• Frontline Workforce
    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.
    Frontline Workforce
    2025年12月22日
  • Frontline Workforce
    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。
    Frontline Workforce
    2025年12月10日
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