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.
20州联合起诉10万美元 H-1B 签证费:一场牵动美国教育与医疗体系的人才之争美国 20 个州正式起诉特朗普政府,反对 10 万美元 H-1B 新签证费用。州政府指出,该政策未经国会授权,将严重冲击教育、医疗等公共领域的人才供给。案件已进入联邦法院,可能对未来美国用工与移民政策产生深远影响,值得 HR 和企业持续关注。
美国围绕 H-1B 签证的政策争议再次升级。近日,包括加利福尼亚州和马萨诸塞州在内的 20 个州,正式向联邦法院提起诉讼,挑战特朗普政府对新 H-1B 签证征收 10 万美元费用 的决定。这一罕见的多州联合行动,迅速在政界、学界和雇主群体中引发强烈反响。
本次诉讼由加州总检察长 Rob Bonta 和马萨诸塞州总检察长 Andrea Joy Campbell 牵头。起诉方核心观点在于:该费用并非由国会授权设立,而是行政部门单方面决定,违反了联邦法律,也背离了国会当初设立 H-1B 项目的立法初衷。
州政府认为,H-1B 项目的本质是帮助美国在关键专业领域补充本土难以满足的人才缺口,而并非设置“准入门槛”式的高额收费。10 万美元的签证费用,不仅远超实际行政处理成本,也将对公共部门造成实质性伤害。
从数据来看,这一担忧并非空穴来风。教育行业是 H-1B 签证使用量排名第三的职业领域,全美约有 3 万名教育工作者 依赖该签证体系。在医疗领域,仅 2024 财年,就有 近 1.7 万名 医疗与健康相关从业者获得 H-1B 签证,其中约一半为医生和外科医生。根据官方预测,如果缺乏海外医疗人才补充,美国到 2036 年可能面临 8.6 万名医生 的结构性短缺。
相比之下,目前雇主为一名 H-1B 员工承担的总费用,通常在 960 美元至 75,595 美元 之间,已经包含多项法定与合规成本。州政府指出,将费用一次性抬升至 10 万美元,不仅缺乏成本依据,更可能迫使公立大学、医院和学区直接放弃国际招聘。
对此,美国国土安全部(DHS)态度强硬。DHS 在回应中表示,该收费措施是合法的,并将本次诉讼描述为“民主党州总检察长出于政治动机,对总统移民政策的阻挠行为”。双方立场分化明显,也使案件的政治与制度意义进一步放大。
值得注意的是,反对该费用的不仅是州政府。美国商会(US Chamber of Commerce) 以及 美国大学协会(Association of American Universities) 也已就同一问题另行提起诉讼,显示出企业界和高等教育体系对这一政策的普遍担忧。
在更广泛的背景下,特朗普政府此前还宣布,将加强对 H-1B 申请人的审查,包括对社交媒体的系统性审阅。这意味着,H-1B 政策正在从“成本层面”和“审查层面”同时收紧,其外溢影响已不再局限于科技行业,而是扩散至教育、医疗等公共服务领域。
目前,该案件已以 State of California v. Noem 为名,提交至 马萨诸塞州联邦地区法院。无论最终判决结果如何,这场诉讼都将对美国未来高技能移民政策、公共部门用工能力以及全球人才流动格局产生深远影响。
对 HR 从业者、雇主和国际人才而言,这不仅是一项费用调整的争议,更是一场关于“美国是否仍愿意为关键行业引入全球人才”的制度性拷问。
CHRO 的新战略机遇:生成式 AI 如何重塑组织的未来概要:74% 的 CEO 认为团队已准备好迎接 AI,但只有 29% 的 C-suite 同意。这一巨大认知差距既是风险,也是 CHRO 最关键的机会窗口。预计到 2025 年,77% 的初级岗位与超过 25% 的高管岗位都将因 AI 发生改变。未来三年,CHRO 必须从支持角色转变为组织未来的设计者,围绕三项任务展开:构建 AI 人才战略、重塑组织运营模式、建立 AI 治理框架。AI 时代的核心竞争力不再是技术本身,而是 CHRO 如何重塑组织能力与文化。抓住这个窗口期,组织才能真正迈向未来。
引言:迎接组织变革的“AI 时刻”
生成式 AI 与以往任何技术都截然不同,它正以前所未有的速度颠覆商业与社会,迫使领导者实时反思并重塑其核心战略。这场变革的核心并非技术本身,而是它对“人”与“工作方式”的根本性重塑。正如深度研究所指出的,“生成式 AI 的一切都与人有关——关乎工作如何完成”。
懂得如何用生成式 AI 赋能人才的领导者,将对业务产生“倍增效应”。在未来三年,首席人力资源官(CHRO)将迎来一个决定性的转折点,从传统的支持角色转变为驱动这一倍增效应的核心战略制定者。然而,当前仍有高达 60% 的高管将人力资源视为纯粹的行政职能,这一认知错位不仅是巨大的风险,更预示着一个前所未有的战略机遇。CHRO 必须抓住此刻,引领组织迎接未来。
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一、趋势洞察:生成式 AI 正在重塑工作的本质
1. AI 放大人类能力,而非取代人类
生成式 AI 的核心价值在于放大人类的专业能力。它通过自动化市场研究、内容创建、数据分析和代码开发等重复性任务,让员工得以专注于更高价值的创造性工作。例如,客服人员可以将常规问答交给 AI,从而专注于销售赋能;程序员可以摆脱繁琐的编程,聚焦于提升代码质量与安全性;HR 专家则能从日常流程中解放出来,全力投入于真正重要的人才发展。
企业的竞争优势不再仅仅来源于技术本身,而是来源于规模化员工的专业知识和扩展组织的能力。这催生了“AI 增强型劳动力”的概念。一个清晰的现实是:生成式 AI 不会取代人类,但使用生成式 AI 的人将会取代不使用它的人。
2. CEO 与组织间存在显著的“AI 准备度差距”
高管层对组织 AI 准备度的认知存在显著脱节,这种乐观情绪背后潜藏着巨大风险。数据显示:
74% 的 CEO 认为他们的团队已经为生成式 AI做好了技能准备。
然而,仅有 29% 的 C-suite 高管 同意这一观点。
这一巨大的认知鸿沟,代表了 CHRO 最为紧迫的行动指令。更值得警惕的是,AI 的影响是普遍的:到 2025 年,77% 的初级员工的岗位将发生转变,同时超过四分之一的高管也无法幸免。这使得 CEO 的盲目乐观尤为危险。CHRO 的核心机会在于,识别并弥合组织内部的人才与能力错配,确保组织具备驾驭变革的真实能力。
3. 未来关键能力:创造力与协作力超越技术力
在一个看似由技术驱动的变革时代,一个反直觉的真相浮出水面:人类独有的软性能力正变得空前重要。一项核心洞察指出:
高管们认为,到 2025 年,对组织最有价值的技能将是创造力。
当技术性工作可以被 AI 高效辅助时,企业的核心竞争力将从技术熟练度转向那些机器无法复制的能力。高管们认为,团队建设和协作能力与软件开发和编码同等重要,甚至领先于分析和数据科学。创造力,将成为引领未来的关键。
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二、CHRO 的三大新使命:未来 36 个月的行动框架
为应对挑战,CHRO 需要一个清晰、可执行的战略框架,围绕以下三大新使命展开行动。
1. AI 人才战略 (Talent Strategy for AI)
目标:重新设计人才的“选、育、用、留”体系,构建一支 AI 增强型团队。
行动建议:
重塑岗位与技能图谱:推动对现有岗位职责的重新定义,将工作重心从执行重复性任务,转向利用 AI 进行分析、创造和战略决策。
推动全员技能再培训:将 AI 技能提升视为员工重大的职业发展机遇。尤其要重点投资于高绩效员工,因为 AI 无法放大平庸的绩效,它带来的是一场革命而非演进,其真正价值在于将优秀人才的能力提升到全新高度。
将人力资源部作为战略试点:要让全员拥抱 AI,首先要从人力资源部开始。CHRO 应将 HR 部门打造为组织内 AI 转型的战略试点项目,率先对 HR 专业人员进行再培训,使其成为组织内 AI 应用的实践者、引领者和赋能者。
2. 组织运营模式重构 (Operating Model Redesign)
目标:打造更敏捷、更智能、更具创造力的组织模式,以释放 AI 的全部潜力。
行动建议:
聚焦高价值应用场景:避免被海量的可能性分散精力。集中资源投资于三到五个最具商业影响力的 AI 应用场景(“Focus on the top five. Or three.”),以点带面,实现价值最大化。
建立快速迭代与试错文化:鼓励团队以“快速失败”(fail fast)的方式进行小范围实验。建立跨部门的反馈循环机制,系统性地分享成功案例、失败教训和实践经验。
利用 AI 优化工作流程:应用 AI 增强的流程挖掘技术,深入分析现有工作流程,精准识别瓶颈与低效环节,并通过智能化改造加速决策效率。
3. AI 治理与伦理 (AI Governance)
目标:建立负责任的 AI 使用框架,确保技术向善,规避潜在风险。
行动建议:
建立明确的道德准则:制定并推行一套清晰的 AI 道德使用框架,其中包含明确的标准、指南和行为期望。
保障数据安全与隐私:在鼓励全员实验的同时,必须围绕数据保护和道德规范设立明确的护栏,确保创新在安全可控的范围内进行。
确保透明与公平:在招聘、绩效评估等关键人力资源环节应用 AI 时,必须建立有效的机制来管理算法偏见,确保决策过程的透明度与公平性。
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三、从战略伙伴到未来设计师:CHRO 的新定位
生成式 AI 正在推动 CHRO 的角色发生根本性演进。CHRO 必须从被 60% 高管视为被动的行政支持者,进化为主动的战略引擎,成为组织未来工作模式的总设计师和 AI 时代人力资本的管理者。CHRO 的新角色是通过前瞻性地引导 AI 在人才与组织层面的落地,主动重塑组织文化、决策模式和业务节奏。
在最高管理层中,CHRO 的新定位是连接技术、人才与业务战略的关键枢纽。AI 的成功绝非单一部门的责任,而需要建立一个由业务、IT 和人力资源负责人共同负责的问责模式。在这个领导力“三驾马车”中,CHRO 作为平等的战略伙伴,确保技术投资能够真正转化为组织能力和商业价值。
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决胜未来,重在组织能力的设计
生成式 AI 时代已经到来,领先的企业正在迅速采取行动。最终的成功者,将是那些能够围绕人才与技能建立灵活、深思熟虑的战略,并积极克服组织焦虑、奖励热情、拥抱包容与乐观的组织。
在生成式 AI 时代,决定企业未来竞争力的不是技术本身,而是 CHRO 对组织与人才能力的重新设计能力。