• 超级员工
    当AI不断取代各种职位的时候,HR岗位反而增长约6%,为什么?! NACSHR核心摘要:AI大规模进入企业之后,HR会不会成为最先消失的部门?Josh Bersin最新分析给出了完全不同的答案。基于Lightcast职位数据,过去约20年HR相关岗位年复合增长约1.2%,而AI发展最迅速的最近24个月,HR岗位反而增长约6%。真正减少的,是HR Assistant、Recruiting Coordinator、Training Administrator等行政和流程型工作;增加价值的,则是HRBP、招聘判断、People Analytics、复杂员工服务和工作设计。美国BLS也预计,2024–2034年全部职业增长约3%,HR Specialists增长6%,L&D Specialists增长11%。 所以AI没有让HR消失,而是在重新划分HR工作的价值:流程被AI接管,人必须向判断、咨询、数据和业务问题上移。你觉得呢 过去两年,几乎所有关于AI与人力资源的讨论,最后都会落到一个问题:当AI能够筛选简历、回答员工问题、生成培训内容、分析人才数据,甚至开始参与绩效管理和组织决策之后,企业还需要这么多HR吗? 从直觉上看,HR似乎应该成为最先被AI压缩的职能之一。但Josh Bersin最近的一组观察,给出了一个看起来有些反常的答案:AI投入越来越多,美国HR岗位不仅没有明显消失,最近24个月反而增长约6%。 这并不意味着AI没有影响HR。恰恰相反,真正发生的变化可能比“裁掉多少HR”更深刻——AI正在重新定义什么样的HR工作值得由人来完成。 HR岗位没有消失,但HR内部的工作正在重新分配 Josh Bersin引用Lightcast招聘数据指出,过去约20年,HR相关职位保持约1.2%的年复合增长;而在生成式AI快速普及的最近24个月,HR岗位增长反而达到约6%。 这与很多人此前的预期完全不同。 过去企业部署HR系统,往往意味着流程自动化;今天部署生成式AI和Agent,更进一步意味着大量知识型、事务型工作也可以被机器处理。因此,一个自然的推论是:HR部门应该需要更少的人。 但Bersin观察到,企业真正做的并不是简单“删除HR岗位”,而是在重新组合工作。 HR Assistant、Recruiting Coordinator、Training Administrator等大量依赖流程、协调和信息处理的角色,确实正在受到自动化影响。但与此同时,企业对员工关系、人才判断、组织设计、技能发展、领导力、数据分析以及业务咨询等能力的需求并没有减少。 所以真正消失的,往往不是整个Job,而是Job里面的一部分Tasks。这可能是理解AI与就业关系最重要的区别之一。 AI首先淘汰的是任务,而不是职业名称 传统讨论经常把问题简化成:“AI会不会取代HR?”,但企业实际上并不是按照职位名称决定哪些工作交给AI。 AI不会首先判断:“这个人是HR,所以我要取代他。” AI取代的是更具体的任务:整理信息、回答标准问题、安排会议、生成文档、总结数据、制作初步报告、匹配简历、生成培训材料。 一个HR岗位可能包含20项不同工作,其中10项可以被AI明显加速,5项可以部分自动化,而另外5项仍然需要人的判断。 于是企业面临的并不是简单的“要不要这个岗位”,而是:剩下来的时间,HR应该拿来做什么? 如果AI让一名招聘人员减少大量简历筛选和面试安排工作,那么他的价值就必须转向人才判断、Candidate Experience、Hiring Manager咨询以及复杂人才市场分析。 如果AI可以自动回答大量福利和政策问题,那么员工服务团队就必须把更多精力放到复杂员工关系、特殊案例和管理者支持。 如果AI可以迅速生成培训课程,那么L&D真正的价值就不再是“制作多少门课”,而是判断企业需要什么能力,以及如何真正推动员工能力改变。 这其实是一场HR工作的价值迁移。 事务型HR正在减少,但专业型HR正在变得更重要 Josh Bersin说传统HR行政和流程型工作可能仍然占到HR岗位的30%—40%。这部分恰恰也是AI最容易产生效率提升的地方。 例如,在Walmart、Standard Chartered等企业,大量基础员工服务、Onboarding和Benefits问答可以通过技术处理,HR人员则可以转向更加复杂的员工绩效、家庭需求和员工关系问题。 在Travelers、Polestar等企业,L&D团队过去可能需要数周甚至数月开发一门课程,现在可以借助AI快速生成视频、Simulation和即时学习支持。 在招聘领域,排期、沟通和初步筛选越来越自动化,但企业同时越来越重视候选人真实性、人才质量、面试判断和面对面互动。 People Analytics同样如此。过去大量时间消耗在Survey、Benchmark和报表制作上,现在HR分析人员必须更直接地回答业务问题:为什么关键人才离职?哪些团队的生产力正在下降?AI正在如何改变岗位技能?企业应该重新配置哪些人才? 所以我们看到的不是HR价值下降,而是低价值HR工作被不断剥离之后,剩余HR工作的价值门槛正在提高。 HRBP可能是这一轮变化最典型的岗位 Josh Bersin特别提到Panasonic、Accenture等企业正在重新定义HRBP。过去很多企业所谓的HRBP,实际上仍然承担大量流程协调、政策解释、员工事务和内部资源对接工作。 AI和HR平台逐渐接管这些基础任务之后,一个真正的HRBP应该越来越像内部管理顾问。 他必须理解业务战略、组织能力、领导团队、人才结构和成本效率,并能够和业务负责人一起回答: 我们为什么招不到这些人才? 哪些岗位应该被AI重新设计? 哪些团队应该增加Headcount,哪些应该减少? 未来两年真正需要什么技能? 组织架构是否仍然适合当前业务? 这类工作并不会因为AI而减少。 相反,企业拥有越多AI工具,管理者面对的组织问题反而可能越复杂。 这也是为什么AI时代一个看似矛盾的现象开始出现:企业越来越自动化,但同时越来越需要能够处理复杂人才和组织问题的人。 AI提高效率,并不必然意味着Headcount同比例下降 这也是Bersin这篇文章最值得企业管理者思考的地方。很多AI商业案例仍然采用一个非常传统的ROI公式: “这套AI工具可以节省多少人工时间,因此可以减少多少人。” 但这种计算方式忽略了一个重要事实。知识工作与流水线生产并不完全一样。 如果AI让HR节省30%的时间,企业不一定会马上减少30%的HR人员。 企业可能选择让HR处理更多复杂问题,提高服务质量,加快招聘,提高管理者效率,推动技能转型,或者承担过去没有能力开展的组织项目。 换句话说:Productivity Gain并不自动等于Headcount Reduction。 它也可能意味着Capability Expansion。 这也是为什么我们会看到AI使用快速增长的同时,部分知识型职业仍然保持就业增长。 技术减少了一部分工作,但同时提高了组织能够解决问题的上限。 对HR而言,真正值得担心的不是岗位消失,而是价值停留在流程层 从NACSHR的角度看,Josh Bersin的观察并不能简单理解为“HR是安全的”。 恰恰相反。 它释放出的职业信号其实非常明确。 如果一个HR的核心价值仍然来自录入数据、安排面试、整理报表、回答标准问题、制作培训材料或者执行固定流程,那么AI对这个岗位的冲击几乎是确定的。 真正有增长空间的,是那些能够把AI转化成更高业务价值的人。 未来HR越来越需要理解业务、判断人才、设计组织、处理复杂员工问题、推动领导力发展、进行Workforce Planning,并重新设计Human + AI共同工作的方式。 换句话说,未来企业衡量HR价值的方式可能会发生变化。 过去是:你完成了多少HR流程? 未来可能是: 你帮助组织解决了什么问题? HR不会消失,但“只会做HR流程”的HR正在失去保护层 “HR岗位最近24个月增长约6%”是一个很容易传播的数据。 但如果只记住这个数字,反而会错过这篇文章真正重要的部分。 Josh Bersin真正描述的并不是“AI无法取代HR”。 而是一个更复杂的现实: AI正在大量取代HR工作中的低复杂度任务,同时把HR推向更复杂、更专业、更接近业务的位置。 Job还存在,但Tasks已经变化。 岗位数量可能增长,但岗位要求也在提高。 HR团队仍然存在,但每一个HR需要创造的价值正在重新被定义。 因此,AI时代真正的问题已经不再是:“未来企业还需不需要HR?” 而是:“当AI可以完成大量传统HR工作之后,企业为什么还需要你?” 能够回答这个问题的人,可能不仅不会被AI淘汰,反而会进入一个价值更高的HR时代。 NACSHR认为,这才是“HR岗位仍在增长”这组数据背后,真正值得全球HR专业人士关注的信号。
    超级员工
    2026年08月13日
  • 超级员工
    Yes, AI Is Really Impacting The Job Market. Here’s What To Do. Josh Bersin 在 2025 年末指出,美国就业市场正在出现结构性变化。整体失业率上升至 4.6%,其中应届大学毕业生的失业率接近 10%,成为最受冲击的群体。与此同时,不要求大学学历的岗位持续增长,一线员工的重要性正在被重新定义。更值得关注的是信任问题。Edelman 调研显示,70% 的员工不信任企业关于 AI 裁员的说法,只有 27% 信任 CEO。AI 不只是技术工具,而是一场社会与组织层面的转型。Josh Bersin 强调,AI 并非消灭岗位,而是放大能力。真正的挑战在于,企业是否愿意投资年轻人才,是否能用透明沟通化解 AI 焦虑。 详细来看 All year I’ve been studying the employment data and talking with press about the smallish impact of AI on the job market. Most of the slowdown in US jobs, from my data and conversations, has been driven by cost-cutting and general economic uncertainty, not explicit AI job replacement. Well going into 2026 the situation is changing. The US unemployment rate is now 4.6%, up from 4.2% one year ago  (a 9.5% increase) and 3.7% in November of 2023 (a 24.7% increase in two years). These are significant increases, especially considering that unemployment was 3.6% in November of 2022. This tells me that the US economy is slowing after the post-pandemic “revenge buying” frenzy of 2021 and 2022. And of course US tariffs, inflation, and relatively high interest rates all contribute. But now let’s look under the covers and break out unemployment into two sub-groups: new college graduates (24 years and younger), and more seasoned workers (age 25-35). Suddenly you see a divergence. The green line, tenured college graduates, shows a steady unemployment rate below the average. This makes sense: these are experienced employees with skills, judgement, and seasoned decision-making maturity. The orange line, new college graduates, is trending upward. In fact right now it’s almost 10%, which is the highest it has been since July 2021, the peak recovery from the pandemic. Looking backwards, the only time young college grad unemployment was this high was in 2011, a period of recovery from the 2008 recession. (St. Louis Fed agrees.) And by the way, to round this out, jobs that do not require a degree are plentiful, roughly 82% of the workforce (up from 79% five years ago). So AI is not only slowing new college grad hiring, it’s also reducing the total number of jobs that require college. There are three important things happening here: First, whether it’s correct or not, employers are slowing down entry level hiring. Companies hire new college grads for many reasons (largely for talent pipeline), and many newly minted grads are far more AI-ready than we are. Despite this, it appears to economists that it’s harder than ever for these young folks to compete, so they need to “sell” their AI readiness and learning capacity. Second, the frontline workforce is becoming much more important. The general automation of white collar work (it’s still early days) and the explosion of jobs in healthcare, social services, retail, repair, entertainment and distribution are making the “college grad” part of the workforce relatively smaller. That’s not to say the money isn’t good, but as a CEO or leader more and more of your energy has to go into supporting these frontline workers. (Read our Frontline-First research for more.) Third, employees don’t trust CEO talk about jobs. A new study by Edelman shows a massive lack of people’s trust in business leaders (and AI scientists) around AI. This 5,000+ worker survey found that 70% of US workers do not trust statements about AI job reductions. When asked “who you do trust” only 27% of US workers trust the CEO. So we, as leaders, have a trust problem. Here’s the trust data, and this is all about “Trust in AI’s Value” not “trust in the AI platform.” AI Is a Socio-Technological Innovation As I talked about in this week’s podcast, AI is “socio-technological.” It has many societal and sociological impacts. If only half your employees believe what leaders are telling them, they’re going to hold back, grumble, and resist change. This is why economic insecurity is high: people are concerned about their jobs, careers, and future earnings. (So AI anxiety could actually lower economic productivity!) The solution to this is not to ignore the topic, but rather to discuss it openly. None of us really know how much impact AI will have (I do know most platforms over-sell its value right now), and AI is a little scary. We have to get comfortable with phones that talk back to us, creepy emails that know our name, avatar-based job interviews, AI-driven career advice, and AI-informed performance reviews. And in 2026 we’re going to see  digital twins, robots, and more real-life animations of people at work. (Galileo Learn uses a “Josh Agent” to coach and challenge you as you learn.) Here’s my advice. If you’re holding back on entry-level hiring you may be making a mistake. Younger staff, who have lived with this technology for more of their lives, are likely to be the ones to most quickly use AI, build with AI, and innovate with its new applications. People who are tenured tend to see new tools as a way to “speed up what they know how to do.” New employees might just say “why not do it this way?” and bring you the reinvention you need. Everyone Has The Opportunity To Be A Superworker Now AI is not a job killer, it’s a big job-leveler. You, as a younger worker, have access to information and research which was often hoarded by experts. If you’re willing to roll up your sleeves, you can move from “apprentice” to “newly minted expert” quickly. And if you’re looking for a job there’s no excuse for not becoming an expert on the company before you talk with a recruiter. For senior, more tenured people the same applies. You can’t rely on your experience alone any more: you, too, should be digging in and learning about new technologies, tools, and advancements in your domain. Employers: Be Careful How You Think For hiring managers and executives, beware of the “tenure trap” above. Just because a senior person knows your business better, you may find that the young “AI-Guru” right out of college catches up fast. Remember, tenured people may see AI as a way to “do things the old way faster” rather than “rethink the way we work.” For HR leaders and recruiters, remember one thing. Younger workers may learn faster and ultimately improve productivity at a faster rate (plus they cost less). If you seek out fast-learning AI pioneers they could be your Superworkers of the future. And for CEOs and other execs, be honest and thoughtful about your plans. All our research points to AI as a “scaling technology,” not one to “eliminate jobs.” The more honest and supportive you are, the faster your employees will adapt and help your company stay ahead.
    超级员工
    2025年12月22日