自动等同于员工满意度或组织忠诚度提高。 Workday进一步发现，只有59%的员工认为雇主真正关心自己这个人，58%认为影响员工的组织变化得到了公平处理。在员工成长体验方面，Career Path的积极评价比例仅为63%，明显低于Mentoring的81%和Learning的79%。这些结果非常值得企业HR警惕。企业可能提供了培训课程，也建立了导师机制，但员工依然看不到自己未来能够走向哪里。这就解释了为什么单纯增加培训预算或者学习资源，未必能够解决员工参与度和留任问题。员工真正需要的，不只是学习机会，而是学习与未来职业发展的连接。对于正在经历组织调整、岗位重构或AI转型的企业，透明沟通、公平的人员决策和清晰的职业发展预期，可能比单纯强调企业文化更加重要。 NACSHR认为，HR管理者尤其需要关注那些“没有离职、绩效尚可，但对未来发展缺乏信心”的员工。这类风险往往不会立即反映在Turnover指标中，却可能逐渐影响员工主动性、知识共享、创新意愿和组织信任。七、大型企业收缩与中小企业增长并存，北美人才市场需要重新观察 Workday报告还呈现了另一个重要变化：不同规模企业的就业增长正在明显分化。 2026年上半年，企业总体员工规模增长接近零，但大型企业和中小企业的表现存在较大差异。在Workday研究样本中，拥有100,000名以上员工的超大型企业贡献了约74%的净员工人数下降，但仅占样本员工总数的26%。相比之下，较小规模企业仍然表现出更明显的增长动力。按照报告中的Headcount Trajectory Index，Emerging/SMB达到58.4%，Midmarket为51.0%，Enterprise为48.9%，Large Enterprise为44.3%，30,000人以上的Majors仅为42.8%。这些数据反映的是Workday客户样本内不同规模企业的人员变化趋势，不能直接代表整个美国或加拿大劳动力市场。但它提示企业，不同规模公司的招聘需求与人才管理重点，可能正呈现明显分化。大型企业可能更加关注组织效率、AI投资回报和内部人才重新配置，而中小型成长企业可能仍然面临业务扩张、人才招聘和管理能力建设的压力。对于北美华人HR而言，这也意味着人才管理策略必须与企业发展阶段相匹配。大型跨国企业可能需要更加成熟的Skills Framework、Talent Marketplace和Workforce Planning能力；处于增长阶段的中小企业，则可能更需要灵活的招聘体系、跨职能人才培养和高效率的HR运营支持。尤其对于在北美持续发展业务的华人创业企业和跨国企业，AI应用可以成为提高组织效率的重要机会，但前提是企业能够明确哪些工作真正适合自动化，哪些岗位需要重新设计，以及哪些关键人才能力必须持续投入。八、NACSHR观察：AI时代，HR正在从人员管理走向工作设计如果将Workday报告中的数据放在一起分析，可以发现一个更加深层的趋势：AI正在改变企业人力资源管理的基本逻辑。过去，HR系统主要围绕员工和岗位展开。招聘负责把人带进组织，绩效管理评价员工表现，学习发展帮助员工提升技能，人才管理决定晋升与继任，薪酬福利则围绕岗位和员工关系设计。这些模块虽然相互关联，但在不少企业中仍然是相对独立运作的。然而，AI正在打破这种边界。当岗位中的部分任务由AI完成时，Job Description就需要调整；当工作内容发生变化时，Skills Framework需要更新；当员工掌握新的能力时，企业需要重新评估内部岗位匹配；当AI提高团队产能时，绩效目标和管理方式也可能需要改变。这些变化最终会影响招聘、培训、绩效、薪酬、组织结构和员工关系。因此，AI时代的人力资源转型不应该被简单理解为“给HR增加一些AI工具”。更重要的是重新建立Work、Skills、People和Technology之间的关系。从NACSHR的角度看，未来企业HR的专业价值，可能越来越体现在四个方面。首先，是能够理解业务和岗位如何被AI改变，而不是仅仅根据管理层提出的人员需求执行招聘。HR需要参与岗位任务分析、组织结构讨论和工作流程优化。其次，是能够识别企业未来真正需要的能力，并把技能要求转化为员工可以理解的发展路径。技能体系不能只是用于招聘筛选，更应该成为内部培养和人才配置的基础。第三，是能够帮助管理者处理组织变化中的人际关系和信任问题。AI可以生成岗位分析和培训建议，却不能自动建立员工对管理者的信任，也无法替代企业对公平性和员工体验的责任。第四，是能够利用数据改善人才决策。企业需要将传统Headcount、Turnover和Time to Fill等指标，与内部人才流动、技能差距、岗位变化和员工职业发展体验结合起来，而不是孤立地观察某一个数字。真正有竞争力的HR组织，将不只是管理企业现有的人力资源，而是能够持续帮助企业重新配置人与工作的关系。九、北美华人HR可以从哪些具体行动开始？对于正在制定2027年人才战略的企业，NACSHR建议将AI转型从抽象讨论转化为可以执行的管理议题。第一步，重新审视关键岗位。企业不需要一开始就重构所有Job Description，可以优先选择招聘、客户服务、财务、人力资源运营、市场营销等AI影响较明显的职能，分析现有岗位的任务构成，识别哪些工作可以自动化、哪些需要人工审核，以及哪些职责可能因此发生变化。第二步，开展技能差距分析。不要只问员工是否会使用AI，而要根据真实业务流程，判断员工需要哪些AI工具应用能力、数据分析能力、流程设计能力和专业判断能力。对于现有员工，应重点识别可以通过培训和实际项目获得的新能力。第三步，将培训与内部机会连接。如果企业希望员工持续Reskill，就应当尽可能提供明确的岗位发展方向。对于无法立即提供晋升的企业，也可以通过跨部门项目、横向发展、岗位轮换和新的专业职责，为员工建立成长空间。第四步，让Manager成为转型的重要参与者。企业应当鼓励管理者定期与员工讨论岗位变化、未来技能需求和职业发展，而不是只在年度绩效评估时讨论目标完成情况。对于涉及AI的组织调整，还应明确经理在员工沟通、公平评价和培训支持方面的责任。第五步，建立更合理的AI转型衡量指标。 AI工具使用率和培训完成率可以作为过程指标，但不应成为衡量转型成功的唯一依据。企业还应关注实际工作效率、员工技能提升、内部流动机会、岗位匹配质量、员工信任和业务结果。对于资源有限的中小企业，可以从一两个关键职能开始试点，不必追求一次性建设复杂的人才管理平台。对于组织规模较大、业务覆盖多个国家或地区的企业，则应当逐步建立跨职能、跨地区的岗位与技能治理机制，同时注意不同司法辖区在员工数据、招聘决策和劳动关系方面的要求。需要指出的是，以上建议是NACSHR基于报告提出的企业管理实践方向，并非Workday报告已经验证有效性的统一实施方案。企业仍需根据自身业务结构、员工规模和管理成熟度进行调整。十、结语：AI时代真正的竞争优势，是组织持续适应变化的能力 Workday将这份报告命名为《The Adaptability Advantage》，其核心含义不只是要求员工学习新技能，而是强调企业需要建立能够持续适应变化的组织能力。在AI持续进入企业的过程中，一些传统任务可能减少，一些岗位可能重新组合，新的技能和职业机会也可能不断出现。对于员工而言，这意味着过去依靠一套专业技能长期维持职业竞争力的模式正在受到挑战。但对于企业而言，挑战同样巨大。如果企业不断要求员工提高效率，却无法解释岗位未来的发展方向；如果企业持续投入AI系统，却没有同步调整工作流程和管理机制；如果员工努力学习新技能，却看不到组织内部的发展机会，那么AI技术带来的生产力潜力就可能无法充分转化为长期组织能力。值得注意的是，Workday报告并未证明AI已经全面减少裁员，也没有证明AI必然提升企业就业规模。它真正揭示的是，在就业总体增长相对平缓的背景下，工作内容、技能需求和员工职业预期正在持续变化。而这种变化可能比单纯的岗位增减更加深刻。对北美华人HR而言，未来的专业竞争力也将越来越取决于能否深入理解业务，参与组织设计，推动人才转型，并在效率提升与员工发展之间建立合理平衡。企业需要的不只是能够执行招聘、薪酬和员工关系工作的HR，更是能够帮助管理层理解未来工作模式、支持员工适应变化，并共同建设高绩效组织的人力资源领导者。 AI时代最值得企业警惕的，或许不是某些岗位正在消失，而是员工的工作已经发生改变，企业的人才管理制度却仍然停留在过去。这也给所有HR管理者留下了一个值得深入讨论的问题：当企业开始用AI重新定义工作时，我们是否已经准备好重新定义人力资源管理本身？关于NACSHR NACSHR（北美华人人力资源协会）致力于连接北美华人人力资源专业人士、企业管理者及行业合作伙伴，推动人力资源领域的专业交流、实践分享与跨行业合作，持续关注AI、组织转型、人才管理、劳动法规及未来工作的发展趋势。官方网站：https://www.nacshr.org 资料来源与研究说明 Workday, Inc.，《Global Workforce Report: The Adaptability Advantage》，October 2026。本文主要参考完整22页报告，涵盖岗位变化、招聘趋势、AI技能、内部人才流动、员工留任及企业规模差异等内容。 Workday / PR Newswire，《Workday Global Workforce Report: AI Is Rewriting Jobs More Than It's Cutting Them》，October 5, 2026。官方新闻稿：https://www.prnewswire.com/news-releases/workday-global-workforce-report-ai-is-rewriting-jobs-more-than-its-cutting-them-302898076.html 研究方法说明： Workday的Global Workforce Reporting结合Workday Human Capital Management、Workday Peakon Employee Sentiment及Workday Recruiting相关数据，涵盖12个主要行业、5种企业规模及19个国家，并使用不同的样本面板进行分析。两项补充调查分别为2026年9月的Q3 Global Workforce Survey（N=6,001，其中决策者相关问题约1,780人），以及2026年8月的AI@Work Survey（N=5,944）。调查覆盖美国、英国、加拿大、澳大利亚、法国和德国。部分指标为新增或暂定指标，报告明确要求将观察结果视为描述性趋势，而非直接因果证据。本文由NACSHR北美华人人力资源协会根据Workday官方研究报告及新闻稿整理、分析并撰写。文中数据来自原始研究，行业判断及管理建议为NACSHR基于报告作出的独立专业解读，不代表Workday官方立场。

人机协作
2026年10月06日
人机协作

精彩回顾：2026 NACSHR北美华人人力资源年度论坛硅谷举行：AI重构工作与组织，判断力成为新的稀缺能力硅谷，2026年9月26日——2026 NACSHR 北美华人人力资源年度论坛（2026 NACSHR Annual Conference）在硅谷举行。50余位来自硅谷、多伦多、芝加哥、休斯顿、洛杉矶及美国东部等地的企业 HR 负责人、企业管理者、科技从业者和专业服务领域专家齐聚现场，围绕 AI 时代的组织转型、工作方式与人才画像、HRBP 角色变化、全球化与跨文化管理、北美华人 HR 职业发展、移民政策、员工福利与企业风险等议题展开了一整天的交流与讨论。论坛得到了赞助合作伙伴 BIPO 与 Ji Mobility Law 的支持，为北美华人 HR 的专业交流、行业连接与知识分享提供了重要助力。如果用一句话总结本届论坛，其核心可以归纳为： AI 超速发展的时代，真正发生的并不只是工具和技能的升级，而是在重新定义工作、岗位、组织、人机分工、HRBP 角色、人才标准、全球化管理与激励机制；当越来越多执行交给 AI，人最稀缺、也最有价值的能力，正在变成判断力。这也构成了贯穿全天讨论的两个关键词：重构（Redesign）与判断力（Human Judgment）。从HR Tech升级走向工作与组织的重构论坛首先从更长的产业周期审视 AI 正在给 HR 和组织带来的变化。长期在HR科技领域的观察者Gawain 以《十年全球 HR 科技趋势与 AI 时代的人力资源挑战》为主题，从过去十余年的 HR Tech 产业数据、融资并购及技术演进出发提出，过去的软件主要帮助 HR 将招聘、绩效、薪酬等流程数字化，而生成式 AI 与 Agent 已开始直接参与甚至执行工作任务。这意味着，企业接下来面对的问题不再只是“如何使用 AI”，而是需要重新回答：什么工作应该继续由人完成，哪些任务可以交给 AI，哪些判断必须由人承担。他同时指出，当前 AI 对个人能力与工作效率的提升已经十分明显，但如何利用 AI 改善组织、重构工作与流程，仍是全球企业共同探索的核心难题。AI 的演进速度正在进一步加快：从微软一直推动的Co-pilot副驾驶目前已经变成了Auto-pilot自动驾驶，AI从辅助到给结果，也是这180天的事。这一变化也意味着，HR 需要把关注点从个人 AI 技能进一步延伸到工作与组织的重新设计。引发HR同仁的深度思考。 2026 NACSHR Conference Chair Bijun Zhang 随后以《When Code Gets Cheap, the Org Chart Breaks》为主题，以 Anthropic 为案例讨论 AI-native 企业如何重新设计劳动分工，并进一步将这一变化延伸到 HR Function。她提出，当 AI 大幅降低代码、内容和执行工作的生产成本后，组织真正的瓶颈正在从“把事情做出来”转向 Judgment——包括验证、审查、取舍、品位、安全与责任判断。新的 Human + AI 分工逻辑因此可以概括为：Humans hold judgment, AI holds throughput。这种变化并不会停留在技术团队。Bijun 进一步提出，随着大量 transactional HR work 被自动化或增强，HR 的时间将更多从事务交付转向 strategic judgment，传统由 COE、HRBP 和 Shared Services 构成的 Three-Pillar Model 也可能被重新设计。未来 HR 可能进一步走向以统一 People Data 与 AI Platform 为底座、以不同 Product Pods 和 Flow-to-Work Teams 为组织方式的新模式，并形成 People Strategist、People Scientist 和 People Technologist 等新的角色分工。CHRO 的角色也可能进一步演变为 Enterprise Workforce Architect，负责设计 Human + AI 如何共同组成企业未来的 workforce。这也为全天讨论奠定了一个重要命题：AI 越能执行，人越需要判断；真正需要改变的，不只是工具，而是工作与组织本身。全球化竞争加速，技术平台与本地能力缺一不可来自 BIPO 的 North America Account Director、Canada Country Manager David Tan 以 “From Local to Global: How BIPO's AI Powers North American Companies Abroad” 为主题，讨论企业进入全球市场过程中面临的人才、Payroll、合规与本地化挑战。作为本届论坛的赞助合作伙伴，BIPO 在分享中指出，市场增长压力、全球人才竞争、客户本地化需求以及更快的竞争周期，正在推动企业加速全球扩张。与此同时，Worker Classification、Payroll、税务、福利、劳动法规以及文化差异，也让全球 HR 管理的复杂度快速上升。 David Tan 提出，将统一的技术平台、AI 能力和本地专业团队结合起来，可以帮助企业降低进入不同国家和地区时的运营与合规复杂度。这也反映出一个更广泛的变化：对于全球 HR 而言，AI 不仅是效率工具，也正在逐步成为跨国家、跨系统和跨规则环境下的组织基础设施。 AI时代的组织转型：判断力、人性与激励重新成为核心上午的「AI时代组织转型」圆桌由来自 Meta AI Labs 的 HRBP Tina 主持，前 Paraform VP of Engineering、前 TikTok 产品与工程负责人陈扬，NextCurve Intelligence 创始合伙人春夏，以及来自 Fireworks 的 Member of Technical Staff 乔健参与讨论。三位嘉宾开场分别用 Reset、Reboot 和“人性与激励” 概括自己对 AI 时代的理解。这三个关键词也几乎定下了整场讨论的基调：AI 带来的变化并不只是技术变化，最终仍然要回到人的能力、组织结构和激励机制。陈扬提出，AI 正在明显压缩 develop 的时间，而 design、QA 和判断所占的比重反而在上升。未来人才之间真正拉开差距的，可能不再只是执行速度，而是能否独立思考、做出判断，以及是否具备对结果质量的 “taste”。由此形成了现场极具代表性的一个观点： Judgment is the new output——判断力正在成为新的生产力。圆桌进一步讨论到，未来三年值得持续投资的能力，不只是某一项 AI 技能，而是判断力，以及跨越传统职业边界解决问题的勇气。当岗位边界逐渐松动，未来的人才越来越可能围绕问题工作，而不是严格围绕 Job Description 工作。乔健则提出，面对 AI 焦虑，与其持续讨论“AI 会不会取代自己”，不如把问题具体化，从一项真实工作开始使用 AI。与此同时，他也提醒，AI 的 productivity 可以快速提升，但人的认知能力、注意力和心理承载能力并不会同步增长。Mental Health、Human Touch、意义感和组织节奏，可能因此从传统员工体验议题进一步上升为 AI 时代的重要组织议题。春夏则从组织跃迁与激励机制出发提出，一个组织真正实现变化，仍然离不开三个基础条件：一号位的认知、工作流的沉淀，以及符合人性的激励机制。随着 Agent 进入工作场景，下一代组织可能逐步从单纯的“人管理人”转变为 Humans + Agents 的混合组织。人和 Agent 如何分工、Agent 如何评价、设计和管理 Agent 的人如何被考核，都将成为新的组织设计与激励问题。从年度续保走向持续福利与风险管理企业成本和风险管理同样是本届论坛的重要议题。来自 NACSHR 的 California Licensed Insurance Broker Annie Huang 以《2027美国企业保险新周期：从员工健康福利到企业风险保障，HR该如何提前布局？》为主题，分享美国员工福利与企业保险市场正在发生的变化。分享指出，随着医疗成本持续上涨，中小企业的员工福利管理已经不能停留在临近 Renewal 时“最后几周比价格”的传统方式，而需要提前90至120天开始更新员工参保数据、比较保险市场、规划企业补贴机制，并提前进行员工沟通。讨论还从 Medical Benefits 延伸到 Workers’ Compensation、EPLI、Cyber Insurance、E&O、General Liability 等企业风险场景。对于 HR 而言，员工福利、用工风险和企业保险正在变得更加紧密，福利管理也正在从一次年度采购逐渐转向持续规划与管理。美国移民政策频变，HR需要学会管理不确定性来自 Ji Mobility Law 的合伙人律师 Jacky（Jiaqi）Ji 以《移民政策频变，HR如何调整预期》为主题，梳理了近期美国高技能人才和国际员工用工环境中的多项变化，包括 H-1B、F-1、CPT、OPT、PERM、H-4 EAD，以及企业裁员与 H-1B 审查之间可能产生的新关联。 Jacky 的分享特别强调了一点：在移民政策频繁变化的环境中，HR 首先需要区分已经生效的规则、受到法院限制的政策，以及仍在规则制定或诉讼过程中的变化，而不能把所有政策消息都当作已经落地的规定。以备受关注的 H-1B 10万美元费用为例，白宫在2026年9月18日延长了相关 proclamation，但此前联邦地区法院已裁定该费用违法，第一巡回上诉法院在7月拒绝暂停该裁定，因此截至论坛举行时，收费要求仍受到法院裁决的限制，相关法律争议尚未结束。 Jacky 也谈到 F-1 Duration of Status（D/S）规则的变化。原计划于9月15日生效的新规在生效前一天被联邦法院暂缓实施，因此截至论坛当天仍未正式生效。对于企业 HR 而言，更值得关注的是移民政策正在与 Workforce Planning 更紧密地交叉。9月18日发布的 H-1B Executive Order 明确要求相关政府部门在审查过程中考虑雇主过去一年是否进行过裁员，或是否计划裁减与 H-1B 岗位类似的美国员工。这意味着，未来 HR、Hiring Manager 和移民律师之间的协作需要进一步前置。移民问题不能只在 Offer 发出或签证即将到期时处理，而需要更早进入 Headcount Planning、Layoff Planning、人才保留和岗位设计。 Jacky 还结合企业日常场景讨论了 H-1B 抽签政策如何向员工解释、CPT 用工如何评估、O-1 中的雇主责任与 Agent 模式，以及 L-1 是否能够在部分场景下成为 H-1B 之外的人才流动路径。这一环节进一步说明，在政策高度不确定的环境中，HR 的专业价值并不是给员工一个看似确定的答案，而是理解规则所处的阶段，评估风险，并帮助企业和员工形成合理预期。中美出海：本地HR正在从执行者转向战略桥梁来自 Freewind Technology Corporation 的 VP of HR & Admin Alice Tian 以《中美出海，本土HR的挑战及跨文化管理》为主题，讨论全球化企业在北美经营过程中经常遇到的管理矛盾。 Alice Tian 指出，总部往往希望将国内已经验证过的管理经验复制到海外，但当地法律、劳动关系、薪酬福利体系、工作文化和员工期待可能完全不同。本地 HR 因此经常同时面对总部和当地员工两个方向的沟通压力。她认为，Local HR 不应只是政策的 Enforcer，而需要成为企业内部的 Strategic Bridge 和 Cross-Cultural Interpreter。面对总部，HR 要学会使用成本、风险、数据和业务语言解释本地现实，在提出“No”的同时提供可以落地的替代方案；面对本地员工，则需要通过透明沟通、清晰边界和对当地文化的尊重建立信任。其分享进一步提出 Glocal（Globalization + Localization）的管理思路：总部需要明确战略、合规和核心预算等“红线”，而更多日常管理与本地政策，则应给予当地团队足够的授权和调整空间。 AI时代工作方式和人才画像：人才标准也在被重新定义下午的「AI时代工作方式和人才画像」圆桌，由来自 Luma Research Lab 的 HRBP & Recruiting Lead Linna Dai 主持。参与讨论的嘉宾包括来自 Weee 的 HR Director Felicity Yang、来自 Zoom 的 Data Scientist Ying Lu（ex-Google），以及来自 Databricks 的 TPM Ethan Guo（曾任 GitLab Director of Infra TPM）。圆桌围绕 AI 时代的工作方式、人才画像、岗位变化、人才标准、招聘与人才选拔，以及人与 AI 的协作模式展开。随着信息搜索、内容生成、代码、分析和部分流程执行越来越容易被 AI 完成，企业的人才问题正在发生变化：过去更多是在判断“这个人是否具备某项技能”，未来则需要进一步判断“这个人是否能够定义问题、判断结果、快速学习，并有效利用 AI 完成工作”。因此，AI 时代的人才标准正在更多地指向判断能力、学习速度、复杂问题解决能力、跨职能协作能力以及 Human + AI Collaboration。传统以固定经验、技能清单和标准 JD 为中心的人才选拔方式，也需要重新被审视。 HRBP的第一次转型，是HRBP自己先改变来自 ASML BL Apps Division 的 Head of Global HR Cynthia Gao 以《HRBP：从AI时代的解毒师到助产士》为主题，讨论 AI 时代 HRBP 角色的变化。她提出，HRBP 的转型首先需要从 HRBP 自己开始。过去的 HRBP 容易停留在观察问题、等待需求、依赖零散经验和维护既有流程，而新的工作方式应该利用 AI 扩大观察范围，将 surveys、cases、workflow、talent data 和 employee feedback 等信息转化为可以被验证和讨论的共同证据。她将这一转型路径概括为：See Earlier. Solve Faster. Prove More Value. 即更早发现问题、更快推动解决，并真正用结果证明 HR 的业务价值。 Cynthia Gao 最后提出了一个具体的30天行动框架：Detox One Barrier. Illuminate One Roadblock. Deliver One Visible Impact. AI 对 HRBP 最大的价值，不是简单增加一个新的工具，而是推动 HRBP 从被动接受问题，走向主动诊断问题、推动解决方案并证明业务影响。北美华人HR的职业发展：从专业能力走向Leadership与影响力年度压轴圆桌「北美华人HR的职业发展」，将论坛从 AI、组织和人才重新拉回到 HR 自身的职业成长。现场圆桌由来自 Silergy 的 HR Director Mindy Gao 主持，Head of HR Jane Liang、来自 Avia Games 的 Head of HR - US Tan Huangfu，以及 Alice Tian 和 Cynthia Gao 共同参与讨论。嘉宾围绕北美华人 HR 的职业成长、Leadership、职业突破、影响力建设、跨文化管理和未来发展机会展开交流。对于北美华人 HR 而言，专业知识仍然是职业发展的基础，但当职业进入更高阶段，真正决定能否进一步突破的，往往是能否理解 Business、能否在跨文化环境中建立信任、是否敢于表达专业判断，以及能否从“完成自己的工作”进一步走向“影响组织做出更好的决定”。 AI 的发展反而让这些能力更加突出。当越来越多执行性工作被技术加速以后，Leadership、影响力、沟通、判断力和跨文化理解的重要性不会下降，而会进一步上升。最后一位嘉宾，是AI 论坛最后设置了一个特别环节——“今天最后一位嘉宾，是AI”。不同于传统论坛以主持人总结结束，NACSHR 邀请 AI 作为当天最后一位“嘉宾”参与实时对话。AI 基于当天嘉宾分享的 PPT、现场议题以及 HR Tech、组织和人才管理等专业背景，回应主持人的现场提问，并对全天讨论进行总结。在最后的交流中，一个贯穿全天的关键词再次被提及： Judgment。因为当越来越多的信息搜集、内容生成和执行性工作可以由 AI 完成以后，真正决定最终结果质量的，是人能否提出正确的问题、辨别答案、理解复杂情境，并对最终决策承担责任。从重构到判断力：2026 NACSHR年度论坛留下的核心命题回看全天，从 HR Tech、AI-native Organization、Human + AI Workforce，到全球化、本地 HR、人才画像、HRBP、职业发展、移民政策和员工福利，不同议题最终都指向了同一个变化： AI 正在从“一个新的工作工具”，进入工作和组织的底层结构。未来 HR 面对的问题，也不再只是应该购买什么软件、员工应该学习什么 AI 技能，而是需要进一步回答：什么工作仍然应该由人完成，什么任务应该交给 AI，人与 AI 如何分工，什么样的人应该被招聘和晋升，组织应该如何重新定义绩效、激励和责任。在这一轮重构中，当执行越来越容易被复制和扩展，Human Judgment——人的判断力——正在成为更加稀缺的能力。因此，如果要用两个词概括 2026 NACSHR 北美华人人力资源年度论坛，就是：重构（Redesign） × 判断力（Human Judgment）。如果用一句话总结： AI 超速发展的时代，真正发生的并不只是工具和技能的升级，而是在重新定义工作、岗位、组织、人机分工、HRBP 角色、人才标准、全球化管理与激励机制；当越来越多执行交给 AI，人最稀缺、也最有价值的能力，正在变成判断力。 NACSHR 希望通过持续的专业论坛、线下交流和同行社群，让北美华人 HR 不仅看到变化，也能够在变化发生的过程中建立新的专业能力、判断力和同行连接。 Stay Together, Stay Powerful. 连接华人 HR，赋能华人职场。 NACSHR 特别感谢本届论坛赞助合作伙伴 BIPO 与 Ji Mobility Law 的支持，也感谢所有演讲嘉宾、圆桌嘉宾、合作伙伴、志愿者及参会者的共同参与。正是来自行业伙伴与 HR 社群的持续支持，让更多专业观点、真实经验与同行连接得以在线下发生。下一站：2027年1月2日周六，NACSHR 洛杉矶新年论坛欢迎您 https://nacshr.org/Public/html/LA/2027.html NACSHR 北美华人人力资源协会 Website：www.nacshr.org Email：nacshr818@gmail.com WeChat：hinacshr

人机协作
2026年09月28日
人机协作

UKG《2026 工作场所三大超级趋势》深度解读：AI、人才生态与赋能时代的组织重塑未来三年企业必须面对的关键变化：AI 加速落地、人才生态系统兴起、以及从员工投入感走向“赋能时代”。报告指出，尽管 78% 的企业已经使用 AI，但 74% 尚未真正获得价值，关键不在技术，而在组织文化、透明沟通与技能差距。全球人才短缺持续恶化，让企业必须建立灵活的人才生态，包括全职、合同工、gig 人才与 AI agents 的协作模式。同时，敬业度已无法支撑组织绩效，高信任、赋能型文化将成为核心竞争力。未来的赢家，将是那些既能用好 AI，又能激发员工潜力的组织。在一个不断被技术与人口结构加速重塑的时代，工作的本质正在悄然改变。企业面临的不仅是数字化带来的流程革新，更是对组织结构、人才模型、管理方式与文化基础的全面挑战。UKG 在《Workplace Evolution: Megatrends Defining 2026 and Beyond》中给出的三大巨趋势——以人为本的 AI、人才生态系统的崛起、以及员工赋能时代的到来——并不是简单的流行话题，而是未来三到五年影响组织持续竞争力的关键支点。本篇深度解读旨在帮助 HR 与业务领导者理解这些趋势的底层逻辑，从而更具前瞻性地重构组织能力。一、AI 的价值不是技术本身，而是“以人为本”的组织设计过去两年的生成式 AI 大热，使得企业纷纷投入大量预算采买工具、建设模型，但 UKG 的数据显示，**尽管 78% 的组织至少在一个业务领域使用了 AI，却有高达 74% 尚未看到可衡量的业务回报。**这与其说是技术问题，不如说是组织心态与适配方式的问题。 AI 的真正价值不在于自动化，而在于释放组织的人类创造力。当重复性的行政事务被系统接管，当手册查询、福利理解、排班与可用性管理不再消耗大量精力，员工便能把时间与认知投入到更具意义的沟通、创新与复杂决策中。然而，要实现这一目标，组织必须跨越两个核心障碍：其一是员工对 AI 的不安情绪，其二是技能差距导致的“会用但不敢用”“敢用却不会用”。报告显示，75% 的前线员工愿意让 AI 处理某些任务，但只有 38% 真的使用 AI，原因在于组织很少提供明确的目标、培训与安全感。尤其对于担心被取代的前线员工而言，透明沟通比任何技术部署都更关键。企业需要说明“为什么用 AI、AI 能做什么、不能做什么”，让员工看到 AI 是赋能工具，而不是削减劳动力的信号。 AI 的时代已经到来，但 AI 真正的竞争力属于那些愿意重新设计人机协作方式、并把员工视为核心主体而非配角的组织。二、人才短缺时代的答案不是加快招聘，而是构建“人才生态系统” 全球人才短缺已成为不可逆现实。UKG 援引 ManpowerGroup、制造业与零售业数据指出：74% 的企业找不到所需技能人才，90% 的制造企业因人力不足影响利润，零售行业同样面临巨大压力。然而，企业若依旧把人力规划等同于“填补岗位”，将愈发难以应对波动的市场与不断扩张的技能差距。UKG 提出的关键词是 “人才生态系统”，意味着组织不再仅依赖全职员工，而是可以同时调动：全职与兼职员工合同工、临时工 gig 灵活用工内部流动人才 AI 劳动力（AI agents）未来的组织将不再以岗位结构为核心，而是围绕“技能 × 任务”的动态组合方式运作。企业首先要做的不是招聘，而是盘点现有人才：谁具备可迁移的技能？谁能通过短期培训承担更高价值的工作？哪些任务适合交给 AI 或合约人才完成？这种“去岗位化思维”正在成为组织敏捷性的核心。然而挑战在于，多数企业尚未具备这种能力——**32% 的 HR 没有追踪员工技能的系统，57% 的 HR 没有内部人才 marketplace 工具。**这意味着企业内部大量潜力被浪费，甚至导致员工因为看不到成长路径而离开。人才生态系统的构建不仅提高效率，也是对抗人才荒的关键策略。组织必须从“招聘驱动”转向“技能驱动”，让人才在组织内部流动，而不是不断流失。三、从“投入感”走向“赋能时代”：真正提升绩效的不是 engagement，而是 enablement 过去十年，员工敬业度（engagement）几乎成为 HR 的 KPI，但现实是：敬业度不升反降。Gallup 的数据显示，2024 年全球敬业度下降至 21%，并造成约 4380 亿美元的生产损失。UKG 指出，造成这一趋势的根源在于组织文化的不信任、管理方式的控制性，以及员工缺乏自主权与资源。因此，报告提出一个更具变革性的方向：员工赋能（Enablement）。赋能并不是“员工开心就好”，而是让员工：具备完成工作所需的资源拥有决策空间能够掌握信息感受到信任拥有成长与贡献机会在组织文化中，当控制减少、透明度增加、心理安全感提升时，员工才真正能够发挥最大价值。UKG 数据显示：**高信任文化可带来 42% 的额外投入（discretionary effort）。**这意味着赋能并非“软文化”，而是实实在在的绩效驱动因素。然而，目前仍有大量组织存在“双重文化”——**47% 的前线员工认为企业对高层与基层执行不同标准。**这正是导致投入感低迷与员工流失的关键原因之一。因此，赋能时代要求组织在制度、工具、沟通与文化上实现一致性，特别是为前线员工提供可访问的数字工具，让他们不再被排除在信息链之外。赋能不是 HR 的福利项目，而是战略能力。未来的组织竞争，不仅是技术与人才的竞争，更是文化与信任的竞争。四、中小企业（SMBs）更需要理解这些趋势，因为它们影响更直接、速度更快 UKG 在报告中专门为中小企业做了解读。相比大型企业，SMBs 的结构更简单、灵活性更高，因此也更容易从 AI、人才生态与赋能模式中获益或受损。 AI 可以成为 SMB 的“副驾驶”，自动化大量行政工作，让本就精简的团队把时间投入到高价值工作中。但这种价值要实现，必须让员工理解它、愿意用它并具备使用能力。人才生态系统对于 SMB 的意义则体现在成本敏感度上：通过灵活用工与技能透明化，可以避免过度招聘，保持组织弹性。而赋能机制更是提升员工留存与忠诚度的关键，在小团队里任何人的流失都可能带来直接损伤，因此“赋能＝韧性”。 SMBs 未来最重要的不是“规模”，而是“敏捷性”。而敏捷性来自技术支持、人才灵活性与文化信任三者共同作用。五、未来三年 HR 的关键任务：重建“技术×人才×文化”的组织能力 UKG 的结论是明确的：未来的工作不是被动变化，而是主动重塑。组织必须同时具备三种关键能力：第一，AI 增强能力（AI Augmentation）——让技术真正融入工作流，而不是停留在工具层面。第二，技能驱动的人才策略（Skills-based Workforce Strategy）——用技能替代岗位思维，实现内部流动与敏捷配置。第三，赋能型组织文化（Enablement Culture）——以信任、透明、自主为核心，实现从“管理劳动”到“激发潜力”的转变。未来不属于技术，而属于能把“人 × 技术 × 数据 × 文化”融合成新型组织能力的企业。正如 UKG 在报告结尾强调的：“工作正在被重塑，无论组织是否准备好。”那些主动构建未来能力的企业，将以更快速度适应变化、抵御波动，并在竞争中保持持续优势。

人机协作
2025年12月10日
人机协作

AI时代的招聘攻略： 2026年美国的五大招聘趋势 AI 已全面进入招聘流程，87% 的招聘团队和 67% 的候选人都在用AI，带来前所未有的效率与信息过载。劳动力市场继续分化，蓝领与医疗持续缺人，白领岗位需求疲软；AI技能岗位快速增长。候选人对雇主信任度下降，仅67%信任雇主，他们会通过社交媒体和AI“事实核查”企业文化。70% 的求职从Google开始，86% 通过社交平台查岗，招聘正在转向“搜索+社交”主导的精准营销模式。科技不是为了减少沟通，而是帮助HR把更多时间用于高质量的候选人互动。这些趋势将深刻影响2026年的招聘策略。新常态已至人才招聘团队正面临着一系列日益严峻的挑战：高利率、关税不确定性和更严格的移民政策共同带来了持续的经济压力，招聘步伐普遍放缓，而人工智能则已从前沿“炒作”迅速转变为日常“习惯”。这些因素在2026年将进一步加速，巩固了我们当前所处的“新常态”。但这并非危机，而是一个孕育创新方法的机遇。本文将深入探讨塑造未来一年招聘格局的五大关键趋势。 1. AI军备竞赛：效率与挑战并存人工智能已全面进入主流，深刻改变了招聘的攻守双方。数据显示，高达87%的人才招聘决策者和67%的求职者正在积极使用AI工具。招聘官利用AI撰写职位描述、总结简历和生成面试问题；而求职者则用它来研究公司、比较薪酬并为特定职位量身定制简历。这种双向应用带来了一个全新的挑战：招聘渠道中充斥着大量经由AI润色、内容高度相似的简历，这使得识别真正具备所述技能的合格候选人变得异常困难。这一局面不仅在技术供应商之间引发了一场提供更优筛选工具的“军备竞赛”，也促使雇主们迫切地需要采纳更先进的AI解决方案以保持竞争力。更具变革性的是，人工智能正在重塑求职者发现工作的方式。我们正见证“提示词搜索”（prompt-based searching）的兴起。想象一下，求职者不再是在谷歌上搜索“我附近的仓库工作”，而是向ChatGPT这样的工具输入：“我是一名42岁的仓库工人，正在克利夫兰寻找一份每周站立工作时间少于30小时的职位。我有叉车安全认证，并且只希望在周二到周六工作。”生成式AI将返回高度定制化的职位推荐。这种对话式的求职体验正成为新常态，促使雇主必须升级其招聘网站以适应这一趋势。 “人才招聘团队正面临双重挤压——人手减少，资金缩减，同时还要承受展示如何有效利用人工智能的巨大压力。” —— Matt Plummer，Appcast首席产品官 2. 劳动力市场分化：冰火两重天 2026年的劳动力市场将呈现出日益加剧的分化。整体就业增长放缓，失业率已攀升至4.3%，创下自2021年以来的新高。市场内部的差异尤为显著，这在很大程度上是由特定的经济政策驱动的：体力劳动岗位（“Standing-up” jobs）：熟练技工、农业、建筑业和医疗保健等岗位面临着持续的劳动力短缺。更严格的移民政策导致依赖外国出生工人的行业劳动力池萎缩，加剧了招聘困难。白领岗位（“Sitting-down” jobs）：市场营销、人力资源和专业服务等岗位的需求持续疲软。关税政策增加了商品生产行业的成本，抑制了消费者需求，从而导致相关领域的企业缩减招聘目标。在整体降温的市场中，医疗保健行业一直是就业增长的“主力军”，但其前景也面临不确定性。联邦医疗补助（Medicaid）的大幅削减可能威胁到数十万个直接和间接的医疗岗位。与此同时，一场围绕AI人才的激烈争夺战正在上演。与AI技能相关的职位发布量在过去18个月里翻了一倍多，薪酬也大幅飙升，成为冷却经济中的一个显著亮点。 “2026年的情况将与今年非常相似，但挑战会更加严峻。由于移民政策，招聘体力劳动者将变得更难；而对于白领岗位，需求低迷和招聘目标缩减的状况可能会持续。” —— Andrew Flowers，Appcast首席经济学家 3. 雇主品牌危机：信任跌至谷底求职者对雇主的信任度正在急剧下降。根据爱德曼（Edelman）的信任度调查报告，公众对雇主“做正确的事”的信任度在该研究的26年历史上首次出现下滑。普华永道（PwC）的调查数据也揭示了巨大的认知鸿沟：只有67%的员工信任他们的雇主，而高达86%的领导者却认为自己深受信任。如今的求职者对企业的宣传信息持高度怀疑态度，68%的人认为商界领袖会故意误导公众。他们利用AI和社交媒体来核实雇主的说法，并与员工的真实体验（如社交媒体上的帖子）进行比对。其结果是，“企业承诺”已失去效力。求职者，特别是Z世代，需要的是证明公司言行一致的“具体证据”，他们希望公司在气候变化、心理健康、多元化、公平与包容等重大社会议题上有明确的立场和行动。此外，由于对人工智能取代工作的担忧和普遍的经济不安全感，员工们更倾向于“抱紧工作”（job hugging），将职业稳定性放在首位。 “你不能只说‘我们关心你’。求职者辨别谎言的能力非常强，过度修饰的语言现在听起来就像空话。重要的是能够拿出证据，证明你言行一致。” —— Erika Boutain，Appcast雇主品牌策略师 4. 招聘即营销：在搜索与社交中触达人才招聘官必须主动去到求职者聚集的地方。数据显示，70%的求职搜索始于谷歌，而86%的求职者会在求职过程中使用社交媒体。这意味着招聘策略必须全面转向数字化平台，主要通过两种方式触达人才：社交广告：触达那些可能对合适机会持开放态度的被动求职者，在他们日常浏览信息流时建立品牌认知。付费搜索广告：精准定位那些正在积极寻找相关职位、意向明确的主动求职者。成功的关键在于由AI驱动的超个性化技术。这种技术摒弃了传统的“广撒网”模式，转而采用类似电子商务的精细化运营。它能够分析候选人的在线行为和社交媒体信号，预测他们可能感兴趣的职位类型以及薪酬、福利、灵活性等关键决策因素，最终实现像“Netflix风格的职位推荐引擎”那样的精准匹配。这不仅优化了广告支出，也显著提高了申请转化率。 “人工智能与行为定位的结合，正在帮助我们探索新的方式，将求职者与符合其兴趣的职位联系起来，并简化他们与工作机会的互动过程。” —— Alexandra Horwitt Anema，Appcast数字媒体总监 5. 回归人性化：用技术解放招聘官技术的最终目标不是取代人类，而是增强人类的能力。数据显示，72%的人才招聘领导者乐观地认为，AI将让他们能够更专注于工作中‘人性化’的一面；同时，78%的领导者相信AI工具将使他们更有效率。面对AI驱动下激增的申请量，理想的工作流程是：让AI处理海量的、重复性的任务，如简历初筛、候选人排序和面试安排。这使得招聘官能够解放出来，专注于更高价值的活动，例如深入评估候选人的实际能力、探讨文化契合度以及与顶尖人才建立稳固的关系。前瞻性的人才团队正在构建一种**“人工参与更少，但整体互动体验更佳”**的工作模式。这种人机协作不仅提高了效率，也为所有求职者（而不仅仅是最终被录用者）带来了更优质、更透明的体验。 “我们将加倍投入技术，以带回招聘中至关重要的人性化元素。” —— Matt Plummer，Appcast首席产品官结论：拥抱变革 2026年是人才招聘团队重新思考长期流程、重塑战略的一年。成功的关键在于平衡AI驱动的效率与定义卓越招聘所必需的人性化关怀。我们仍处于探索阶段，最好的策略是大胆试验、衡量一切，并支持那些被证明有价值的投入。那些保持好奇心并对变革持开放态度的人，将定义2026年及未来的招聘成功。最终，正如Appcast首席执行官Matt Molinari所指出的：“拥抱变革的人和公司将成为赢家。”

人机协作
2025年12月04日
人机协作

The best HR & People Analytics articles of July 2025 HR如何在AI时代掌握主动？David Green发布的7月《Data Driven HR Monthly》汇集全球顶尖报告与实践，聚焦“技能+任务”新范式、AI对员工体验与倦怠的双面影响，以及CHRO在企业AI战略中的领导地位。BCG数据显示，印度AI使用率达92%，但全球员工对AI培训满意度仅36%。Upwork报告揭示：高效AI用户更易疲惫离职。McKinsey与Gartner呼吁HR重构组织模型与人才规划体系。本期还探讨神经多元、NASA人才图谱与“Vibe Coding”等创新实践。 I always enjoy spending time in India, so I was delighted to arrive in Delhi yesterday ahead of People Matters Tech HR later this week. I’ll be delivering the opening keynote on how HR leaders can ace the next curve of change as well as leading a workshop on the science of better decisions. I’m looking forward to catching up with fellow speakers such as Jason Averbook (tip: subscribe to his Now to Next blog, if you don’t already), Pushkaraj Bidwai, Mukesh Jain, and Shefali Raias well as immersing myself in what is happening in the Indian HR tech scene. In this month’s edition of the Data Driven HR Monthly, which comes against the backdrop of CEOs flexing on the impact of AI on jobs, I’ve included new research from BCG and Upwork on AI at work, and the role of HR. Marc Effron is spot on here with his assessment that CHROs need to be leading the strategic conversation with the executive team on their desire to reduce costs through job reduction enabled by AI: “CHROs can lead this conversation through organization, operating model and job design, where we should be experts.” I expect plenty of discussion at Tech HR on this topic as well as the wider impact of AI on work, the workforce, and the workplace. One of the messages, I’ll look to get across in my keynote is: AI guides, but humans decide. We must prioritise the ‘H’ in HR. This edition of the Data Driven HR Monthly is sponsored by our friends at TechWolf Skills, Tasks, and Workforce Intelligence: Navigating the AI Transformation This month’s edition highlights an important conversation from the TechWolf Podcast, recorded live in New York, featuring Marc Steven Ramos, global learning leader with 25+ years’ global transformation experience with Google, Microsoft, Accenture, Novartis, Oracle, and Cornerstone, and Jeroen Van Hautte ?, CTO & Co-Founder of TechWolf. The discussion explores how task-based intelligence complements skills data to create a complete view of workforce capabilities, empowering organizations to navigate one of the largest business transformations in history: the AI-driven redefinition of work. Skills without context can be ambiguous. Tasks ground them in real work, and that’s where change, productivity, and AI come together — Marc Ramos Why This Matters Now: The pace of change in the workforce is unprecedented. Leading enterprises are already recognizing that workforce intelligence - the ability to understand, predict, and act on how work is changing in real time - is no longer optional. From skills to skills + tasks + jobs: Combining these data points allows organizations to connect individual capabilities to tangible outputs and outcomes. AI as a catalyst: AI is accelerating job evolution, making real-time visibility into tasks and skills essential for workforce planning and redeployment. Strategic urgency for boards: Workforce automation isn’t a distant trend — it is reshaping workforces today, creating pressure on executives to act on reskilling, redeployment, and workforce design at speed. To really understand a skill, you need to understand the context in which it’s applied — the tasks. And that’s where AI can add transformative clarity — Jeroen Van Hautte For HR leaders, this is an opportunity to lead. With skills and tasks as the foundation, HR is uniquely positioned to drive cultural alignment, manage change, and deliver on the board-level mandate to prepare workforces for the AI era. Listen to the Episode: ?️ Marc Ramos & Jeroen Van Hautte on Tasks, Skills & the Future of Work (TechWolf website summary) To sponsor an edition of the Data Driven HR Monthly, and share your brand with more than 145,000 Data Driven HR Monthly subscribers, send an email to dgreen@zandel.org. JULY ROAD REPORT Until flying to Delhi yesterday, as mentioned above for Tech HR India later this week, July had been a light month of travel other than a short trip to Switzerland to run an AI workshop with the HR leadership team of one of the companies that are part of the Insight222 People Analytics Program. For those interested, one of my speaking engagements from earlier this year, at the Wharton People Analytics Conference, is now available to view (see below). In the talk, I explore the critical role of data democratisation and adoption in driving workforce insights, enhancing decision-making, and scaling HR’s strategic impact. I also share best practices from our work and research at Insight222 for making people analytics accessible to leaders and employees alike, the challenges of adoption, and the key investments required to unlock the full potential of workforce data. Enjoy! Share the love! Enjoy reading the collection of resources for July and, if you do, please share some data driven HR love with your colleagues and networks. Thanks to the many of you who liked, shared and/or commented on June’s compendium. If you enjoy a weekly dose of curated learning (and the Digital HR Leaders podcast), the Insight222 newsletter: Digital HR Leaders newsletter is usually published every other Tuesday – subscribe here – and read the latest edition. HYBRID, GENERATIVE AI AND THE FUTURE OF WORK BCG - AI at Work: Momentum Builds, but Gaps Remain | JOHN BRAZIER AND NICK SOUTH - BCG’s AI at Work 2025 report: Four takeaways for HR leaders Companies are realizing that merely introducing AI tools into existing ways of working isn’t enough to unlock their full potential. The real magic happens—and value generated —when businesses go further and reshape their workflows end-to-end. BCG’s annual AI at work global survey of employees is packed full of insights and guidance for business and HR leaders looking to maximise value, adoption and employee experience with AI. The key takeaways include: (1) AI is now part of our daily work lives: 72% of respondents are regular AI users (although adoption amongst frontline employees has stalled at 51%). (2) Investment in training, leadership support and access to the right tools can break this ceiling: Yet only 36% of employees are satisfied with their AI training. (3) The Global South is showing higher adoption of AI. India leads the pack with 92% of regular users compared to the US (64%), UK (68%) and Japan (51%). (4) The next frontier: from adoption to value with end-to-end redesign. One-half of respondents say their company is starting to reshape processes. These companies also invest more in their people – and it pays off (see FIG 1). (5) AI agents are not widely deployed. Only 13% see agents integrated into broader workflows (see FIG 2). Kudos to the authors: Vinciane Beauchene, Sylvain Duranton, Nipun Kalra, and David Martin. For HR leaders, I also recommend reading John Brazier’s interview with BCG’s Nick South about the implications of the report’s findings for HR on the UNLEASH blog. FIG 1: The relationship between workflow redesign due to AI and investment in people (Source: BCG) FIG 2: Use of AI agents (Source: BCG) GABBY BURLACU AND KELLY MONAHAN - From Tools to Teammates: Navigating the New Human-AI Relationship Full time employees getting the most done with AI are also the most burned out, disengaged, and disconnected from their teams. In their study for the Upwork Research Institute, Gabriela (Gabby) Burlacu and Kelly Monahan, Ph.D. identify a crucial message for the future of work: while AI is undeniably boosting productivity – with a reported 40% jump for many workers – it's also creating a human paradox. Alarmingly, top AI performers are experiencing high burnout (88%) and are twice as likely to leave, often feeling disconnected from strategy and even trusting AI more than human colleagues (see FIG 3 and 4). The report offers three urgent calls to action for business leaders: (1) Redesign work for human-centered, AI-empowered talent and workflows, prioritising autonomy, trust and psychological safety. (2) Cultivate flexible and resilient talent ecosystems, combining full-time employees, freelancers, and AI capabilities to create agile, resilient, and high-performing teams. (3) Redefine AI strategies to focus on the end-to-end human experience, including new roles, norms, and governance. For HR leaders, these findings are a wake-up call. We must prioritise the relational side of AI, ensuring human connection, well-being, and purpose are augmented, not eroded. It's about preventing burnout in our most productive AI users, fostering alignment, and learning from agile models like freelancers to build a truly sustainable human-AI collaborative future. FIG 3: The human cost of AI productivity (Source: The Upwork Research Institute) FIG 4: The rise of human-like relationships with AI (Source: The Upwork Research Institute) COBUS GREYLING - Do AI Agents Substitute Human Workers — Or Enable Humans To Succeed In New Ways? | L. ELISA CELIS, LINGXIAO HUANG, AND NISHEETH K. VISHNOI - A Mathematical Framework for AI-Human Integration in Work AI Agents are good at tasks not jobs… In his article, Cobus Greyling provides an insightful and accessible analysis of a new study by Elisa Celis, Lingxiao Huang, and Nisheeth Vishnoi, which presents a mathematical framework that models jobs, workers, and worker-job fit, and introduces a novel decomposition of skills into decision-level and action-level subskills to reflect the complementary strengths of humans and GenAI. Greyling’s incisive analysis offers a helpful perspective for HR leaders navigating the future of work. His core message is clear: AI agents are fantastic at tasks, not entire jobs. They're not just substitutes, but powerful amplifiers of human capability, especially for less experienced workers, effectively compressing productivity gaps and fostering extraordinary collaboration. Here are four key learnings for HR: (1) Agentic AI Augments Human Potential: AI agents boost efficiency and performance, particularly for junior talent, by handling structured tasks and freeing humans for higher-order work. (2) Redefine Skills & Development: While AI takes on the mundane, HR must strategically ensure continuous skill development, focusing on uniquely human capabilities like judgment, creativity, and complex problem-solving. (3) Design for Human-AI Synergy: Organisational design must pivot to foster premium collaborations between humans and AI. It's about combining complementary strengths to achieve outcomes greater than the sum of the parts. (4) HR Leads Strategic Integration: Our role in HR is pivotal. We must orchestrate the strategic integration of agentic AI, balancing its efficiency gains with the imperative to preserve and nurture human ingenuity, driving both innovation and connection. FIG 5: Al for work: skill difficulty continuum (Source: Cobus Greyling) PEOPLE ANALYTICS KETAKI SODHI AND COLE NAPPER - Who Needs a “Human in the Loop” When AI Gives Itself Feedback Ketaki Sodhi, PhD, Program Owner for Agentic Listening and Analytics at Microsoft, and Cole Napper provide a fascinating perspective on the "human in the loop" concept for Generative AI, provocatively asking: which human, and how? This isn't just a technical question; it's where I/O Psychology and People Analytics come into their own. The article frames AI "evals"— the systems for assessing whether AI outputs are useful, accurate or aligned —as essentially performance management for Large Language Models. Just as we've wrestled with defining "good" in complex human knowledge work for decades, we now face the same challenge in building AI systems. In a world of infinite " " answers, AI evals demand the same nuance we apply to human systems: competency models, multi-rater input, calibration, and context. One of the key takeaways from Ketaki and Cole is that true success lies not in chasing perfect answers from AI, but in designing smart, human-informed systems. These are the systems that can discern between good, better, and what genuinely drives impact for your organisation. For people analytics leaders and I/O psychologists, this is a clarion call to leverage their deep expertise in human performance to shape the very fabric of our AI-driven future. FIG 6: Source – Ketaki Sodhi BEN BERRY - The future is built by everyone: What is Vibe Coding and why should People Analytics teams adopt it | ROSARIO GERMINO - From People Analytics to People Economics and Impact | ADRIAN PEREZ – GitLab People Analytics Team Handbook | DOMINIK TOMICEVIC - Can NASA’s People Graph and LLMs Revolutionize Workforce Planning? | MORGAN DEPENBUSCH - How to let color do the storytelling In each edition of the Data Driven HR Monthly, I feature a collection of articles by current and recent people analytics leaders. These are intended to act as a spur and inspiration to the field. Five are highlighted in this month’s edition: (1) In a particularly insightful piece, Ben Berry examines whether vibe coding, a product management practice of using AI tools to rapidly build functional prototypes to help turn rough ideas into working concepts, should be adopted in people analytics. (2) In her thoughtful article, Rosario Germino argues that to elevate people decisions to the same level of strategic investment as product or finance, we need a new way of thinking—and a new kind of function – People Economics and Impact, which she then breaks down into the why (see FIG 7 on the multi-dimensional aspect of informed decision making), what and how. (3) In a recent post, Adrian M. Pérez provides open source access to GitHub’s People Analytics Team Handbook, a rich resources covering areas such as (i) data governance framework, (ii) tools and methodologies, (iii) survey administration, and (iv) Tableau dashboard strategies. (4) Dominik Tomicevic provides a compelling account of how NASA’s People Graph is supporting a range of priorities from upskilling to workforce planning – with insights from the NASA team of David Meza, Madison Ostermann and Katharine Knott, MBA: “Knowledge graphs offer flexibility, since you don’t need a full schema upfront. We began with known relationships and expanded as we uncovered more insights in the data.” (5) In an edition of her excellent Trending Up newsletter, Morgan Depenbusch, PhD offers some compelling guidance on the use of colour in data visualisation and storytelling. FIG 7: Informed decisions are multi-dimensional. Financial logic makes them investable (Source: Rosario Germino) THE EVOLUTION OF HR, LEARNING, AND DATA DRIVEN CULTURE MCKINSEY - HR Monitor 2025 The gap is widening between what is needed from an efficient, effective HR function and what most organizations currently offer McKinsey's HR Monitor 2025 benchmark study of workforce and HR trends across Europe, delivers a sharp analysis of the critical shifts shaping the HR profession, emphasising that the next 12-24 months are decisive for the function. The report identifies five key trends: (1) Workforce planning is not approached strategically enough – see FIG 8 - (“…with rapid changes driven by gen AI and shifting skill needs, workforce planning must move beyond short-term staffing forecasts to include a longer-term view and future-scenario planning”). (2) Talent acquisition is becoming more complex: with only 56% offer acceptance rates, 18% of new hires leaving during their probationary period and the overall hiring success rate in Europe standing at a lowly 46%, a more strategic and coordinated approach to attracting and hiring talent is required. (3) Employee development continues to be highly fragmented (“To prepare the workforce for future challenges, organizations must connect performance management, learning and development, and talent development in one cohesive strategy”). (4) Employee experience is essential—and underdeveloped (“A more tailored, data-driven approach to the employee experience is needed to build motivation and long-term commitment to employers”). (5) Gen AI and shared-services centres could boost efficiency and effectiveness (“HR departments must modernize their operating models by expanding SSC adoption and using automation and gen AI to increase speed, scalability, and strategic impact”). For Chief People Officers, the message is clear: You must align HR strategy directly with business priorities, strengthen your HR operating model, and aggressively build digital and AI skills within HR. This is about laying the foundation for a modern, AI-enabled HR function that is both deeply people-centric and laser-focused on organizational performance. Kudos to the authors: Julian Kirchherr, Vincent Bérubé, Charlotte Seiler, Dr. Kira Alexandra Rupietta, Kristina Stoerk, Nina-Marlene Senst, and Simon Gallot Lavallée. ...with rapid changes driven by gen AI and shifting skill needs, workforce planning must move beyond short-term staffing forecasts to include a longer-term view and future-scenario planning FIG 8: Engagement in workforce planning (Source: McKinsey) FIG 9: Predicted impact of gen AI on HR department (Source: McKinsey) ESER RIZAOGLU AND STEPHANIE CLEMENT - How CHROs Can Prepare Their Function and the Enterprise for AI Transformation CHROs play a key role in safely using AI at scale to deliver business outcomes. Recent research by Eser Rizaoglu and Stephanie Clement for Gartner provides a helpful roadmap for CHROs steering their organisations through AI transformation, by focusing on HR's pivotal role in shaping the future of work. The report highlights three key actions for CHROs to enable their organisation's AI approach: (1) Assist in delivering business outcomes using AI: Leverage GenAI for HR productivity first, then expand to drive enterprise-wide improvements with a broader AI portfolio. (2) Manage behavioural outcomes of AI: Cultivate a culture of innovation, build human-centred change management plans, and introduce new HR roles to foster human-machine partnerships. (3) Enable workforce readiness for AI: Implement AI literacy programs for all (see FIG 10), while targeting upskilling efforts on segments most impacted, building empathy, and tracking readiness indicators. For CHROs in Steady-AI-Pace organisations, the focus is on foundational AI literacy and policy. Those at an Accelerated-AI-Pace must deepen this by targeting high-impact workforce segments and deploying AI champions to drive effective, human-centric change. FIG 10: AI Literacy Program Roadmap (Source: Gartner) DAVE ULRICH - Navigating Eight Paradoxes of AI for HR When algorithms combine with human empathy, judgement, and creativity, sustained progress occurs. In his article, Dave Ulrich highlights eight paradoxes on the AI for HR agenda that he believes business and HR leaders need to navigate to move up the s-curve and waves of HR impact (see FIG 11) to deliver more value. As Dave explains: “Navigating (not just managing) paradox means highlighting and working through opposing ideas—each of which is valid—that combine to create more value.” The eight paradoxes identified in the article are: (1) AI and AI: Artificial Intelligence * Authentic Intimacy. (2) Remove jobs and redefine work. (3) Bottom line efficiency and top line growth. (4) Distribute and concentrate power. (5) Lower and increase risk. (6) Expand perspective and reduce cognition. (7) Provide answers and explore questions. (8) Isolate and connect. FIG 11: Five stages of AI for HR evolution (Source: Dave Ulrich) EMPLOYEE LISTENING, EMPLOYEE EXPERIENCE, AND EMPLOYEE WELLBEING JARED WEINTRAUB - A day in the life of a GenAI-enabled workforce Deloitte forecasts that 25 percent of companies currently using GenAI will launch agentic pilots this year, rising to 50 percent by 2027 Jared Weintraub, PhD, SPHR's article for Deloitte paints a tantalising picture of a 'Gen-AI enabled workforce,' showcasing how AI agents are already transforming our daily work. Through a fictional Fortune500 company, Jared brings to life three key personas: (1) New Hire (Riley): Experiences personalised onboarding, with AI agents helping her navigate culture and quickly excel in her role. (2) VP (Taylor): Sees optimised leadership workflows, receiving instant summaries, personalised action items, and even real-time feedback on calls. (3) CEO (Angelina): Gains powerful support for strategic decision-making, with AI agents providing real-time insights and even coaching for high-stakes events like public town halls. These examples demonstrate AI's profound potential not to replace workers, but to fundamentally enhance human potential, leading to a significantly improved employee experience where individuals, teams, and organisations can thrive and perform at their absolute best. Thanks to Brian Heger for highlighting in his excellent Talent Edge Weekly. WORKFORCE PLANNING, ORG DESIGN, AND SKILLS-BASED ORGANISATIONS SCOTT REIDA AND KRISTIN SABOE - Applying the Rule of 72 to Workforce Skill Obsolescence and Productivity Degradation Amazon's Scott Reida and Google's Kristin Saboe, Ph.D. introduce a powerful financial concept to HR: the "Rule of 72." Traditionally, it's a shortcut to estimate how long an investment takes to double, by dividing 72 by its annual growth rate. They ingeniously flip this, applying it to skill evolution: by dividing 72 by a role's weighted average 3-year Compound Annual Growth Rate (CAGR) of its skills, one estimates the "years to obsolescence" if no upskilling occurs. This provides critical directional clarity on how fast job competencies are shifting. Their framework, illustrated in FIG 12, categorises skills into four key zones: (1) Emerging (low adoption, high growth, representing the cutting edge). (2) Table Stakes (widely adopted, foundational must-haves with steady growth). (3) On the Cusp (moderate adoption, sustained expansion, offering long-term value). (4) Sunset (declining demand, requiring intentional upskilling). This enables smarter workforce planning. HR can now target training budgets where skill erosion is rapid, shifting from reactive to proactive strategies. It transforms talent into a dynamic portfolio , informing sharper hiring and career development in our accelerating world. FIG 12: Categorising skills into four key zones (Source – Scott Reida and Kristin Saboe) McKINSEY - The new rules for getting your operating model redesign right When people feel invested in and supported, they are more likely to embrace change, contribute meaningfully, and sustain the behaviors that drive long-term impact. New research from McKinsey updating their nine golden rules for operating model redesign, which finds that five original (evergreen) rules have stood the test of time while four new (evolved) rules have emerged (see FIG 13). The study identifies a key finding: redesign success jumps from 59 percent when using all nine original rules to 97 percent when using all nine in the refreshed set. The article also presents four broad redesign themes for leaders to focus on: (1) Create alignment among leaders and decision-makers, grounded in strategy. (2) Invest deeply in rewiring workflows. (3) Make significant investments in people. (4) Create a performance-oriented culture for durable impact. For Chief People Officers, the key takeaway is that they need to become the architects of dynamic, human-centric operating models. Their focus shifts from traditional talent management to proactively designing how work gets done, emphasising skills and capabilities over static roles. CPOs should also lead on ethical AI integration, foster a culture of continuous learning, and empower leaders. This creates a workforce built for perpetual reinvention, driving sustained value in an increasingly uncertain world. Kudos to the authors: Brooke Weddle, J.R. Maxwell, Tristan Allen, Deepak Mahadevan, Elizabeth Mygatt, and Olli Salo. FIG 13: The refreshed golden rules of organisational redesign (Source: McKinsey) LEADERSHIP, CULTURE, AND LEARNING JEFF WETZLER - The Right Way to Prepare for a High-Stakes Conversation Curiosity increases your ability to process new information and respond creatively to complex problems. It activates the brain’s learning and reward centers, increasing your capacity for insight and creative problem-solving. In his recent HBR article, Jeff Wetzler introduces a helpful concept for leaders: The Curiosity Check (see FIG 14). This diagnostic is designed to fundamentally shift your mindset from defensive certainty to productive curiosity, and so improve your effectiveness in high-stakes discussions and boost your influence. It’s all about unlocking crucial, often hidden, insights. Wetzler outlines three actionable steps: (1) Choose Curiosity Over Certainty: Actively ask yourself "What am I missing?" challenging your assumptions. (2) Make It Safe to Speak Up: Create an environment where people feel secure sharing their true thoughts, proving safety through action, not just words. (3) Pose Quality Questions: Shift from shallow or leading questions to open-ended, neutral, and deeper inquiries that encourage genuine reflection. Wetzler brings this to life with examples, highlighting how leaders often miss critical information when they assume team alignment, never probing for the "unspoken thoughts" that hold the real insights. This approach empowers you to tap into wisdom you might otherwise completely overlook. Thanks to Amy Edmondson for highlighting. FIG 14: The Curiosity Curve (Source: Jeff Wetzler) MCKINSEY RESEARCH AND INNOVATION LEARNING LAB – Reimagined: Development for the Future of Work – Evolving Trends in L&D Article | Full report Leaders must prepare for a future defined by radical candor regarding the impacts of AI on work and the workforce. The 2025 McKinsey Learning Perspective spotlights three interconnected themes crucial for people development in a rapidly changing world: (1) Fluid Development Ecosystems: Organisations must design work to be inherently developmental, shifting from rigid structures to dynamic, data-driven ecosystems. This means de-siloing HR functions and embedding learning into daily work, making growth continuous and seamless. The goal is to make daily challenges catalysts for growth, supported by real-time data and foresight. (2) Responsible AI Adoption: This defining moment demands leaders preserve employee trust by showing AI will help them thrive, not just automate work. It's about fostering powerful human-AI collaboration, offloading repetitive tasks to AI to unlock human creativity and higher-order skills. Responsible adoption hinges on equipping employees with uniquely human capabilities like critical thinking and judgment. (3) Resilient and Adaptable Individuals and Organisations: Thriving organisations anticipate challenges, adapt, and grow, building structural and cultural foundations for resilience. This involves unlocking the potential of diverse, multigenerational workforces, supporting recuperation to prevent burnout, and enabling organisational resilience through sustainable workflows. It means seeing resilience as a shared, cultivated capability, not just an individual trait. Read the article by Heather Stefanski, Benjamin Hall, Jake Gittleson, and Jessica Glazer, and then dive into the full report, which also includes contributions from the likes of Sandra Durth. DIVERSITY, EQUITY, INCLUSION AND BELONGING ROBERT D. AUSTIN, NEIL BARNETT, CHLOE R. CAMERON, HIREN SHUKLA, THORKIL SONNE, AND JOSE VELASCO - How Neuroinclusion Builds Organizational Capabilities Leaders should consider neuro-inclusion as a strategic capability-building opportunity rather than a diversity initiative In a rapidly evolving world, neuro-inclusion is emerging as a critical organisational capability, as highlighted by Robert Austin, Neil Barnett, Chloe Cameron, Hiren Shukla, Thorkil Sonne, and Jose Velasco in the MIT Sloan Management Review. This isn't merely a diversity initiative; it's a strategic imperative that unlocks competitive advantage by leveraging the rich, natural variation in human cognition. By intentionally designing processes for neurodistinct individuals, organisations can profoundly improve: (1) Hiring, by tapping into overlooked talent pools with unique skills (as seen with SAP attracting highly credentialed candidates often missed by traditional interviews); (2) Innovation, through diverse perspectives that spark novel solutions (Microsoft's Teams ‘Blur’ feature emerged from a neurodistinct engineer's insights); and ultimately, (3) Culture, by fostering a more adaptive and truly inclusive environment for everyone. As the article reveals, EY, Microsoft, and SAP are prime examples of organisations already reaping these benefits, demonstrating that embracing neurodiversity enhances collective intelligence and drives superior business outcomes. FRANK DOBBIN AND ALEXANDRA KALEV - Achieve DEI Goals Without DEI Programs Many management innovations designed to improve performance actually boost workforce diversity as well, without inviting the backlash of formal DEI programs. Frank Dobbin and Alexandra Kalev, in their recent HBR article, challenge the traditional view of DEI. They argue that as formal DEI programs face headwinds, HR leaders can still drive significant diversity, equity, and inclusion by focusing on high-performance management techniques that naturally foster inclusion and improve business outcomes, all without the ‘DEI program’ label. They highlight five powerful techniques and provide examples of how these have been implemented by companies: (1) Referral programs: Companies like Oracle use these effectively, often boosting representation organically. (2) Skills upgrading: Walmart exemplifies this, investing in employee upskilling that broadens opportunities for diverse talent (see FIG 15). (3) Mentoring programs: IBM has long leveraged robust mentoring to support career progression across all groups. (4) Scheduling flexibility and stability: Gap demonstrates how providing predictable yet flexible schedules empowers diverse workforces. (5) Performance-based retention: Amazon uses data-driven approaches to identify and retain top performers, inherently benefiting those who excel regardless of background (also see FIG 15). This approach embeds DEI within the fabric of how we manage and develop our people, making it an undeniable component of business success. It’s about doing good by doing well. FIG 15: Walmart and Amazon’s changing workforces (Source: Dobbin and Kalev) HR TECH VOICES Much of the innovation in the field continues to be driven by the vendor and analyst community, and I’ve picked out a few resources from July that I recommend readers delve into: LISA K. SIMON - How Much Is a Skill Worth? In her article, Lisa K. Simon, Chief Economist at Revelio Labs, presents the findings of a new paper, she co-authored with David Dorn, Ludger Woessmann, Moritz Seebacher and Florian Schoner, which finds that the number and type of skills workers report are strong predictors of how much they earn: “In fact, differences in skills predict earnings better than differences in education or past experience. Workers who list more skills tend to be in better-paid jobs. On average, each additional skill listed on a resume is associated with 0.67 percentage points higher earnings.” Another finding is that not all skills are valued equally, with occupation-specific and managerial skills providing the largest boost to income, while a higher prevalence of general skills is associated with lower earnings (see FIG 16). Thanks to Seth Hollander, MBA for highlighting the article and paper. Workers who list more skills tend to be in better-paid jobs. On average, each additional skill listed on a resume is associated with 0.67 percentage points higher earnings. FIG 16: Only having general skills on a resume is associated with lower earnings (Source: Revelio Labs) WARDEN AI - State of AI Bias in Talent Acquisition This is an excellent new report from Jeffrey Pole and the team at Warden AI, which provides a comprehensive and data-driven review of AI bias, compliance and responsible AI practices in talent acquisition – the area of HR, which perhaps has the most significant adoption of AI. With a foreword by Kyle Lagunas, and contributions from the likes of Hung Lee (see quote below) and Sarah Smart, Sultan Murad Saidov and Trent Cotton, key findings include: (1) 75% of HR leaders say bias is a top concern when adopting AI. (2) 15% of AI systems fail to meet fairness metrics for one or more demographic group. (3) AI scores 0.94 vs 0.67 for humans, outperforming on average across fairness metrics (see FIG 17). (4) AI is up to 45% more fair than humans for women and racial minority candidates. Congrats too to Jeff and the team for raising $1.6m in a recent funding round. We are right to worry about AI bias, but we should not forget that the baseline, human only judgment, is far from bias-free - Hung Lee FIG 17: AI outperforms humans across fairness metrics (Source - Warden AI, State of AI Bias in Talent Acquisition) COLE NAPPER - From HR Skills…to HR Jobs When new trends emerge at work, they are likely to first appear as skills. As skills evolve, they consolidate into job titles and full occupations. The prolific Cole Napper highlights Lightcast data to paint a compelling analysis on the journey of people analytics, workforce planning and talent intelligence from trends to skills to jobs: “When new trends emerge at work, they are likely to first appear as skills. As skills evolve, they consolidate into job titles and full occupations.” In the article, Cole presents data visualisations and analysis on how job postings mentioning each of the three skills fluctuated over time, how this translated into job titles, and the wage premium (see FIG 18) that these three categories have on HR salaries in general (on the theme of people strategy and analytics salaries, read this post by Pallavi Narang) Look out for Cole’s book, People Analytics: Using data-driven HR and Gen AI as a business asset, which is available for pre-order now ahead of being published on August 26. FIG 18: Median salaries in HR areas (Source: Lightcast) PODCASTS OF THE MONTH In another month of high-quality podcasts, I’ve selected four gems for your aural pleasure: (you can also check out the latest episodes of the Digital HR Leaders Podcast – see ‘From My Desk’ below): PETER FASOLO - Leading with impact as a chief human resources officer – In this must-listen episode of Capital H, Peter Fasolo, Ph.D., former chief human resources officer at Johnson & Johnson, joins host Kyle Forrest to discuss the power of systems thinking, board collaboration, aligning your people agenda with enterprise strategy, and more. ANGELA LE MATHON - AI-Native HR Operating Model & AI Agents for Skills/Tasks – The brilliant Angela LE MATHON joins Cole Napper to discuss how AI is transforming the work that people analytics does and how the function operates as well as envisioning a new AI-native operating model for HR. SVENJA GUDELL, BROOKE WEDDLE, AND BRYAN HANCOCK - What the labor market isn’t telling you—yet – Svenja Gudell, chief economist at Indeed, joins Brooke Weddle, Bryan Hancock, and host Lucia Rahilly, on an episode of McKinsey Talks Talent to help leaders make sense of the current collision of labour market trends: generative AI, agentic AI, an aging workforce, shifting priorities, and more. BEN WEIN – How Bristol-Myers Squibb used skills data to solve a life-or-death talent shortage – Ben Wein, Director of Workforce Skills Enablement at Bristol Myers Squibb, joins Julius Schelstraete ? on The TechWolf Podcast to share how BMS is becoming a skills-based organisation—starting with a business-critical talent shortage in cell therapy manufacturing. Ben explains how BMS uses skills data to drive faster hiring, smarter workforce planning, and ultimately, patient impact. VIDEO OF THE MONTH DJ PATIL - Data, Decisions, and the Future of Work: How AI and Curiosity Are Redefining Careers Many of the videos of the talks at the recent Wharton People Analytics Conference are now available on the Wharton School YouTube channel, including my talk on How Top Companies Scale People Analytics Adoption. There are some wonderful talks from the likes of Amy Edmondson, Ravin Jesuthasan, CFA, FRSA, Ben Waber, Karalee Close, Guru Sethupathy and Michael Fraccaro, but perhaps my favourite session of the two days was former US Chief Data Scientist DJ Patil’s fireside chat with Eric Bradlow on how firms can harness data science to navigate the future of work. They explore the evolving relationship between AI and human collaboration, the promises and pitfalls of algorithmic management, and how leaders can build ethical, resilient, and high-performing organizations in an increasingly data-driven world. BOOKS OF THE MONTH Given it’s the summer in Europe and North America, here are two books to read while you are getting some well-earned relaxation time: PETER HINSSEN – The Uncertainty Principle - Peter Hinssen's The Uncertainty Principle, his fifth book, is a vital read for HR leaders. It argues we're in a "Never Normal" world, where constant change is inevitable. Hinssen transforms uncertainty from a threat to an opportunity, urging us to move faster and think bigger. For HR, this means embracing ambiguity, leading cultural shifts, leveraging people data, and redefining talent and leadership for relentless evolution. It's about equipping our people to thrive and transform every challenge into a strategic advantage. For a preview of the book, I recommend Peter’s recent discussion with me on the Digital HR Leaders podcast: Uncertainty as an Opportunity: HR's role in Shaping the Future. JENNY DEARBORN AND KELLY RIDER - The Insight-Driven Leader: How High-Performing Companies are Using Analytics to Unlock Business Value - Jenny Dearborn, MBA and Kelly Rider's The Insight-Driven Leader is an inspirational guide to unlocking serious business value through people analytics. This book shows how to transform raw data into powerful workforce insights, solving critical challenges and driving success. You'll learn: (1) How to move beyond traditional rear-view HR metrics to actionable insights. (2) Real-life case studies from leading organisations, as well as cautionary tales. (3) Recommendations for becoming an insights-driven organization using workforce analytics. The book is a must-read for leaders aiming to align data with strategy and build a truly insight-driven culture. FROM MY DESK July saw four new episodes of the Digital HR Leaders podcast – all sponsored by our friends at Mercer (thanks IŞIL ÇAYIRLI KETENCI): ANSHUL SHEOPURI - How People Analytics is Powering Business Strategy - Anshul Sheopuri, Executive Vice President of People Operations & Insights at Mastercard, joins me for a conversation on how to embed analytics into enterprise-wide decision-making at scale. Thanks to Sasha Houlihan for organising. PETER HINSSEN - Uncertainty as an Opportunity: HR's role in Shaping the Future – As highlighted in the Books of the Month above, Peter Hinssen joined me to discuss what it really takes for HR to embrace uncertainty and lead in this era of the ‘Never Normal.’ RAVIN JESUTHASAN AND BRIAN FISHER - The Skills Revolution: Your Playbook for Workforce Agility – Ravin Jesuthasan, CFA, FRSA and Brian Fisher join me to explore why skills-based workforce planning has surged to the top of the HR agenda - and what leading companies are doing to turn intent into action. AMY BAXENDALE - How Arcadis Built a Skills-Powered Organisation – Amy Baxendale , Global Future of Workforce Director at Arcadis, provides a detailed guide on the journey the company has embarked to become a skills-powered organisation. The episode includes discussion on the business case, securing sponsorship, setting up governance, the partnership with Mercer and Eightfold, and the early benefits: We are early in the journey, but we are seeing some promising signs of progress. Our time to hire is trending downwards - that has a direct commercial impact for the business. We've also actually been able to calculate the financial impact of work that's being completed through gigs and show the actual impact on EBITDA LOOKING FOR A NEW ROLE IN PEOPLE ANALYTICS OR HR TECH? I’d like to highlight once again the wonderful resource created by Richard Rosenow and the One Model team of open roles in people analytics and HR technology, which now numbers over 525 roles with half of these being new. THANK YOU To HR magazine and Charissa King for including me again in their annual HR Most Influential list as one of the ten most influential practitioners The Talent Games for including the Digital HR Leaders podcast at #6 in its 27 Best Leadership Podcasts for HR Leaders. Steve Sands for including my work as part of his Human Resource Management Analytics night class at the National College of Ireland. A huge thank you to the following people who either shared the June edition of Data Driven HR Monthly and/or posted about the Digital HR Leaders podcast, conferences or other content. It's much appreciated: Emmanuel Duncan, Rob Baker, FCIPD, MAPP, Richard Hall, Robert Rogowski, Catherine de la Poer, Caroline Lambe, Jeremy Sholl, Narelle Burke, Edan Halili, Francesca Caroleo (SHRM-SCP, ICF-ACC), Uwe Gohr, Joseph Frank, PhD CCP GWCCM, Randeep Kaur, Aaron Chasan, Danial Singh Kang, Jorge-Luis Gonzalez, Anisha Moosaأنيشا موسى?????, Carlos Lopes, Danielle Farrell, MA, CSM, Kris Saling, Hiroyuki MIYAI, Ph.D., Yukiko Hosomi, Dr. Christoph Spöck, Joachim Rotzinger, Kevin Le Vaillant, Seung Won Yoon, Alexis Fink, Timo Tischer, Dr. Tobias Bartholomé, Jose Luis Chavez Vasquez, Meg Bear, Abhinav Tiwari, Esther Abraas, Gareth Flynn, Elizabeth Musso, Jana Glogowski, Maarten van Beek, K Nair, Joonghak Lee, Sameer Tahir, Robert Allen, Volker Jacobs, Bilal Laouah, Florent Maire, Oliver Kasper, Jaap Veldkamp, Patrick Coolen, Jeff Wellstead, Jean-Francois (Jeff) BOUBANGA MIGOLET, Dan George, Shujaat Ahmad, Alexandra Nawrat, People Edge Consulting Ltd., Andrew Spence, Roshaunda Green, MBA, CDSP, Phenom Certified Recruiter ?, Austin Brockert, MBA, Dan Riley, Sanja Licina, Ph.D., Anna A. Tavis, PhD, Stela Lupushor, Jeremy Shapiro, David Simmonds FCIPD, Catriona Lindsay, Aravind Warrier, Michael Arena, Greg Pryor, Isabella Cheshire, Amardeep Singh, MBA, Aline Costa, Anis Alexandros El Namparaoui, Adam Treitler, Helder Figueiredo, Sebastian Knepper, Sebastian Kolberg, Lewis Garrad, Kerry Ghize, Preetha Ghatak Mukharjee, Jacob Nielsen, Pete Jaworski, Søren Kold, Prabhakar Pandey, Avani Solanki Prabhakar, Ian Grant FCIPD, Erik Samdahl, Max Blumberg, Sergey Puchka, Romy Hobson, Bettina Dietsche, Hernan Chiosso, CSPO, SPHR ?, Paola Alfaro Alpízar, Sergio Garcia Mora, Hanadi El Sayyed, David van Lochem, Maria Nolazco Masson, David McLean, Clara W Estanqueiro, Shonna Waters, PhD, Kevin Martin, Kathi Enderes, Serena H. Huang, Ph.D., Smadar Tadmor, Tobias W. Goers ツ, Dr. Denise Turley AI.Impact.Equity, Stella Ioannidou, Apeksha Awaji, Evan Franz, MBA, L N Divya Mudundi, Ross Sparkman, Salman Farooq, Megan Reitz, Todd Tauber, Heather Muir, AJ Herrmann, Priyanka Mehrotra, Oliver Auty, Priya Subrahmanyan, Naotake Momiyama, Bill Banham, Matthew Yerbury, Prachi Agasti, Robin Haag, Fabian Stokes, MBA, SWP, Monika Manova, Barry Swales, Dean Carter, Ian OKeefe, Ying Li, Alexandre Monin, Mike Zarrilli, Natasha Fearon, Pedro Pereira, David Balls (FCIPD), Naomi Verghese, Geetanjali Gamel, Frankie Close, Warren Howlett, Stephanie Murphy, Ph.D., John Gunawan, Jesse Clark, MBA, Caitie Jacobson Mikulis, Meghan M. Biro, Dan Trares, Kouros Behzad, Kathleen Kruse, Nick Lynn, Mariana Allain Carrasqueira, Marina Pearce, PhD, Dawn Klinghoffer, Raquel Mitie Harano, Delia Majarín, Deborah M. Weiss, Courtney McMahon, Nirit Peled-Muntz, Hanne Hoberg, Adam McKinnon, PhD., Don Dela Paz, Matt Elk, Sophia Houziaux, Danielle Bushen, Nabil Dewsi, Sai Bon Timmy Cheung 張世邦, Dolapo (Dolly) Oyenuga Agnes Garaba, Wouter Minten, Olly Britnell, Nick Hudgell, Roxanne Laczo, PhD, Claire Masson, Daisy Grewal, Ph.D., Laura Cole, Brian Elliott, Erin Eatough, PhD Henrik Håkansson Gabe Horwitz Russell Klosk (智能虎) The final note this month is a sad one - rest in peace Diogo Jota and André Silva. ABOUT THE AUTHOR David Green ?? is a globally respected author, speaker, conference chair, and executive consultant on people analytics, data-driven HR and the future of work. As Managing Partner and Executive Director at Insight222, he has overall responsibility for the delivery of the Insight222 People Analytics Program, which supports the advancement of people analytics in over 100 global organisations. Prior to co-founding Insight222, David accumulated over 20 years experience in the human resources and people analytics fields, including as Global Director of People Analytics Solutions at IBM. As such, David has extensive experience in helping organisations increase value, impact and focus from the wise and ethical use of people analytics. David also hosts the Digital HR Leaders Podcast and is an instructor for Insight222's myHRfuture Academy. His book, co-authored with Jonathan Ferrar, Excellence in People Analytics: How to use Workforce Data to Create Business Value was published in the summer of 2021. MEET ME AT THESE EVENTS I'll be speaking about people analytics, the future of work, and data driven HR at a number of upcoming events in 2025: July 31 - August 1 - People Matters TechHR India 2025, Delhi August 13-16 - GCHRA Africa, Accra, Ghana (I will join virtually) September 25 - Visier Outsmart Local London, London October 7-9 - Insight222 Global Executive Retreat, Atlanta (exclusive to the people analytics leader in member companies of the Insight222 People Analytics Program®) October 15-16 - People Analytics World, New York October 21-22 - UNLEASH World, Paris November 12-13 - HR Forum 2025, Oslo More events will be added as they are confirmed.

人机协作
2025年07月27日

人机协作

微软首席人力官Kathleen Hogan：员工如何充分利用人工智能 Kathleen Hogan Chief People Officer at Microsoft [Photo: courtesy of Microsoft] 微软首席人力官 Kathleen Hogan表示，人工智能对我们工作方式的影响将比个人电脑更大。 AI是我们时代的决定性技术，创造了一个巨大的范式转变，它将改变我们的工作方式，影响力甚至超过了个人电脑的引入。我们曾经有一个大胆的愿景，“每个办公桌上、每个家庭里都有一台电脑”，而今天，我们希望在“每个人的口袋里都放一个副驾驶”。当然，AI的影响也伴随着挑战。我们必须解决关于工作流失、算法偏见以及组织快速培养技能的真实担忧。但最终，我相信AI的潜力太大，不能采取观望态度。领导者需要创造正确的环境，让AI获得积极的势头。这将需要准备和有意识的方法，以便这些新的AI工具不仅帮助员工提高生产力，而且帮助他们茁壮成长。我建议关注这三个方面，以更快实现这些好处：培养基于敏捷的文化、重新想象我们的工作方式、投资于更深层次的人类技能。培养基于敏捷的文化为了充分利用AI的承诺，团队必须保持敏捷。即使是那些多年来一直在内部使用AI进行数据分析、预测建模和任务自动化的公司，生成性AI也代表着一个重大转变。通过能够理解人类语言、导航大量文档知识并创造内容，更多职能的员工现在可以使用这些AI工具。一个基于敏捷的文化还将加速组织建立推动AI价值的更广泛基础和最佳实践的能力。我相信，在AI时代培养这样的文化意味着拥抱适应性领导力，领导者必须愿意深入未知。重新想象工作方式 20世纪80年代和90年代的机器人自动化进步使制造业生产力翻了一番。这不是仅仅通过给工人提供更高效的工具实现的——公司通过重新思考生产技术和重新设计工作流程，优化人与机器之间的流程，实现了机器人自动化的全部价值。同样，要充分利用AI采用的价值，领导者需要重新想象工作是如何完成的。这始于将工作分解为更小的任务，以确定AI能做什么，以及或者比人类做得更好。除了自动化一些重复或乏味的工作任务，我们还需要确定AI可以如何协助员工处理更复杂和微妙的任务，如研究、写作和分析。这个想法是让领导者利用这段时间，不仅是自动化流程，而且是与AI一起重新想象流程，寻找新的工作方式。这将最终帮助人们更聪明地工作，而不是更努力地工作，给他们带来更多的精力，并发现更有意义和更令人满意的工作。关注人类技能生成性AI已经被训练了大多数人类语言，所以任何人都可以使用它。但就像任何新技术一样，仅仅给人们新工具而不提供使用它们的技能是不够的。而且，尽管这似乎与直觉相反，人类技能与技术技能一样重要，以有效使用AI。这包括分析判断力、灵活性、情商、创意评估、智力好奇心、偏见检测和处理能力，以及委派任务的能力。事实上，我们现在发现，基本的管理技能是发掘AI副驾驶的全部潜力的关键。就像委派给人类员工一样，与副驾驶合作需要能够清晰地沟通，设置背景和参数，定义期望，分析结果，并提供反馈。一个好的起点是根据学科开发AI技能培训和实践。随着我们从自动驾驶AI转向副驾驶AI，对人们来说，仍然扮演飞行员的角色，用批判性的视角评估他们从AI工具中获得的输出是必要的。这包括验证准确性和评估偏见。最终，飞机的船长有责任成功着陆。我相信，解锁AI的全部潜力是领导者的责任。AI的创新正在以惊人的速度发生。当我们导航AI对工作场所的影响时，组织领导者必须立即开始培育正确的环境，以确保没有人被遗留在后面。仅仅将AI工具放在员工手中是不够的。当我们培养基于敏捷的文化、重新想象我们的工作方式，以及建立获得AI最佳效果所需的人类技能时，我们可以帮助我们的组织和员工在这个新时代中茁壮成长。对我来说，能够成为这个令人难以置信的时刻的一部分，既令人兴奋又令人振奋。英文原文来自：https://www.fastcompany.com/90982077/microsofts-chief-people-officer-heres-how-workers-can-get-the-most-out-of-ai

人机协作
2023年11月27日

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