• AI readiness
    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.
    AI readiness
    2025年12月22日
  • AI readiness
    AI并非裁员元凶:财富100强陷入“解雇—再招聘”循环,250亿美元换不来AI转型 美国财富100强的裁员潮与AI关系不大。报告分析了超过一万条招聘信息,发现仅有11%的岗位提及AI,6%要求具体技能。过去一年,这些企业共裁员8.6万人,但又在2025年7月新增5.8万个职位。所谓的“解雇—再招聘”循环让企业仅在2024年就支付了250亿美元的遣散费,平均每节省1美元,实际支出却高达1.27美元。 在AI热潮席卷全球的当下,企业大规模裁员似乎成了数字化转型的必经之路。但来自 Orgvue 的最新研究却揭示了一个令人意外的事实:AI并不是驱动裁员的核心力量,美国财富100强企业正陷入一场高成本、低回报的“Fire-to-Hire(解雇—再招聘)”循环。 一、AI“高声量、低落地”:仅一成岗位提及AI Orgvue 对财富100强企业最新招聘信息的分析显示,在所有岗位中,仅有 11% 提及AI,其中仅 6% 明确要求具体AI技能或平台经验。换句话说,大多数企业在招聘层面并未显现出对AI能力的迫切需求。 行业差异同样显著: 科技行业的AI需求最高,占比 26%; 金融与医疗行业分别仅为 9% 和 8%; 非管理岗位仅 8% 要求AI技能,而总监级以上职位则高达 18%。 这一结果揭示出一个趋势:AI素养正成为决策层的“战略语言”,而非一线员工的“执行工具”。 Orgvue 首席产品官 Jessica Modrall 指出: “AI 技能的真实需求远低于市场想象。企业似乎尚未明确AI究竟能在哪些岗位、哪些场景中真正创造价值。” 她补充说,AI 投资在实践中“屡屡令人失望”,暴露出雄心与落地之间的巨大断层。 二、裁员不是AI的结果,而是效率幻觉的代价 过去一年,48家财富100强企业共裁员86,000人,但其中 46家又在2025年重新招聘。仅2025年7月,这些企业就新增了 58,000个职位。 Orgvue 将此现象定义为“Fire-to-Hire Cycle”——一种表面上削减成本、实则代价高昂的循环。报告显示: 2024年财富100强企业仅遣散费支出就达 250亿美元; 扩展至财富500强,总额高达 430亿美元; 平均而言,企业每节省1美元人力成本,反而要额外支出 1.27美元 的隐性成本(包括招聘、培训与生产力损失)。 这意味着所谓“AI驱动的精简”并未带来效率提升,反而使企业在重组中不断失血。 Jessica Modrall 评论道: “AI经常被用作裁员的理由,但缺乏对岗位、技能与工作内容的数据洞察,企业实际上是在丢失宝贵的组织记忆与知识资产。” 三、“AI取代人类”是误解,企业更倾向招募年轻可塑性人才 研究还发现,64% 的新招聘岗位面向工作经验不足5年的候选人,其中近一半为基层岗位。这意味着AI并未消灭初级职位,反而让企业更青睐“灵活、学习能力强”的新生代劳动力。 然而,只有 24% 的招聘信息提及职业发展机会,18% 未公开薪资区间,显示企业更关注“短期补位”而非“长期培养”。这种策略虽然能降低薪资支出,却可能削弱企业的知识沉淀与文化连续性。 四、行业画像:AI需求冷热不均,文化与灵活性成关键差异点 科技行业(Tech):处于AI与文化双重引领地位。92% 的招聘岗位提到企业文化,70% 提供股权激励。 医疗行业(Healthcare):以灵活工作模式和职业发展机会领先,42% 岗位支持远程或混合办公。 金融行业(Finance):高层招聘比例最高(39%),但AI应用仍处早期,仅9% 岗位提及AI技能。 五、解读:AI不是“裁员导火索”,而是“转型信号灯” Orgvue 的研究为当前“AI导致大规模裁员”的论调泼下冷水。AI并未直接带来岗位消失,而是暴露出企业在组织规划与技能转型上的盲区。 真正的挑战不在于“AI取代人”,而在于“如何用AI重塑人”。企业若持续依赖短期的“裁员—补员”循环,而不建立系统性的人才与技能规划能力,将在AI浪潮中失去竞争力。 Modrall 总结道: “未来的关键,不是是否转型,而是你是否基于数据、有计划地转型。那些依赖直觉裁员、盲目重组的企业,正在为短期利益牺牲长期韧性。” AI并非洪水猛兽,也不是万能解药。真正的竞争优势来自于企业能否以数据为基础进行劳动力洞察,找到“技术—人—组织”三者的最优平衡点。在AI时代,管理者的任务不再是裁掉人,而是设计出让“人+AI”协同创造价值的新工作体系。
    AI readiness
    2025年10月30日
  • AI readiness
    你以为大家都懂 AI?其实他们都在装懂——Pluralsight《2025 AI 技能报告》深度解读 “我其实不太懂,但又不好意思说。”——这是许多技术人员和高管面对 AI 时的真实心声。 在我们谈论 AI 如何颠覆行业、重塑岗位的时候,也许我们忽略了一个关键问题:究竟有多少人真的懂 AI? Pluralsight 最新发布的《2025 AI 技能报告》给出了一个惊人的答案:大多数人其实都在“演戏”。 是的,你没有听错。报告调查了来自美国和英国的 1,200 位技术高管和从业者,发现整整 79% 的人承认夸大了自己对 AI 的理解,而站在组织最前线的高管,居然有 91%“装懂”。这不仅是一场职场里的集体错觉,也是一面照见现实的镜子:AI 正在迅速成为新的职场“裸泳”试炼。 “会不会用 AI”变成了一种表演 在很多公司,使用 ChatGPT 或 Copilot 本应是一种提升效率的手段,但却被悄悄贴上了“偷懒”的标签。报告显示,61% 的人觉得在工作中用生成式 AI 会被认为不够敬业。 于是,人们开始偷偷摸摸地用 AI —— 不打招呼、不留痕迹,生怕别人知道自己依赖了工具。这种“影子 AI”现象,让整个职场变得有点像小学考试时偷偷翻书的学生:大家都在作弊,却都装作没有。 “我懂 AI”成为职场社交货币 在调查中,九成从业者自信地说:我有足够的技能把 AI 工具融入工作中。 但问题来了:几乎同样比例的人又说,是“其他人”的 AI 技能不够,才导致项目失败。 这不是一个技术问题,而是一个认知偏差问题。正如报告所言,这可能是“达克效应”(Dunning-Kruger Effect)在作怪:越不懂的人越自信,越懂的人越谨慎。 我们真的会被 AI 取代吗? 报告也揭示了另一种深层焦虑:90% 的受访者担心自己被 AI 替代,而这个比例较去年增长了 19%。最焦虑的行业包括:内容创作、数据分析、销售和市场。 但现实其实并不那么残酷。数据显示,有近一半的企业正在新增 AI 相关职位。换句话说,AI 并不是“替代者”,而是“重塑者”。只是那些被“重塑”之前的人,必须先完成一场认知与技能的跃迁。 真正的赢家,懂得不断更新 幸运的是,大多数公司正在醒来。59% 的企业已经开始提供 AI 培训,54% 的企业通过涨薪来缓解员工的焦虑,甚至有些公司开始为员工提供“AI 心理建设”。 更可喜的是,有 8 成的技术从业者表示:AI 真的让我的工作更轻松了。 从数据建模到个性化推荐,从云管理到自动化任务,这些看似“高冷”的 AI 应用,正在变得触手可及。 写在最后:别再装了,真的可以学 也许我们都该承认:AI 发展太快了,不懂是常态,懂才是稀缺。真正拉开差距的,从来不是“演得像不像”,而是你有没有诚实地面对自己的技能盲区,并持续进步。 这份报告不是在揭示一个笑话,而是在给每一个职场人提个醒:别再装了,时间不等人,AI 的浪潮已经拍到了你脚边。 你是要假装会游泳,还是现在就跳下去学?
    AI readiness
    2025年04月03日
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