Josh Bersin 专栏 - 北美华人人力资源协会 - nacshr.org

Josh Bersin

Josh Bersin

In 2001, Josh Bersin founded Bersin & Associates, which became the leading research and advisory company for corporate learning, talent management, and HR. In 2012, Josh sold the company to Deloitte, when it became known as Bersin by Deloitte. As a Deloitte partner, Bersin was involved in many HR and learning engagements and was a principal author of Deloitte’s annual Human Capital Trends Report. He retired from Deloitte in 2018.

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Josh Bersin

Is The HR Profession As We Know It Doomed? In A Strange Way, Yes. I just spent a week in London meeting with several dozen companies and most of the discussion was about AI. The overwhelming majority of the conversations were about how companies are struggling, pushing, and agitating about the implications of AI, both within HR and within their teams. Coming from the CEO and CFO, HR team are under intense pressure to automate, improve their services, and reduce headcount with AI. Yes, we know AI is a technology for growth and scale, but the main message right now is “hurry up and do some productivity projects.” And “Productivity,” as you know, is a veiled way of saying “Downsizing.” So before I get back to HR, let me discuss downsizing. It’s absolutely true that almost every company we work with has too many people. Why? We have a sloppy way of hiring people, allocating resources, and managing work. We delegate “headcount” to managers and they go out and hire as many people as they can. We don’t really teach (or incent) managers how to build “productivity,” we actually do the opposite. We tend to reward them for “hiring more people.” The result is a problem I just talked about with a large advertising company: too many weird jobs and no consistency or structure to our work. This particular company has around 100,000 employees and more than 60,000 job titles. In other words almost every job is “invented for this person.” It’s insane. The whole reason we have companies (and not individual craftsmen) is to build scale. If we expect every individual manager to figure out how to scale, we’re more or less designing low productivity into the business. There are some simple models we use: call centers, global services groups, shared services, capability communities, and centers of excellence. But that kind of high-level productivity design is now becoming obsolete. In this new era of high-powered multi-functional agents, we need to go much further. Elon Musk likes the “first principles” approach. Fire everyone and start from “first principles,” only hiring the people you urgently need to build, sell, and support your product. That may work in small companies but when you’re big there are too many “support services” to consider. One of the companies we are working with has “program managers” and “project managers” and “analysts” sprinkled all over the organization in random places. In other words, their core staff don’t know how to manage projects, programs, or data. So there’s a bunch of overhead staff doing this for them. Drives me crazy. This took place because there was no discipline in hiring, so each group “bulked up” with staff. This is really business as usual. Organization design is an old, crusty, under-utilized domain so most companies barely think about it. IBM told me a few years ago that their “org design” strategy is to “hire a high performing executive and let him or her figure it out.” I hear that, it’s quite common. The bottom line is this: if we want to get a sound ROI from all these AI tools and agents we have to get a lot smarter about “work design.” And that is not building org charts, it’s the basics of figuring out our workflows, areas of common and uncommon process, and where and how we can automate. Most of our clients have tons of productivity systems already (ServiceNow, Salesforce, Workday, whatever), but they either don’t know how or don’t have the discipline to use them well. So they just keep hiring people. As an engineer I see this visibly all the time. It’s very easy to delegate a “problem” to a person, and not think about it as “plumbing.” But it is plumbing. As Tanuj Kapilashrami from Standard Charter put it, we need to focus on plumbing first, then we figure out where to apply AI. This means we can’t just cross our fingers and hope that the Microsoft Copilot is going to make everyone more productive. We need to look at business processes and skills at the core, and then literally reinvent our companies around these new AI tools. And skills are very important. The reason companies hire a bunch of “analysts” and “project managers” is because individuals and existing managers just aren’t good at their jobs. We all need to learn how to project manage, schedule, and analyze work. That way these high-powered specialists can work on big things, not sit in staff meetings taking notes (where AI note-takers do this well). (By the way, I have to guess that we’ll soon have AI agents for project management, program management, and functional analytics, so those staff jobs are going to be automated next!) How Does This Impact HR Let’s get back to HR. Given this massive effort to re-engineer and implement AI, where does HR fit? Well fundamentally HR is tasked to build process, expertise, and advisory services around the “people processes” in the company. That means hiring, developing, managing, paying, rewarding, and supporting people. It’s a big mission, and when we start to focus on “productivity” then HR must be involved. The general belief is that a “well run” HR team has about a 1:100 ratio to the company. In other words, if you have 10,000 employees you’re going to have around 100 HR people. And the HR team doesn’t just run around doing things, they buy and build HR technology for scale. So HR itself, as a “plumbing” type of operation, needs to be “lean and mean.” If your CEO wants you to hire 50 top notch AI engineers you can’t just start phoning everyone you know: you must decide precisely how you’re going to do this in a scalable, efficient, and highly effective way. (AI engineers are rare, they’re hard to hire!) So your little HR team has to think about productivity. Should we outsource this? (Which is a cheap and dirty way to look productive.) Should we buy a talent intelligence or sourcing system? Should we hire three high-powered recruiters? You know where I’m going. We have to find a way to “be productive” while we try to “make the company productive.” This means we, as a support and advisory function (HR professionals spend a lot of time coaching and supporting managers) have to stop creating forms and checklists and implement AI agents as fast as we can. Why? Because so much of our work is transactional, workflow-oriented, and administratively complex. And AI can do a lot of amazing things, like “assessing the skills of an AI engineer” for example. (Our AI Galileo can literally evaluate a recorded interview and give you a pretty good assessment of an individuals skills, mapped against the Lightcast, SHL, and Heidrick functional and leadership models.) Let’s assume we do this well, and HR technology vendors give us good products. We wind up with amazing recruiting agents, AI agents for employee training, onboarding, and coaching, AI agents that help with performance management, AI agents for succession and careers, and AI agents that deal with all the myriad of personal benefits and workplace questions people have. Where do we end up? Do we “automate away” our own jobs? Well, in a way the answer is yes. AI, through its miraculous data integration and generation capabilities, can probably do 50—75% of the work we do in HR. All this is far from built out yet, but it’s clearly coming. (We just talked with a large pharmaceutical company that is “all-AI” and they manage a team of 6,000+ scientists and manufacturing experts with only ten people in learning and development. They’ve automated training, compliance tracking, onboarding, leadership support, and all the details of training operations.) Could you do all that for a fast-growing 6,000 person company with 10 people? I doubt it. Most companies would have more than 10 people in sales training and sales enablement alone. So here’s my point. HR, like other functional areas in our companies, is going to have a real-life identity crisis. If you can’t figure out how to move your HR function up the maturity level quickly (check out our Systemic HR maturity model) someone’s just going to cut your headcount (the Elon Musk approach). Then you’ll be figuring out AI in a hurry. (Galileo can assess your HR maturity with its “consulting mode,” by the way.) I’m not saying this is easy. The AI products we need barely exist yet. But the pressure is on. You shouldn’t wait for the CFO to point his “productivity gun” in your face, you have to get ahead of this wave. Start pushing yourself to fix plumbing, check out the new tools in the market, get your IT team involved, and redesign your work using your own expertise. Many surprisingly good things will happen. Let me give you an example. A few years ago Chipotle adopted an AI-based agent system for recruiting, effectively automating a complex workflow for hiring. Not only did it save millions of dollars, the “speed and quality” of hiring went up so high the CEO talked about it as their top “revenue driver” with Jim Cramer on CNBC. In other words this “identity crisis” in HR is a good thing. Our recruiting, training, and employee services groups are too big. AI can automate enormous amounts of this work. So my advice is this. As the AI wave sweeps across your company, get out your old “org design” book and start redesigning how your HR team operates right now. Then you can go to the AI vendors and tell them what you want. That’s the secret to keeping HR in tip-top shape. Will HR go away? Well a lot of the process, data management, and support roles will absolutely change. And yes, employees and job candidates will happily use intelligent bots instead of calling their favorite HR manager. But as a Superworker, you, as an HR professional will do more interesting things. You’ll become a consultant; you’ll manage and train AI systems; and you’ll have much more real-time information about the strength and weaknesses of your company. We’re just going to have to lean into this AI wave to get there. As AI agents arrive, it’s time to seriously re-engineer HR. And this time it’s not a transformation, it’s a reinvention. Bottom line is this. Don’t wait for Workday, SAP, or some other vendor to “invent” a tool that changes your HR operation. You should do it yourself first and bring your IT people with you. That way you’ll buy and build the AI systems you need, and the result will be a new career, an even better HR function, and the opportunity to help your company move from “hiring” to “productivity” in the future. 我刚刚在伦敦与数十家企业进行了为期一周的交流，大部分讨论都围绕着AI展开。绝大多数对话的主题是：公司在应对AI带来的影响时，感到焦虑、推动、甚至焦躁不安，这种焦虑不仅体现在HR部门，也体现在各业务团队中。在CEO和CFO的压力下，HR团队正被要求加速自动化、优化服务、并通过AI实现人员精简。虽然我们都知道AI是一种能够促进增长和规模化的技术，但当前传递出的主要信息是：“赶紧推动生产力项目。” 而所谓的“生产力”，实际上就是“裁员”的委婉说法。先谈谈裁员几乎我们接触的每一家企业，都的确存在人员过剩的问题。这是为什么呢？因为我们的招聘、资源配置和工作管理方式本身就非常低效。我们将“编制名额”下放给各级管理者，而他们则倾向于尽可能多地招聘人员。我们并没有真正教导或激励管理者如何构建高效的生产力，反而往往奖励他们“扩大团队规模”。结果就是，像我最近在一家大型广告公司看到的那样，组织中充满了各种各样的职位，但缺乏统一性和结构性。这家公司有约10万名员工，却设有超过6万个不同的岗位头衔——几乎每个职位都是为某个人量身定制的，这种做法显然荒谬。企业存在的根本目的，是为了实现规模化。如果每个部门经理都各自为战，自行搭建团队架构，那无异于将低效深植于企业之中。虽然我们有一些基本的组织效率模型，比如呼叫中心、全球服务中心、共享服务、能力中心等，但这些传统设计在当下正逐渐过时。在高性能多功能AI代理全面普及的时代，我们必须走得更远。从“第一性原理”重构组织？ Elon Musk 推崇“第一性原理”方法——即解散现有团队，只从零开始招聘最核心、最迫切需要的人员。这种方法在小型公司或许奏效，但在大型企业中，由于存在大量“支持服务”，简单地“砍掉重建”并不可行。现实中，很多公司在各个角落散布着项目经理、程序经理、分析师等职位，因为核心员工缺乏管理项目、推进计划、或进行数据分析的能力。由于招聘过程中缺乏严格的标准和规划，各部门纷纷自行扩编，导致组织臃肿、效率低下。组织设计本来就是一门古老且被严重忽视的学问，多数公司对此缺乏系统化思考。IBM 曾表示，他们的组织设计策略是“聘请一位高绩效高管，让他/她自己摸索出解决方案”——这实际上是行业普遍现象。 AI真正改变的，是“工作设计” 如果我们希望从AI工具和代理中获得真正的投资回报率，就必须彻底重新思考“工作设计”——不仅仅是画组织结构图，而是要厘清工作流程、标准化与非标准化的业务环节，并找出可以自动化的领域。尽管大多数企业已经部署了大量的生产力系统（如ServiceNow、Salesforce、Workday等），但由于缺乏使用这些系统的能力或纪律，反而持续地通过“增加人手”来解决问题。作为一名工程师，我对此体会尤深。将问题推给某个人远比优化底层“管道”来得容易。然而，管理工作流程就像修建城市水管系统——如果基础设施不合理，再先进的AI工具也无济于事。正如渣打银行Tanuj Kapilashrami所说：“必须先修好管道，才能合理应用AI。” 这意味着，我们不能指望微软Copilot之类的工具神奇地提升员工生产力。我们必须从根本上重新审视业务流程与员工技能，并围绕AI重新设计整个企业运作模式。员工技能，未来的关键企业之所以聘请大量“分析师”和“项目经理”，往往是因为普通员工和管理者缺乏项目管理、时间安排、数据分析等基本技能。未来，所有人都需要掌握这些能力，而不再依赖大量辅助人员。高阶专业人才应当专注于重大事务，而不是出席会议做会议记录（AI记录工具早已能胜任此事）。（顺便提一句，我预测很快就会出现AI项目经理、AI程序经理、AI数据分析师——这些岗位也将逐步被自动化！）那么HR会怎样？回到HR领域，当企业致力于重塑流程、导入AI时，HR的角色至关重要。 HR的本质任务是构建并管理围绕“人”的各项流程：招聘、培养、管理、薪酬、激励与支持等。这项使命极为庞大，当公司将焦点转向“提升生产力”时，HR必须积极参与。一般认为，一个运作良好的HR团队与公司整体人数的理想比例是1:100。也就是说，一家拥有1万名员工的公司，大约需要100名HR人员。而优秀的HR团队不仅自己高效运作，更会采购、搭建技术系统，以实现规模化管理。举例来说，如果CEO要求你招聘50名顶尖AI工程师，你不能只是随便打几个电话，而是要设计一套高效、可扩展的方法。这可能包括外包、引进人才情报系统、招聘高端猎头，等等。总之，HR自身也必须成为高效运作的样板。因此，HR团队必须迅速引入AI代理，取代大量重复性事务，尤其是那些依赖工作流、流程管理和行政性处理的工作。比如，我们的Galileo系统已经可以自动评估候选人的面试表现，并将其技能映射到Lightcast、SHL和Heidrick的领导力模型。未来，HR工作会消失吗？某种程度上，答案是肯定的。凭借出色的数据整合和生成能力，AI可以完成50%-75%的HR工作。目前这些AI系统尚未完全成熟，但趋势已经非常明显。我们刚刚与一家大型制药企业交流，他们已经基本实现了“全AI化管理”，以仅10人规模的学习与发展团队，服务6000多名科学家和制造专家。他们通过AI自动完成了培训、合规追踪、入职辅导、领导力支持等任务。对于大多数公司来说，这种效率简直是难以想象的。 HR将迎来身份危机未来，HR必须迅速向更高的成熟度迈进（可以参考我们提出的Systemic HR Maturity Model）。否则，就会像Elon Musk那样，被大规模裁员，并被迫在短时间内仓促上马AI项目。我并不是说这条路轻松易行。事实上，市面上真正成熟的AI HR产品还非常有限。但压力已经到来。 HR不能等着CFO拿着“生产力枪”指着自己，必须主动出击，修好内部“管道”，试用新工具，联合IT团队，重新设计工作模式。这样，你将能主动选择适合自己公司的AI系统，并构建一个全新的、充满机遇的职业未来。结语：HR的重塑与再创造让我们看看Chipotle的案例。他们通过部署基于AI的招聘代理，成功自动化了复杂的招聘流程，不仅节省了数百万美元，还大幅提升了招聘速度和质量。甚至在接受CNBC采访时，CEO将这一成果称为公司的“主要营收驱动因素”。这场HR身份危机，其实是一个难得的机遇。我们今天的招聘、培训、员工服务团队规模普遍过大。AI将能够自动化其中大量工作。我的建议是：在AI浪潮席卷而来之前，立即拿起你尘封已久的组织设计手册，重新设计HR团队的运作方式。这样，当面对AI供应商时，你可以主动提出自己的需求，而不是被动接受他们的产品。未来HR不会消失，但大量传统流程、数据管理与支持岗位将发生剧变。员工与候选人也会越来越习惯通过智能机器人，而非人力HR来解决问题。不过，真正优秀的HR专业人士，将会变成超能型人才（Superworker）——你将成为企业战略顾问、AI系统训练师，并且能够实时掌握公司人才与流程的整体健康状况。这次，不再是简单的“转型”，而是真正意义上的“再创造”。

Josh Bersin
2025年04月26日
Josh Bersin

AI冲击下的白领危机：你准备好职业重塑了吗？概要：随着 AI 技术的快速普及，白领就业市场正悄然发生结构性变化。ADP 数据显示，需要高等教育背景的岗位增长最慢，而零售、餐饮、制造业等“传统蓝领”岗位需求激增，薪资涨幅甚至是白领的三倍。Josh Bersin 提出，白领专业人士需正视现实，主动进行职业重塑。这不仅仅是“学习新技能”，更是一次心态与方向的双重更新。经验与判断依然宝贵，但如果不能掌握AI工具和新方法，将难以在职场中保持竞争力。在这个快速变化的时代，你是否也思考过如何在5年、10年后仍保持职业优势？欢迎留言分享你正在学习的新技能，或者你对“终身职业”概念的看法。以下是正文，最后附录英文原文：在过去六个月里，我们已经看到大量迹象表明白领经济正处于衰退之中。员工停止跳槽，工资增长放缓，而研究表明，拥有大学学历的员工如今是市场上最不被需要的群体。请看 ADP 的最新研究，数据显示：那些需要高等学历（“高度准备”的岗位）现在是增长最慢的职业类别。 ? 大学学历的需求正在下降好消息是，这也让低薪、教育程度较低的群体迎来了更多机会。餐饮、医疗、零售和制造行业的就业需求强劲，工资增长速度甚至是白领工作的三倍。从整体来看，这对美国经济是利好的，因为它有助于缩小收入差距、提升生活水平。但对于那些在大学、研究生教育甚至博士学位上投入了大量金钱和时间的人来说，我们是否正在变成“未来被边缘化的劳动力”？不幸的是，答案是是的。那么，我们（以及雇主）该怎么办？简单地说，“赶快学会使用 AI”，对吧？研究显示，使用 AI 的软件工程师生产效率在几周内提高了 26%。对于市场营销、研究、出版、设计等专业人士来说也同样有效。但这种转变需要时间。一次令人震惊的拍摄经历我最近在伯克利为一门在线课程拍摄视频，当我走进拍摄场地时，我惊讶地看到 6 名资深的视频/音频人员，一个摆满灯光、摄像机和音响设备的房间，还有一名制片人、剪辑师以及其他专业人员，他们大多是 40 到 50 岁之间。这一天的拍摄团队成本估计至少在 5 万美元以上。而实际上，很多内容完全可以在一个灯光良好的家庭环境中，用一部 iPhone 和几只好麦克风就搞定了。请一位熟悉剪辑的 YouTube 博主，也能出不错的效果。虽然质量可能不同，但我几乎整整一个下午都在注视着一群“旧模式的工作者”。老一代的职业失落感我还看过一篇关于 Gen-X（40-50岁）职场人的职业困境的文章，一位资深广告人感叹道： “我花了 20 年研究广告和品牌，而现在一个 20 岁的网红比我更懂营销！” 这太真实了，真的。接受现实：我们必须适应变化我们这些曾经的顾问、分析师、工程师和专业人士，如今正在经历 1970 到 80 年代制造业工人曾面临的焦虑。我们也必须学会适应。以下是我个人的一些建议： 1️⃣ 放下偏见，承认需要重塑自我我曾经不断为自己 1970 年代接受的人文学科教育辩护，那段经历确实美好且重要。它教会我“看待世界的角度”，但并不等同于“实用技能”。此后的职业生涯，我不断“自我重塑”： 80年代学电脑和IT 90年代学数据、市场和分析 2000年代了解互联网、创业、领导力最近十年，深入研究 HR、管理、领导力和 AI 每个十年，我都重新开始，而“谦逊”是最大的动力。说实话，我曾以为 AI 只是 LISP 编程和一些疯狂的 UC Berkeley 计算机科学家搞出来的东西。直到三年前我才开始重新学习，从 YouTube 视频、播客、文章中补课。无论你是财务、市场、工程还是设计专业人士，都需要这样做。曾经用滑尺的你，得接受 HP 计算器，再接受电子表格，现在要接受 AI。不学习，你也会被取代。这很难受，但你任何时候都可以重新学习。请接受这个现实。并且要明白，“资历”可能并不重要。在这个时代，你可能得重新成为一个“学徒”。 2️⃣ 不要抛弃你的智慧与判断力尽管技术在变，但你的经验、判断力、教育背景仍然很重要。比如一位资深的视频制作人，他也可以像年轻人一样掌握 iPhone 和 AI 工具，但他的经验、审美、品牌意识、语言控制力，是新人难以比拟的。 AI 可以让每个财务部门都变得“自动化”，但最终真正盈利的公司，一定是那些更懂成本结构、盈利产品和商业模式的。这些能力不是工具教你的，而是智慧与判断的积累。 3️⃣ 尝试新事物，失败就放弃技术快速变化，很多人会选择“观望”，等那个“最牛”的工具出现再去学。但那通常是失败之路。例如 Galileo 这样的系统，也许已经比你现在用的工具好 10 倍了。即使它未来可能失败，也值得尝试。 1980 年代 Lotus 1-2-3 是一项伟大发明，首次实现了表格、文档和演示的整合。但最终它也被淘汰了。但那些第一时间学会 Lotus 的人，很快又掌握了下一代工具。一位我在 IBM 的朋友，就是 Lotus 的第一位系统工程师，后来成了 Yahoo 亚洲区总经理，最后还当上了风投合伙人。如果他当时只顾担心 Lotus 会不会失败，也不会有后面的辉煌。 4️⃣ 投资你的激情、能量和生命力接受职业终结是痛苦的。有时候让人焦虑、迷茫、甚至抑郁。我也经历过，花了多年学习的知识，如今一提就被人白眼：“你还活在过去。”我自己也常常这么做，可能跟年龄有关。解决方法是：重启你的个人能量。我花很多时间和年轻的 HR 领导、创业者、家庭成员相处，保持活力，吸收新鲜观念。保持身体健康（散步、早起、健身）也非常重要。这些让你有精力去“重启”。我每个周六早上都会录播客，这既是总结，也是前瞻。这种反思与更新，是重塑的重要部分。 5️⃣ 接受不确定性最后一点也是最重要的。当你的工作没了、或你需要重新开始时，就像跳下悬崖——你不知道落地在哪里。但这是可以接受的。如果你愿意更新技能、接触新世界，总会有新机会出现。就像那些失去工厂岗位的蓝领工人，后来转行做木工、包工、教师等等。如今我们这些“白领被冲击者”，可能无法像从前那样清晰地规划未来。但我敢保证，新机会一定存在。只要你准备好，未来一定充满希望。 Over the last six months we’ve seen much evidence of a white-collar recession. Employees have stopped changing jobs, wage growth is slowing, and research shows that workers with college degrees are the least “in-demand” in the market. Note this new research by ADP which shows that jobs requiring advanced degrees (“extensive preparation”) are now the slowest-growing part of the job market. The positive of this is that lower-wage, less educated workers are seeing opportunities. Demand for food service, healthcare, retail, and manufacturing workers is strong, and in fact their wages are growing at 3-times the growth of white-collar jobs. And this is positive for the US economy, since it reduces income inequality and raises standards of living. But for those of us who invested heavily in college, graduate school, and other advanced degrees, are we becoming the new “dislocated workforce” of the future? Unfortunately the answer is yes. What Should We (and Employers) Do? Well the simple answer is “get your act together with AI,” right? Studies show that software engineers who use AI are 26% more productive in weeks, and the same is true for those of us in marketing, research, publishing, and design. But this shift takes time. I recently spent an afternoon doing a video-shoot for an online course here in Berkeley, and when I arrived at the location I was astounded to see 6 senior video/audio people, an entire room of lighting, cameras, and audio equipment, and a producer, editor, and other professionals, each of whom were in their 40s or 50s. This massive team of video producers was probably costing the vendor $50,000 or more for the day. I bet most of this could have been done in a nicely lighted home with an iPhone and some good microphones and a YouTube influencer who knows video editing. I’m not saying the quality would be the same, but I was literally staring at “legacy work” for hours as I sat painstakingly through the interview. I recently read an article about the career frustrations of Gen-X workers (now in their 40s and 50s) and I had to smile. One of the professionals lamented “I spent 20 years learning about advertising and branding and now a 20-year old Influencer knows more about marketing than me!” So true, so true. Let me not belabor the issue, we just have to accept that things have changed. We, as the privileged consultants, analysts, engineers, and professionals in the world, face the same frightening fate which manufacturing workers felt in the 1970s and 1980s. And we have to learn to adapt. Let me give you my advice. 1/ Let go of your bias and admit you have to reinvent yourself. I spent a lot of my life cost-justifying the “liberal arts education” I received in the 1970s, and it was a wonderful and important experience. And I continue to maintain that learning about history, science, and philosophy is valuable over time. But what it taught me was “perspective,” not skills. Yes, I learned to read and write and think, but most of my career since has been about reinventing myself regularly. In the 1980s I learned about computers and IT; in the 1990s I learned about data, marketing, and analytics; in the 2000s I learned about the internet, entrepreneurship, and leadership; and in the ensuing decades I’ve learned about HR, leadership, management, and now AI. Every decade you have to reinvent yourself, and in every situation your humility is what drives you. Honestly I thought AI was all about LISP programming and the crazy UC Berkeley computer scientists I worked with until three years ago. I woke up like everyone else and “relearned” what I needed to know, watching YouTubes, reading, and listening to podcasts. If you’re a finance person, marketing professional, engineer, or other white collar worker, you must do the same. Just because you found your slide-rule fun and trendy to use in the 1980s, you had to shift to the HP calculator, spreadsheet, and now AI to stay ahead. If you fail to reinvent, you too can find yourself “thrown aside” for a younger replacement. This is a humbling experience, but you can learn at any age. Just accept that the world has changed. And let me add this. Your “seniority” and “experience” may not really matter. In a world of career reinvention, you may have to be a bit of an apprentice again. 2/ Don’t let go of your wisdom, judgement, and maturity. Despite the amazing skills of some, your experience, judgement, and education does matter. While you learn new tools and skills, it’s ok to fall back on everything you’ve learned before. And that means you, as a white-collar professional, are bigger and more than your “skills.” Consider the videographer, for example. He or she may learn to use AI and the iPhone like a teenager, but they bring their experience with mood, branding, tone, and language. Your experience as a finance professional, an engineer, a designer, or a leader still matters. Technical skills are actually the easiest to obtain – it’s the judgement, wisdom, and experience that create value. Imagine, for example, if every finance department is fully “AI-enabled.” That doesn’t mean every company in an industry will be as profitable – it will be the companies that deeply understand their cost structure, their profitable products, and their business models that outperform. That stuff comes from wisdom, judgement, and experience. 3/ Try new things and throw them away if they fail. When technology changes quickly there’s a tendency to “wait.” I’ll just wait until the world’s leading “design tool” or “finance tool” comes along, and then I’ll jump in and reskill myself. Sorry, that’s a recipe for failure. New systems (like Galileo, for example), may be 10 times better than the ones you’ve used before, even though some may fail. Lotus 1-2-3 was a miraculous invention in the 1980s and it taught us how to integrate spreadsheets, documents, and presentations. (Believe it or not, nobody even considered such integration in the 1980s.) But Lotus went the way of the dinosaur, and those skills were stranded. The people who jumped into Lotus and learned how to use it quickly migrated to a new generation because they had been playing around. One of my friends at IBM in the 1980s left the mother ship to join Lotus as their very first systems engineer. Yes, he eventually left but later that he became the general manager of Yahoo Asia and then a successful venture capitalist. If he had worried about Lotus’s future (it was a small company at the time), he never would have succeeded as he did. I play with lots of new tools all the time, often just to see what’s going on in my domain. This is why I talk with almost every HR tech vendor that approaches us. 4/ Invest in your own passions, energy, and longevity. It’s not easy to face the demise of your career. It’s painful, frightening, and sometimes depressing. I spent so many years learning about my old stuff and when I bring it up people roll their eyes and think “this guy is living in the past.” I know I still do it and maybe it’s because of my age. The solution is to reinvigorate your energy: personal and professional. I spend a lot of time with young HR leaders, young entrepreneurs, and my own young family members. It helps me stay current and excited about the future, because many of the things they do are amazing and unexpected. Take care of your physical health (go for walks, get up early, go to the gym). This gives you the energy to “reinvent.” I spend every Saturday morning working on my podcasts, largely as a way to “think ahead” as well as summarize the week. These periods of personal reflection and exercise are vital as you reinvent yourself. This morning I was watching a video of a job fair in Washington DC, watching dozens of middle-aged professionals who had been “DOGE’d” out there looking for work. One woman, a senior research professional in the FDA, was lamenting her need to reinvent her career at the middle of her life. I could see the sadness and fear in her eyes. She made the comment, “I spent a few days sitting on the couch wondering how I could ever get up again,” but then went to a job fair and suddenly realized there was a huge market of new opportunities. The reporter asked her how she felt, and I could see her eyes flash as she realized “maybe this reinvention will be good for me.” 5/ Uncertainty is ok. And that leads me to the final point. When your job is gone or you need to reinvent, it’s like jumping off a cliff. You don’t know where you’ll land. Well that’s perfectly ok. In most cases if you build your skills and reach out into the new world, you will find something new that you never expected. Many blue collar workers who lost factory jobs became carpenters, contractors, teachers, or other careers. We, as the white collar disrupted, may not see the future as clearly as we have in the past. I can guarantee, however, that new opportunities do await. Just strap in for a ride and positive things will happen ahead. Additional Information

Josh Bersin
2025年03月31日
Josh Bersin

Josh Bersin: Understanding the Path to CHRO Josh Bersin 最新研究揭示 CHRO 成长轨迹与未来挑战!近年来，首席人力资源官（CHRO）这一角色正在经历前所未有的变革。最新发布的《Understanding the Path to CHRO》报告(点击可以下载报告，同时附录在文章后)，基于对 20,000 多名 CHRO 的数据分析，深入研究了 CHRO 的成长路径、核心能力及全球 HR 领导者如何适应企业需求的变化。该研究揭示了HR 从传统行政职能向战略核心的转型趋势，同时发现： 75% 的 CHRO 来自外部招聘，内部继任计划严重不足。 CHRO 逐步迈入 C-suite，13% 进入企业最高薪酬前五名，相比 30 年前增长 26 倍。四类 CHRO 发展路径浮出水面：职业型 CHRO（Career CHRO）、企业型 CHRO（Company CHRO）、业务型 CHRO（Business CHRO）、运营型 CHRO（Operations CHRO）。具备国际化经验的 CHRO 绩效更高，75% 的高绩效 CHRO 曾在海外工作。政治学、经济学背景的 CHRO 更具影响力，而 HR 专业背景反而在高绩效公司中占比最低。从这些数据来看，CHRO 角色不再是简单的人才管理者，而是企业变革的推动者、业务战略的支持者、AI 与科技革新的领导者。那么，中国的 HR 领导者如何才能成长为具备全球视野的 CHRO？本文将从CHRO 角色的转型趋势、职业路径、核心能力模型及中国 HR 的成长路径四个方面展开分析。报告下载地址：https://www.hrtechchina.com/Resources/59250FA4-A800-58D9-5CE6-76E4DBC4F82A.html ? CHRO 的转型趋势：从 HR 负责人到企业变革领导者传统 HR 主要聚焦于招聘、薪酬管理、劳动合规等事务性工作，过去常被视为“后勤支持”部门。然而，随着全球劳动力市场变化、AI 赋能 HR、企业运营模式调整，CHRO 的角色发生了深刻变化： 1️⃣ CHRO 从 HR 服务交付者转变为业务战略伙伴过去 HR 被认为是支持职能，而今天，CHRO 需要直接参与企业战略决策，关注人才如何驱动业务增长。例如，疫情后全球远程办公兴起，CHRO 需要设计全新的组织架构、推动员工体验升级、调整绩效激励模式，以适应新的工作模式。 2️⃣ AI 与数字化重塑 HR 角色AI 和 HR Tech（人力资源科技）正在改变 HR 的运作方式。CHRO 不仅需要理解 AI 招聘、数据驱动绩效管理、智能学习平台，还要在组织中推动这些技术的应用。例如，采用 AI 进行人才画像分析、通过自动化面试减少招聘成本、利用数据分析优化员工保留率。 3️⃣ 全球化人才流动与多元化管理企业越来越依赖国际市场，CHRO 需要具备跨文化管理、远程团队领导、国际雇佣合规的能力。报告发现，在高绩效公司中，75% 的 CHRO 具备国际工作经验，这说明全球视野已成为 HR 领导者不可或缺的竞争力。 ? 四类 CHRO 发展路径：你属于哪一类？研究报告将 CHRO 的职业路径划分为四种主要类型，每种路径各有优势和挑战： 1️⃣ 职业型 CHRO（Career CHRO）——最常见的路径通过在不同公司担任 HR 领导职务不断晋升，占比 73%。优势：具备跨行业 HR 经验，能从外部引入最佳实践，拥有更广阔的专业网络。挑战：对新公司的文化和业务理解较浅，缺乏长期稳定的 C-suite 关系。 2️⃣ 企业型 CHRO（Company CHRO）——公司内部晋升在同一公司内部从 HR 经理逐步晋升为 CHRO，占比 17%。优势：深谙企业文化和业务流程，与内部管理层关系紧密。挑战：缺乏外部视角，可能难以推动 HR 变革和创新。 3️⃣ 业务型 CHRO（Business CHRO）——来自业务部门从销售、运营、市场等业务部门转型进入 HR，占比 8%。优势：更能理解业务需求，与 C-suite 关系更紧密，推动 HR 战略落地能力强。挑战：缺乏 HR 专业知识，需要依赖强大的 HR 团队支持。 4️⃣ 运营型 CHRO（Operations CHRO）——来自行政管理从财务、法务、风控、合规等行政职能转型进入 HR，占比 2%。优势：擅长数据分析、预算管理、企业治理。挑战：缺乏人才管理经验，对 HR 战略落地理解较弱。 ? 在北美工作的华人 HR 领导者如何突破瓶颈？在北美职场，华人 HR 面临文化适应、晋升壁垒、C-suite 话语权较弱等挑战。如何突破天花板，成长为 CHRO？ ? 1. 强化本土商业思维，提升 C-suite 话语权深入了解北美商业环境、企业运营模式、行业趋势。参与跨部门会议，与 CEO、CFO 直接对话，培养以业务为核心的人才战略思维。 ? 2. 培养影响力，突破“华人 HR 只擅长执行”的刻板印象多发声，多展示成果：在公司内外分享 HR 变革案例，塑造领导者形象。主导 HR 变革项目，例如推动 AI 赋能招聘、优化薪酬激励机制，提升 HR 价值感。 ? 3. 争取国际轮岗机会，提升全球 HR 领导力申请企业的跨国 HR 轮岗项目，拓展跨文化管理经验。参与国际 HR 论坛、北美 HR 高管社群，建立全球视野和人脉资源。 ? 4. 选择适合的 CHRO 职业路径喜欢跨行业挑战？选择职业型 CHRO 路线。想深耕企业文化？适合企业型 CHRO 发展路径。具备销售、运营经验？向业务型 CHRO 方向发展。 ? 5. 强化数据与 AI 能力，掌握 HR 科技趋势学习数据分析、AI 招聘、人才预测建模，让 HR 决策更具数据支撑。掌握 HR Tech 生态系统，推动数字化 HR 变革，提高 HR 部门的战略价值。 ? 结论：北美华人 HR 需要突破自我，成为“全球 CHRO” 要成为北美企业的 CHRO，仅靠 HR 知识远远不够，商业思维、数据能力、影响力、全球化经验都是必备技能。北美华人 HR 需要打破行业天花板，成为推动企业变革、掌控未来人才战略的全球化 CHRO 领导者！

Josh Bersin
2025年02月17日
Josh Bersin

Despite Political Firestorm, Diversity Investments Are Alive And Well Josh Bersin 发表文章：尽管政治压力和社会对多元化与包容性（DEI）计划的批评日益加剧，许多公司依然重视相关投资。这些企业将DEI从单独的HR计划融入到领导力、绩效管理和招聘战略中，形成了更加全面的文化建设方式。在员工对企业领导层信任度下降的背景下（如Edelman信任晴雨表指出的68%员工认为CEO不诚实），信任、透明和公平已成为企业文化的核心要素。企业如今更注重绩效文化，通过构建基于能力与高绩效的包容环境，吸引各年龄、性别及种族的优秀人才。杰米·戴蒙等领导者已公开表示支持DEI，证明高绩效与包容性是现代企业成功的关键。尽管DEI独立职能角色在减少，但相关实践已经深度融入企业运营。各行业的领先企业正通过这种方式实现快速转型和增长，进一步强调了DEI对企业文化和绩效的重要性。下面是全文，请欣赏： As the WSJ has reported extensively, companies like Harley Davidson, Tractor Supply, Walmart, and McDonalds are publicly pulling back on DEI programs, largely under pressure by political activists. Fueled by the supreme court’s striking down of affirmative action in 2023, there is a political movement to dismantle the “social justice” movement that took hold in corporate HR departments. Now, driven by the new administration, the Federal Government is “ending radical and wasteful” government DEI programs. And the executive order is asking the Justice Department to litigate up to 9 private companies as examples. As a part of this plan, each agency shall identify up to nine potential civil compliance investigations of publicly traded corporations, large non-profit corporations or associations, foundations with assets of 500 million dollars or more, State and local bar and medical associations, and institutions of higher education with endowments over 1 billion dollars. Of course this has created a firestorm of debate, and many companies are doing away with dedicated DEI roles in HR. But our research, which includes discussions with many dozens of Chief HR Officers, heads of recruitment, and others, finds that the investments are alive and well. Here’s where I sense we are. While DEI and pay equity programs have been around since the 1960s (companies like Coca Cola and Google have been sued for gender and racial pay inequities), the topic got out of hand. Post George Floyd, which was a traumatic event in the United States, companies went overboard with training and messaging about social justice, oppression, micro-aggression, and other uncomfortable topics. Many programs included discussions of topics like “white fragility,” “intersectionality,” “oppression,” and other social topics. While this was trending in the media, many employees told us these programs made them uncomfortable. In a country like the United States (I just got back from two weeks in South Africa, where these issues are front and center) where we have a long history of immigration and diversity, this topic has been debated for hundreds of years. I worked at IBM during the days of affirmative action (1970s and 1980s) and my personal experience was very positive. Black and Asian professionals were actively recruited and promoted at IBM during my tenure and I have fond memories of IBM as a company with a powerful culture of “respect for the individual” (IBM’s motto). (Read Thomas Watson’s 1963 manifesto: it’s a bit gender-biased but remains relevant today. Watson, the founder of IBM, talks extensively about equity between white and blue collar work, fair wages and benefits, and opportunities for all. Note that IBM is one of the only tech companies that has survived more than 100 years so these principles have served the company well.) Now that we’ve entered a business focus on productivity, AI, and technology transformation, companies want to build a culture of meritocracy, skills, leadership, and internal mobility. The #1 issue we hear from CHROs and CEOs is “how do we transform our company faster?” Sitting around to debate diversity targets or DEI agendas just doesn’t feel important. That said, as we discuss regularly with leaders in every industry, CEOs and CHROs are very concerned about corporate culture. The new Edelman Trust Barometer describes a shocking drop in trust among workers. More than half of all employees believe CEOs are overpaid and 68% believe they lie on a regular basis. So cultural topics of inclusion, fairness, and respect are extremely important. (The Edelman research even points out that 40% employees believe that hostile activism against their employer is acceptable (violence, property damage, social media attacks). So building a culture of trust, transparency, and listening remains essential. And that’s why culture still matters. As I discuss in our research “The Rise of the Superworker,” (and PwC’s 2025 CEO survey also points this out), companies that transform faster make more money. And transformation, regardless of the technology behind it, is always dependent on people. So when we read about corporate transformations at companies like Boeing, Intel, and Nike, we know that there are always issues of culture. Where does the DEI agenda now fit? As I talk with leaders around the world, it has clearly not gone away. Today, rather than focus on representation targets or social issues, companies are embedding their focus on meritocracy within the business, moving it out of the world of an “HR program.” And this, despite the political backlash, is a good thing. As even Robby Starbuck points out, every leader believes in meritocracy. We want our teams to reward high performance and encourage everyone to learn, grow, and advance in a fair way. DEI, which became a standalone mission of its own, is now a part of “building a culture of performance,” and that means respecting high performance among all genders, races, disabilities, and ages. It means creating a culture of psychological safety where people can speak up, and it means being crystal clear with feedback, accountability, and behaviors we value. Finally, let me celebrate the public statement by Jamie Dimon, one of the most respected CEOs in the world. When asked about DEI activists at the World Economic Forum, he answered “bring them on, we’re proud of what we do.” While much of the political focus against DEI seems to focus on “moving companies to the right,” I think the real trend is quite different. Leaders and HR departments are taking the high-profile DEI agenda and embedding it into the disciplines of leadership, recruitment, performance management, and rewards. And even today, as Lightcast data shows, there are more than 7,000 DEI roles posted for hire. The highest performing companies in the world are inclusive and fair by nature – that’s why high-performers want to work there. Let’s let “DEI” as an HR agenda move aside, and move the topic back into the business of leadership where it belongs. (Listen to real-world case studies in The Josh Bersin Academy or browse all our DEI research in Galileo.)

Josh Bersin
2025年01月27日
Josh Bersin

超级员工的崛起 -The Rise of the Superworker: Delivering On The Promise Of AI 《超级员工的崛起》研究报告揭示了AI如何深刻改变工作场所与工作方式。随着AI技术融入工作流程，传统工作模型被重新定义，AI正助力“超级员工”以创新的方式提升生产力和创造力。报告指出，企业若想在AI时代中保持竞争力，必须重新设计工作与组织模式。首先，需要通过AI实现任务自动化并提高工作效率；其次，推动工作流程的整合，利用智能代理提升整体生产力；最后，培养员工适应变化的能力，推动动态化的工作环境。 AI并不是简单地取代工作，而是通过赋能实现员工能力的跃升。例如，一些企业利用AI快速生成培训计划，将原本需要数月的工作缩短为数天。报告也强调，随着AI成为“同事”，全新岗位将随之出现，如知识库维护员、AI数据隐私与伦理管理者等。为了迎接这一变革，报告提出了五大关键战略：重新设计工作与组织模式，构建动态人才模型，调整薪酬与绩效体系，加强以人为本的领导力，以及加速系统性HR®的转型。只有将技术与人的因素完美结合，企业才能成功实现AI转型。报告强调，AI的核心并非技术，而是通过创新推动人与组织的共同成长。1月28日的发布会将深入剖析这些趋势与战略。 We’re excited to launch our groundbreaking research “The Rise of the Superworker,” a deep dive into the impact of AI on the future of work. As our hallmark research for the year, it defines the roadmap for leadership, technology, and HR. (Register for the launch webinar on January 28.) The Workforce and Workplace Environment We are entering a year of political change, economic disruption, and changing labor markets. As I discussed recently (The Tumultuous Year Ahead), the world is experiencing talent shortages in front-line and blue collar work (US unemployment remains at 4.1%) while white-collar employment is softening. CEOs are investing in AI in a quest for productivity and workers are asking to be retrained. And many core values (diversity and inclusion, pay equity, remote work) remain challenging. Companies believe that AI will transform their business, so investment in technology is exploding. Yet as history tells us, this “trillian dollar AI-based re-engineering” effort is about people, not technology. As the research points out, the AI revolution, as exciting as it feels, is all about redesigning the way we get things done. And that lands in the laps of HR: how we redesign, reskill, and redeploy people in a world of highly intelligent systems. Understanding The Superworker and The Superworker Company Let’s start with the basics. Companies are filled with business processes, tools, and job models designed around traditional people-centric work. Every job function, from sales to marketing to manufacturing, has been designed around the old-fashioned job families of the past. In other words, we’ve run our companies as “people machines.” We design a set of jobs and job families, then hire, train, and promote people to grow. This model creates a sprawling company filled with skills challenges, people wanting promotion, and fragility as the business goes through change. The digital revolution, which defines the last 27 years of transformation, did speed things up. It automated many processes and opened up the ideas of self-service, e-commerce, and direct consumer transactions. But it didn’t fundamentally change how companies are organized: rather it accelerated the processes we had. Suddenly, with AI everything is different. As the most intelligent and data hungry technology ever, AI stands to integrate and redefine every business process and “superpower” every employee. And this shift, toward copilots, agents, digital twins, and intelligent platforms, forces us to rethink how we’re organized, what we do, and what we define as a “job.” We are building a company of Superworkers. What exactly is a “Superworker?” A Superworker is an individual who uses AI to dramatically enhance their productivity, performance, and creativity. As routine work gets automated, AI has the potential to empower everyone, eliminating some roles while empowering many others. A “Superworker company” is an organization that embraces this transformation, building a culture of adaptability where people reinvent themselves. Our new Dynamic Organization research shows that such change-ready companies outperform their peers by six-times. Just as Superman Clark Kent learned to channel his powers, we must learn to harness AI for individual and team performance. This means not just automating existing tasks, but rethinking how work gets done, empowering people to do more, and creating opportunities for growth. The Historical Perspective: From Automation to Autonomy We’ve seen waves of automation before, but this time it’s different. In the past we used machines to automate the work of craftsmen and tradespeople. A welder, farmer, or shoemaker had his or her expertise built into a machine so their craft could scale at low cost. The expert didn’t go away, rather he or she helped design the machine. AI does the same for white collar work. Writers, analysts, marketers, and sales people are now superpowered, leveraging their skills to drive scale. AI will not replace these special individuals: it empowers them to scale and expand their impact. But in the case of AI we go further: it doesn’t just automate tasks; it becomes a co-worker itself: listening, learning, reasoning, and acting. So new and better jobs are created, designing, training, and managing the AI. And the shift to Superworker happens everywhere: from the retail clerk to the nursing supervisor to the senior executive. The New Corporate Imperative: Redesign Work and Jobs This transformation won’t happen without effort. Today, as AI systems still mature, our challenge is not implementing AI, but redesigning jobs, and business processes around AI. And that’s why success with AI is a people problem, not a technology one. And if you don’t get this right, your AI transformation will lag. Academic studies show that 45% of change management programs fail, and 72% of the reason is “people resistance.” So consider this: For each dollar spent on machine learning technology, companies may need to spend nine dollars on intangible human capital,” Erik Brynjolfsson wrote in 2022, citing research by him and others. Consider the four stage model below, where we look at “current jobs” vs “re-engineered jobs” on the horizontal, and level of output on the vertical. AI transformation begins with assistance, then moves to augmentation, then to work replacement and then to autonomy. The level of performance improvement goes up exponentially. This process of rethinking business processes takes time. When electricity was invented companies replaced horse-driven machines with motors. Decades later engineers realized we could redesign the entire manufacturing process by integrating the entire supply chain. The same will happen again. We may start by automating emails and data access, but over time we build “digital twins” and configurable agents to manage entire projects and business processes. One of our clients built an entire platform that can interview stakeholders, import documentation, build training programs, and publish training and certification programs by AI. Humans are still needed, but now they’re the “super-curators” and “craftsmen” perfecting the product. New programs that took 3-6 months can be generated in a few days. This kind of redesign is now being used for claims analysis, sales enablement, RFP generation, and workplace design. (Our report 100 Use Cases For Galileo explains dozens of such solutions available now for HR.) The Work Redesign Challenge How do we get there? Business and HR teams work together, following these stages. Improve efficiency at current job: Use AI to make existing work more efficient: same job as before, new tools to make it easier. Examples include an office worker using MS Copilot. Automate tasks to increase scale: An engineer uses AI to write code. A marketer builds videos and campaigns automatically. An HR manager rapidly builds job descriptions or analyzes performance. Integrate processes to improve productivity: Agents now handle multiple connected steps. A retail clerk automatically checks out customers; a nurse uses a machine to monitor dozens of patients and make diagnostics; an HR manager builds learning programs in minutes. Leverage autonomy for more: The AI manages multi-step processes (customer service, candidate communications, recruiting, campaign design) and the people “manage” the digital employee. This creates four types of Superworker: An Example: The HR Business Partner Consider the role of HR Business Partner (HRBP), a complex job that’s constantly changing. An HR business partner (HRBP) equipped with AI like Galileo™ can automatically analyze turnover, productivity, individual performance, and leadership potential. The AI HR Agent can help compare job candidates against multiple requirements. Analysis, coaching, and hiring speed goes up, and the HRBP is now a Superworker. Then the transformation continues. What if we give the AI to managers. Do we need the HRBP at all? (IBM has made this step.) Yes, now the HRBP manages the AI. Just as Wayze may drive you automatically, someone behind the scenes is monitoring your trip to help you when things go wrong. This “Superworker” job is the upgraded role of the HRBP. AI As A Job Creation Technology Many new jobs will be created. Who maintains the knowledge base that feeds the AI? Who ensures data privacy and security? Who handles the ethical issues that arise? Who monitors the AI to make sure it’s trained well? And once these multi-step digital employees exist, who will manage them? These are new Superworker jobs. Five Imperatives for 2025 How do we make this transition a success? Here are five key imperatives detailed in our study: Redesign Work, Jobs, and Organizational Models: Focus on the customer, how success is measured, then apply AI. This is what we call “productivity-based job design”. Deconstruct work into activities, evaluate AI solutions, and determine the human role alongside AI, using the models above. Create a Dynamic Talent Model: The traditional “prehire to retire” model is becoming obsolete. We need a more dynamic approach where people move across roles and projects. Prioritize internal mobility and foster a culture of growth. Focus on “doing more with what we have” by upgrading the productivity of our existing workforce. Focus on building “talent density“. Rethink Pay, Rewards, and Performance: Move from traditional pay models to “systemic rewards,” based on role, skills, and output. New roles may warrant higher pay, not lower. (Lightcast sees a $45,000 premium for workers with AI skills.) Refine Leadership and Culture: Focus on human-centered leadership: this is a time of change. Ensure leaders understand AI, foster innovation, and focus on productivity, not headcount. Start co-design projects in every functional areas. Get line employees involved in transformation efforts. Accelerate the Shift to Systemic HR®: HR must operate in a consulting role. Integrate HR silos, develop a change-enablement team. Experiment with AI tools in HR and train the HR team about AI. Let me give you an example. One of our large clients, a healthcare company, created a “transformation enablement” team in HR that does co-design workshops throughout the business, helping with process redesign, role design, job changes and pay and rewards changes. They built a set of tools and methodologies which are well established. HR professionals rotate into this team for education. Every HR function should set up “AI transformation teams” like this. AI isn’t here to replace us; it’s here to empower us. How To Get The Research and Learn The Rise of the Superworker predictions report is available to all users of Galileo™, The Josh Bersin Academy, or Corporate Members. (A Galileo Pro membership is only $39 per month, and JBA membership is $49 per month.) If you want to learn more and follow our ongoing case studies, briefs, and AI tools, download the Rise of the Superworker Overview today. You will be registered for regular updates. And please register for our launch webinar on January 28 where I will detail this entire story. The Superworker era has arrived, join us in the journey!

Josh Bersin
2025年01月16日

Josh Bersin

How To Make Productivity Soar: Four Stages of AI Transformation We’ve been doing a lot of advisory work on skills and job design and now that AI tools have arrived, we’re reinventing work faster than ever. So let me give you some thoughts on this process, and you can also learn more from my recent podcast. As you know, there are many types of AI business tools: Copilots, Assistants, Agents, Talent Intelligence Systems, and embedded applications. Each of these products are built on an AI-first foundation and they layer on domain expertise, use-case analysis, and iterative design to build smarter and smarter systems. Self-driving cars started as voice assistants, automatic braking, and lane warnings. Now they keep you in the lane and slow your car when the speed limit changes. And soon enough they’ll be driving for us, so we can sit in the back seat and read a book. Our HR Assistant Galileo started as a research and problem solving tool, and it’s rapidly becoming an AI coach, benchmarking tool, recruiting, and change management system. So all these tools go from simple use-cases to deeper applications and autonomy over time. As the tools get smarter and more domain focused we are going to have to rethink our jobs and business processes. And unlike ERP, where we essentially trained people to “adopt” the system, now a lot of the groundbreaking applications come from the bottom up. Individuals will discover capabilities for AI and then apply them in increasingly innovative ways. And over time, as they get smarter, our jobs move more to “supervisors” and “trainers” of AI, not just consumers. For example if our self-driving car took a bumpy route, we may “retrain it” to take a longer but smoother road. As I discuss in the podcast, I believe there are four stages of adoption today. And we’re in the middle of doing all four at the same time. Level 1: Make existing work easier. (Same job, better tools.) This is where we click on the Microsoft Copilot or Zoom or Teams and the system analyzes a meeting, summarizes emails, or writes a document with our help. We do our jobs the same way we did before, but we now have a “super-productivity” tool to make it easier. These “add-on” use cases are emerging everywhere, and they already feel like a commodity. In most cases employees see 10-15% or more improvements here, but life isn’t that much different. And sometimes the tool slows us down (Copilot doesn’t create slides well at all yet) and may actually get in the way. But we can expect this mode to continue and most of us figure this out on our own. Level 2: Major steps eliminated, but the job is the same. (Same job, tools eliminate work.) At level 2 we automated a lot. Software engineers now use copilots to develop 70% of their code, so they’re spending more time testing and prompting the AI. Their individual coding skills may atrophy, but they can now work on more architectural issues. The “job” of software engineer may still be the same, but the output is far greater. So we’re making the same pay, doing the same work, but using highly automated tools. This includes scenarios like chip designers, software engineers, supermarket checkout clerks, nurse scheduling jobs, and even recruiting assistants. Paradox customers, for example, virtually eliminate “scheduling assistants” for recruiting. At this level companies can see 50-75% productivity improvement, and free time to focus on quality management, customer service, and ongoing improvements to the tools. Level 3: Re-engineered work, partnered with agents. (New job, redesigned process, agents automate work.) At level 3 we go further: we re-engineer the process and the work. Imagine how McDonald’s replaced its counter workers with a kiosk, eliminating the “may I take you order please?” role. This took some major design effort but resulted in a whole new set of roles, workflow, and management structure in the restaurants. The “cost per burger” went down, and the customer experience is almost as good (not quite). Here we need to be careful because sometimes the “self-service, AI-enabled” experience doesn’t work. A good example is the supermarket self-checkout. It rarely works well and usually takes longer than standing in line. But it will get better, and the resulting experience is faster throughput, more data (the self-service agent might offer you a discount since it knows your buying history), and far superior employee roles. In level 3 the employees are still involved, and we are more or less “working with the machine,” aiding and supporting the process. Level 4: Autonomous intelligent agents, people training and managing the AI. (New job, redesigned process, people “manage” the agents.) At level 4 we go even further. Imagine an AI recruiter (Paradox does this) that could email a hiring manager and his team, gain feedback and requirements on a job and role, consolidate input, and create a total description. This Agent could then review this job against the company culture and pay policies, compare the job against similar jobs in the external market, and tweak the level, job title, and description to be competitive. And then it could start sourcing, and give the hiring manager and human recruiter a set of candidates ranked by various criteria. That process, which takes dozens of steps for a recruiter, could be fully automated and vastly improved. The Agent could even look at prior hires and get even smarter about who to source based on the success of other candidates. Now the human job is to “train” and “monitor” and “manage” this AI Agent, who has effectively become a digital employee. (Note: Salesforce is doing a terrific job of building this out for sales and service.) The Rise of the SuperWorker Our thesis is that AI is not a “job-replacement” technology, it’s a “SuperWorker empowerment” technology. In other words, most of these scenarios result in higher value jobs, higher pay, and value creation (not cost reduction) in the business. This is happening fast. We’re in the middle of a big study in this area and I’ll be explaining this more in our upcoming 2025 Predictions report. The upside of all this will be new and higher paying jobs, faster response to business change, but a lot of IT, design, and data management to do. But based on our research, this is coming soon.

Josh Bersin
2024年12月01日
Josh Bersin

HR：清醒吧！员工更信任AI而非HR 多年来，我一直是HR的支持者和朋友。在与HR团队的每次交流中，我都对他们的热情、投入和善意印象深刻。然而，尽管我们尽了最大努力，一项针对851名职场专业人士的最新调查发现，“员工更信任AI，而非HR。” 什么？这怎么可能？在你否定这个结果之前，让我解释一下数据。这并不像表面看起来那样简单。数据揭示了什么？ 1. AI被认为更值得信任当被问到“你更信任AI还是HR专业人士”时，54%的受访者表示更信任AI，而27%表示更信任HR。这个数据虽然听起来奇怪，但实际上反映的是“信任”的问题。员工知道经理有偏见，因此任何由HR提供的绩效评估、加薪或其他反馈可能都会受到某种偏见的影响（甚至是近期偏见）。而AI没有“个人意见”。在基于真实数据的情况下，它的决策往往更“值得信赖”。65%的受访者相信AI工具会被公平使用。这很合理：我们已经从认为AI会毁灭世界的担忧中跨越了鸿沟，现在更多地将其视为统计和基于数据的决策系统。而且你可以问AI“为什么选择这个候选人”或“为什么这样评估这个员工”，AI会给出精准且明确的答案。（而人往往难以清楚地解释自己的决定。） 2. AI已被信任用于绩效评估尽管目前市场上可用的AI绩效评估工具还很少（如Rippling的工具），但39%的受访者认为AI的绩效评估会更公平，33%认为基于AI的薪酬决策不会有偏见。同样，这很可能是因为AI能够清晰地解释其决策，而管理者往往依赖“直觉”。 3. AI更受欢迎作为职业教练当被问到“你是否重视AI工具在职业目标设定方面的指导能力”时，64%的受访者表示“是”。这再次表明员工对反馈和指导的需求，而这是许多管理者做得不够好（或者不够开放）的地方。这不是对HR的否定，而是对管理者信任度的质疑对我而言，这些数据揭示了三个重要点，每个都可能让你感到意外： 1. 员工对管理者的决策能力存疑我们并不总是信任“管理者”在招聘、绩效和薪酬方面做出公正、不偏不倚的决定。员工知道偏见存在，因此希望有一个系统可以更公平地选择和评估他们。 2. AI从“令人恐惧”到“被信任”的转变我们已经跨越了“AI令人害怕”的心理鸿沟，开始更多地将其视为可信赖的工具，这使得企业可以更大规模地将AI用于人事决策。 3. HR需要迅速适应AI时代对于HR部门来说，前进的方向已经明确。我们现在必须立刻学习AI工具，将它们引入最重要的HR领域，并投入时间去管理、培训和利用这些工具。关于HR赢得信任的能力，现在的逻辑变成了这样：公司内部支持和信任的建立将越来越依赖于HR如何选择和实施AI系统。员工的期望很高，因此我们必须满足这些需求。不管你喜欢与否，AI正在改变我们管理人的方式。

Josh Bersin
2024年11月21日
Josh Bersin

Josh Bersin:通过效率实现高速增长：新时代的主题最近的选举中，各种信息混杂，但有一条呼声响彻领导人的耳中：美国政府必须提高效率。美国选民似乎对芯片和基础设施法案上花费的数十亿美元并不感冒：他们想要的是更低的税收和更负责任的政府。正如埃隆·马斯克所解释的那样，降低成本是一项涉及数千个细节的工作。每当你聘请一名经理，就会产生更多的费用中心。本周，亚马逊首席执行官安迪·贾西 (Andy Jassey) 宣布他希望减少经理人数。正如我在最近的 HBR 文章（通过力量倍增器发展你的公司）中所讨论的那样，如果你围绕“更少的人”进行设计，你的公司实际上可以发展得更快。围绕更少的员工来优化公司意味着什么？这意味着要改变很多事情：在没有组织发展计划的情况下，不要分配员工不要在发展前就招聘员工并期望收入会随之而来（Salesforce招聘 1000 名销售代表来销售 AI？）迫使管理人员在基层实现自动化，并不断重新思考岗位职责消除复杂的职位名称，减少级别，以便于人员调动停止根据“控制范围”支付管理人员的薪酬——根据产出、收入、盈利能力或增长进行评估加倍投资培训，并开始在不同的职业类别之间进行交叉培训告诉那些请求增加员工数量的领导“重新考虑减少员工数量的计划” 用奖金支付员工工资，避免根据绩效高薪加薪（这会使不公平制度化）大力投资人工智能和自动化测试项目，让一线员工给你出主意除非你有非常明确的商业案例，否则避免大规模的 ERP 升级培育精英管理文化，奖励人们的技能和表现，而不是“达到目标”。许多人力资源实践必须进行调整。最重要的是人才密度的理念，让每个人都能表现出色……并重新思考我们的招聘方式，这样我们就不会在不知不觉中招聘了太多员工。我们从小就接受这种古老的钟形曲线观念：只有 10% 的人能被评为 1，20% 的人被评为 2，依此类推。这个愚蠢的想法本应迫使人们竞争，这样人们就会争相获得备受推崇的 1 评级。虽然这在逻辑上说得通，但效果却适得其反。如果你相信（就像我一样）每个人都能成为高绩效者，那么这种制度会伤害最有抱负的人的绩效。每个员工都能在合适的角色中发挥出超强的表现。研究表明，真正的团队表现遵循“力量曲线”——少数人（篮球界的勒布朗·詹姆斯或斯蒂芬·库里）的表现比其他人高出 10 到 100 倍。其他团队成员见证了他们的成功，并找到了属于自己的“超强表现”角色。如果所有高评价的位置都被占满，其他人的动力又是什么呢？我们希望每个人都能感觉到自己可以成为超级明星，我们希望公司能帮助他们找到这个机会。我们招聘员工时，不是以附加的方式满足“缺少的技能”或“缺少的人数”，而是以“力量倍增效应”为目的。新员工是否会成倍地提高整个团队的绩效？或者他们只是“填补了一个看似空缺的职位”。后一种做法是走向官僚主义的旅程；前一种做法是超级竞争性增长的秘诀。（我们称之为“人才密度”）为什么现在提出这些观点？在一个员工减少的世界里，我们所有人都将面临人才短缺的问题。随着AI的加速发展，我们必须把公司视为由超高绩效员工组成的网络。我无法预测联邦政府将会做些什么，但希望这些有启发性的思考能够影响华盛顿。是的，我们还有工会等问题需要考虑，但即使是世界上最大的机构也有其局限性。如今，自动化触手可及，任何“大公司”都可能受到小公司的威胁。因此，越早开始“精简”思维，越能获得优势。作者：Josh Bersin

Josh Bersin
2024年11月13日
Josh Bersin

LinkedIn推出AI招聘助手：重新定义未来招聘流程 LinkedIn Enters AI Agent Race With LinkedIn Hiring Assistant LinkedIn推出了首个AI Agent : Hiring Assistant，旨在帮助招聘人员重新成为招聘人员。 LinkedIn于本周推出了全新的AI招聘助手，这款工具旨在自动化招聘过程中高达80%的工作，特别是候选人筛选和招聘前的步骤。通过与LinkedIn平台的无缝集成，这款助手不仅提高了招聘人员的工作效率，也显著提升了候选人的质量。该工具的“体验记忆”和“项目记忆”功能，可以记录招聘人员的搜索和操作习惯，并将所有与招聘项目相关的信息进行整合，从而智能化地优化招聘流程。这款助手已经在西门子、Canva等公司的招聘流程中得到了应用，这些公司报告称，通过LinkedIn招聘助手，招聘人员的生产力显著提升，候选人质量也得到了极大的改善。招聘前的AI辅助搜索仅需30秒即可完成，而传统的搜索通常需要15分钟。 LinkedIn招聘助手还通过AI驱动的沟通功能改善了候选人的体验。数据显示，使用AI辅助发送的招聘信息的接受率提高了44%，接受速度也加快了11%。此外，AI搜索的候选人接受率高出18%。随着越来越多的公司采用AI技术，招聘与候选人之间的竞争日益加剧。求职者也在利用AI工具优化简历，甚至在面试中使用AI辅助表现，从而使HR在筛选候选人时面临更多挑战。因此，LinkedIn招聘助手等工具正成为招聘人员不可或缺的助手。 LinkedIn招聘助手不仅仅是提高效率的工具，它真正的价值在于解放招聘人员，使他们能够专注于与候选人和招聘经理的对话，改善雇主品牌，并更好地了解就业市场。这种转变反映了人才获取的战略性转变——从执行角色转变为人才顾问，帮助公司更好地实现增长。详细请看Josh Bersin 写的这篇介绍 As I discussed in the article Digital Twins, Digital Employees, Agents Everywhere, tech vendors are creating AI-powered Agents as fast as they can. And in HR, where we deal with hundreds of mundane checklist-types of processes, the opportunity for automation is everywhere. This week, just as Microsoft launched a tools to help companies build Agents in Copilot, LinkedIn announced its Hiring Assistant. And this is a pretty amazing product. The Hiring Assistant is the first highly-integrated agent I’ve seen that fits right into the LinkedIn workflow. And the companies using it now (Siemens, Canva, AMS) are seeing recruiter productivity and candidate quality skyrocket. Here’s how to think about it: consider a schematic of the recruitment workflow. As you can see, there are more than 30 steps to complete, and this doesn’t even include background checking, offer-letter generation, benefits discussions, pre-boarding, and onboarding. With this brand new Assistant LinkedIn believes they can automate almost 80% of this pre-offer workflow. And the LinkedIn Hiring Assistant is just getting started. Here are some screenshots of the workflow: As you can see, the agent prompts the recruiter with intelligent responses and questions along the way. And throughout the process it stores more and more information to get smarter and smarter. This Is A Sophisticated Product This is a well-engineered product. Not only does it include many subtle features (ie. “find me a candidate like Joe,” which brings in Joe’s profile and analyzes Joe’s role, skills, and experience), it includes several platform innovations. The first is something LinkedIn calls “Experiential Memory,” storing the recruiter’s search and activity history for future work. The Hiring Assistant learns what this recruiter is doing, how they communicate, and how they operate, to tune its results to each recruiter’s needs (ie. a tech recruiter vs. an executive recruiter). Second is a feature called “Project Memory,” which brings together all the information about a single search project. This means the candidate selection criteria, emails, and input from hiring managers are stored in the project, enabling the assistant to see the whole experience of selection. Recruiters understand this challenge: every hire and every hiring manager is different, and each project has unique and sometimes new requirements which have nothing to do with the job description. Other Agents Will Have To Take Notice LinkedIn is not the first mover in this space, but the company’s credibility will accelerate the market. Paradox, the current leader in recruitment automation, has been automating high-volume recruiting for almost a decade and offers an agent that not only helps recruiters but also supports job seekers. It isn’t focused on sourcing liked LinkedIn, but it automates the rest of the process (candidate inquiries, interview scheduling, assessment, onboarding). And it really works: this week Chipotle announced that Paradox’s solution reduces time to hire by 75%, making it a central part of the company’s growth strategy. LinkedIn Hiring Assistant is receiving similar accolades. “Doing a normal search before AI took upwards of 15 minutes. Now, with AI-Assisted Search, it takes about 30 seconds to get results. The time saved is tremendous. It is so much more convenient and easier doing it this way,” said Victoria Östryd Söderlind, Senior Recruitment Specialist, Toyota Material Handling Europe. “The AI features on LinkedIn have allowed our recruiters to do more, to be better and to grow faster in all of our activities. It’s about spending time in the right places where our time is more valuable and LinkedIn’s AI features have enabled us to do that. What it’s not doing is removing great conversations with candidates, stopping our ability to ask them questions or getting to know candidates as people and humans,” said Olivia Brown, Head of Talent Acquisition, Octopus Energy. Improving Candidate Experience While LinkedIn talks about the value to HR, the bigger value may be for candidates. The company found that AI-Assisted outreach messages generate a 44% higher acceptance rate and are accepted 11% faster by job seekers. And AI-based searches produce 18% higher candidate acceptance. As Paradox has discovered, candidates don’t like to waste time scheduling calls with recruiters if they can avoid it. And that leads to another important issue. There is now a growing AI battle between recruiter and candidates. AS AI helps recruiters source and screen candidates, the candidates are using AI to “power-up” their resumes. One of our clients told me that almost all their job applicants now submit resumes that look eerily similar to job descriptions. Why? Job candidates are using AI also! This means is that tools like LinkedIn Hiring Assistant are more essential than ever. As job seekers tweak their identity and even use AI interview assessments to game interviews, HR has to beef up its tools to better differentiate candidates. Liberating Recruiters To Recruit And Advise The big story is actually this: while Hiring Assistant is an efficiency tool, what it really does is free up recruiters to talk to candidates. Recruiters who are bogged down with drudgery can talk with hiring managers, improve employment brand, and get to know candidates and the job market better. This is part of what we call Systemic HR: moving talent acquisition away from the “fulfillment center” role to that of a talent advisor, helping the company think about its best ways to grow. As you look at these tools and think about automation, I encourage you to read our new research on the strategic shift in talent acquisition. Automation is not just about productivity and cost savings: it’s really about liberating our minds to think and add value in new and exciting ways.

Josh Bersin
2024年10月29日
Josh Bersin

Josh Bersin :SuccessFactors Leapfrogs HCM Capabilities: AI, Skills, Talent Intelligence, And More 本周，SuccessFactors 宣布了一系列重大更新，巩固其在人力资本管理（HCM）市场的领先地位。这些新功能包括 AI 驱动的工作推荐、文本分析、绩效评估和全球工资单升级等。SuccessFactors 还推出了开放的技能系统，并与 Lightcast、Degreed 等技能供应商合作，提供更全面的职业发展工具。此外，通过整合 WalkMe，SuccessFactors 改善了用户体验，使其在实施和使用方面更具优势。Dan Beck 的领导下，SuccessFactors 持续推动 HR 技术的创新与发展。有兴趣进一步了解下 This week SuccessFactors announced a vast array of new features, focused on taking the lead in the red hot HCM war against Workday, Oracle, and others. These capabilities fall into four areas, each of which bring SAP into a leading position in many areas of the global HCM market. (Product details here.) As I learned about the release I noticed the fingerprints of Dan Beck, the company’s new president and chief product officer. Dan has been at SAP for 11 months and has accelerated the company’s technology roadmap and focus on total solutions. Let me summarize what’s new. 1. More And More AI Capabilities Built-In First, of course, is AI. Two years ago SAP announced its “Business AI” strategy, which describes how all SAP business applications are integrated and enhanced with AI. (Workday’s similar strategy Illuminate was launched a few months ago.) In the prior release SuccessFactors described 63 AI use-cases; this week they introduced 30 more. And all are integrated into Joule, SAP’s intelligent Agent. Each “use-case” is essentially an AI application and many are quite complex: automatically developing job descriptions, analyzing performance reviews, setting and aligning goals, developing onboarding, creating growth plans, and evaluating pay inequities. In other words these AI “features” are really automation workflows that each eliminate hours of work for HR professionals. Since each is also integrated into Joule, you can use them through the conversational interface. While many HR vendors are adding AI features, I find SAP’s particularly robust because they’re integrated into the entire lifecycle of an employee. SAP’s engineering focus really shows here. Some of the new features include AI-based job recommendations to job seekers (and internal employees), text analysis and editing for performance reviews, and new mobile use-cases for Joule. 2. Upgrades to Global Payroll The second set of announcements are a significant update to global payroll. SAP currently has the broadest global payroll solution in the market and now has a new UI, a Payroll Command Center, and a sophisticated AI offering called “Explain Pay Slip.” You will effectively be able to ask Joule “why has my pay changed from last month” and it will dig into all the details and explain the differences. This covers 70% or more of the questions employees ask HR service centers, so this feature has an enormous ROI. Employee Central, the company’s core HR and payroll module, now has a more integrated view of all benefits and more integrations with Joule, making the 52-country payroll system the broadest in the market. 3. Open Skills System and Launch of Career and Talent Development The third set of announcements will change the HR Tech market: SAP is formerly opening up its Talent Intelligence Hub to accommodate every skills and skillstech vendor. Providers like Lightcast, Korn Ferry, Techwolf (SAP invested in them), and Degreed can now feed the SuccessFactors skills system and SAP is going to build tools to normalize and harmonize skills. This brings SAP to parity or beyond Workday Skills Cloud: the skills model is integrated into Opportunity Marketplace, Career and Talent Development (the new version of SuccessFactors learning), and SuccessFactors job architecture, team management, performance management, and recruiting. The new Career and Talent Development offering also introduces AI-assisted career insights, leveraging skills and aspirations to find relevant jobs and career paths. The system lets managers create assignments, find and onboard internal candidates, and then use Work Zone (onboarding and enablement) to start their new internal position. This level of integration goes beyond tools from Gloat or Eightfold or others for internal talent marketplace. Several years ago SuccessFactors introduced its comprehensive skills strategy and today it’s coming to fruition. There are several major implications here. First, vendors like Eightfold, Gloat, Phenom, Beamery, and many others will have to decide how they partner or compete with SAP. Last month I met with both Delta Air Lines and Pepsi, both of which are using SuccessFactors Talent Intelligence hub as their new end-to-end platform. Each company told me that they no longer felt the need to use some of these other third party products. Second, the SuccessFactors skills model is expansive. In addition to harmonizing and helping companies build technical and leadership models, the system itself has its “whole self” module which includes aspirations, styles, motivations, and preferences. Companies that use this can add subtle human needs to the model. Other vendors have tried this (Cornerstone and Gloat both ask users to express career and personal work preferences) but SAP, with its enormous customer base, has the potential to leverage this across industries. Imagine an employee in IT who aspires to work in HR, for example – the system would find the HR Tech jobs within the company which leverage their architectural or technical skills. SuccessFactors also includes a mature system for team-based work, which is missing in these other applications. This release adds AI-assisted 360 reviews, performance templates, and integration with Joule (employees and managers can share performance information through the agent.) 4. Integration of WalkMe into SuccessFactors. The fourth major announcement is the bundling and integration of WalkMe. Given the vast and complex nature of SuccessFactors, there are many places to read documentation and learn how the system works. This forces customers to build large training programs for users. (All HCM platforms have this issue.) WalkMe, which was acquired this year for $1.5 Billion, is the leading provider of “digital adoption platforms.” It is essentially an advanced AI system that watches a user’s interaction with a system to coach, train, and automate your work. Initially developed to help users learn how to use systems like SAP or Salesforce, WalkMe advanced into a highly intelligent real-time coach, similar to what we now expect out of an AI agent. While I don’t know how this will be priced, this gives SuccessFactors an “ease of implementation” advantage. WalkMe is an open platform and does support many HCM applications, but now that it’s integrated and bundled into SAP customers will find SuccessFactors much easier to deploy and use. (Just for your reference, the SuccessFactors and Workday “how to” manuals include nearly 1,000+ pages each.) Bottom Line: SuccessFactors Leadership Emerges SAP’s ambitious, long-term engineering approach to human capital management is clear. I’ve been watching SuccessFactors since it was a small independent company in California, now growing to a vast cloud business with 10,000+ customers and more than 150 million end users. This release demonstrates how patience, engineering excellence, and relentless focus on customers pays off in enterprise software. Under the leadership of Dan Beck, SuccessFactors now offers industry-leading capabilities in most areas of HCM, giving customers an even deeper offering to consider as HR technology rapidly evolves.

Josh Bersin
2024年10月28日

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