• AI adoption
    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 adoption
    2025年12月22日
  • AI adoption
    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。
    AI adoption
    2025年12月10日
  • AI adoption
    Why AI is now HR’s business Could the AI revolution also herald a revolution in HR? Generative AI is leaving many businesses in a fix. On the one hand, the potential of the technology is strikingly obvious. Since ChatGPT debuted to the public in late 2022, AI has made extraordinary advances. Coding tools can spin up micro apps from a simple prompt. Chatbots can produce instantaneous research. Video models can create studio-grade clips. Tools like these can supercharge all kinds of work, whether it’s helping create a whole marketing campaign or simply assisting an individual reason through a thorny problem. One estimate sizes the corporate opportunity at $4.4 trillion globally. Yet it can be bewilderingly hard for enterprises to realize those gains. Studies show that generative AI is having limited impact on productivity. Many organizations find themselves either stuck in pilot purgatory, or rolling out initiatives that fail to deliver ROI. Others don't even know where to start. This issue is especially pronounced for smaller enterprises. In fact, research suggests that AI is seen as the number-one challenge by four out of five small business leaders in the UK. Small firms are half as likely to have implemented it compared to larger companies. And within the small companies that have adopted AI, usage is often uneven. Seventy three percent of senior managers use it at least once a month, compared with only 32 percent of entry-level employees. This creates what Kevin Fitzgerald, UK Managing Director of the all-in-one employment platform Employment Hero, calls the “AI advantage gap.” “AI is only delivering productivity gains for some, and that’s a huge problem,” he says. “For technology to drive meaningful change, it needs to be in the hands of everyone.” Human resources (HR) departments are uniquely positioned to help manage some of the challenges around AI adoption. That’s because taking full advantage of the new AI tools available to organizations is more than just an IT project. “AI is all about job redesign, new skills, new organization structures, and new roles for leaders,” says Josh Bersin, a respected HR industry analyst and CEO of HR consultancy The Josh Bersin Company. “HR people are essential as part of companies’ AI transformations.” In practice, this kind of project tends to be easier for smaller businesses, which have fewer employees and less organizational complexity to disrupt. Bersin says that Chief Human Resources Officers (CHROs) now frequently lead AI-based organizational redesigns. Going further, almost two thirds of IT decision-makers expect their HR and IT teams to merge in the next five years, according to a recent survey. This is already happening at companies such as Moderna, the biotech firm with more than 5,000 employees, which now has a single leader covering both. “HR has a once-in-a-generation opportunity to reshape the future of work,” says Fitzgerald. “And it’s important to get this right. Bad AI rollouts can slash personal productivity in half.” So what does HR-led transformation look like in practice? Here we spotlight three ways HR leaders can set their organization up for AI success… 1. HR as pioneers Leading on AI transformation means deeply understanding training needs, integration challenges, employee resistance and—fundamentally—how and where AI offers value. This means HR professionals need real experience of those things themselves. There are many HR tasks to which both traditional machine learning and generative AI is well suited. Much of the press buzz is around recruitment—using AI to source candidates, screen CVs, and automate parts of the application process—but its impact can be much broader. The creative and communication side of the job is a natural fit for the capabilities of large language models (LLMs), which excel both in summarizing and expressing information. Whether it’s drafting job descriptions, communicating complicated policies in plain language, or managing the team’s internal knowledge, there’s plenty that an LLM can help with (so long as it offers appropriate privacy assurances). There are a range of options for deployment, from buying tools that package up an LLM for delivering on a specific use case—such as offering AI training programs or building FAQ chatbots—to simply subscribing to a frontier AI assistant like ChatGPT. The most immediate benefit is the potential gains for the HR team itself. Handing off repetitive tasks to AI can free up time. But it’s also the baseline for any HR team that is planning on leading the way in a business’ AI transformation, because credibility will be vital. That’s not to say that it should only be HR leading the charge on AI—Bersin says that more often than not having a dedicated committee with representatives from HR, legal, and IT is most effective—but it’s a necessary criterion for playing a central role. “It’s about leading by example,” says Fitzgerald. “People don’t want technology forced on them—they want to see its benefits, and be given the freedom and encouragement to explore it.” Of course, much of HR’s AI usage will be internally facing, so there’s a comms job to be done. “My advice to the HR leader would therefore be: share,” says Fitzgerald. “Share the wins that you've had, and actually put them out there to the broader business.” 2. HR as culture definers Establishing the right culture around AI is vital. “It’s the missing link in AI adoption,” says Deepali Vyas, Global Head of Data & AI at global talent advisory firm ZRG. There are two crucial reasons for this. The first is that when a company chooses to roll out AI, it can create ill feelings. People can fear it’s a prelude to cost cutting and job losses. Of course, an organization may be planning to downsize—but equally it could be planning to do more with the same number of people. Whatever the plan, be transparent. If nobody needs to worry about their jobs, tell them. If a restructure is likely, fair dealing and honesty can go a long way to attenuating resentment. HR has the authority and the skills to lead on conveying this information in the most effective and appropriate way. The second reason concerns “shadow AI.” This is where employees use AI tools of their own without telling management, either because they fear for their jobs or because they view AI as a shortcut and don’t want to pull back the curtain on how they get things done. Shadow AI is already widespread; the security firm Varonis estimates that up to 98 percent of employees use shadow AI or shadow IT in some capacity, with employees hiding their AI use out of fear of their employer's reaction. While the primary risks of shadow AI are to do with security and privacy, there is also a more systemic drawback. Top-down AI tool implementation can be important, but companies that don’t also tap into the wisdom of the crowd will miss out on AI opportunities. Generative chatbots are general-purpose tools with the most open-ended interface possible: there are countless different ways to use them, and the people best placed to figure out how this kind of AI can help your business are the people who work there. But you can’t enjoy the fruits of their experiments if they are unwilling to share how they’re using it and what they’re discovering as a result. “You really need to bring shadow AI use to the surface,” Vyas says. “In any case, banning or ignoring shadow AI is not going to make it disappear. It's only going to drive it further underground.” Bringing it out into the light is, again, a question of culture. If IT owns guardrails and platforms, and the C-suite owns vision and accountability, HR owns the people and behaviors piece. In addition to quelling fears that revealing AI usage will jeopardize jobs, HR needs to create forums to encourage sharing across all teams. This could take the form of workshops and hackathons or simply dedicated channels on Slack. There should also be incentives, so that individuals who come up with approaches that create meaningful value are well remunerated for their contributions. “There's a lot of fear versus empowerment,” says Vyas. “HR’s cultural mandate is building a culture of AI fluency, normalizing AI as a partner in work and to build trust around its use.” 3. HR as organization designers AI transformation is not just about rolling out the tools. You need teams with AI literacy, skills and mindsets—teams that are open to new ways of working and to reimagining workflows that have perhaps remained unchanged for decades. You may also need to create new roles like a Chief AI Officer, or hire specialist software developers. “It's about building that future-ready workforce,” says Vyas. HR’s expertise in recruitment and training will be crucial in this effort—only half of employees in SMEs believe their company has done a good job instilling technological know-how—and AI itself can play a powerful role in making a success of it. Forward-thinking organizations weave AI into workforce management, from how workers move internally to how they train and learn, Vyas says. “There’s personalized learning journeys, there's internal mobility recommendations, there's workforce planning tied to all of these business scenarios.” As they scale, companies may wish to rethink their org charts in light of AI. The traditional triangular org chart has been a mainstay since Brigadier General Daniel McCallum unveiled the first example in 1855. But many commentators believe that new architectures will coalesce to reflect how people work best with AI. Microsoft’s Work Trend Index Annual Report 2025 argues that the org chart will be replaced with a “Work Chart,” which it describes as “a dynamic, outcome-driven model where teams form around goals, not functions, powered by [AI] agents that expand employee scope and enable faster, more impactful ways of working.” In practice this means a flatter, more flexible operating model. Firms that have harnessed AI in this way report having more satisfied, more optimistic employees. HR will need to play a pivotal role in managing any such transformation. “That’s not only because most savvy HR leaders are also very good at change enablement,” says Bersin, “but also because this clearly would have implications for pay models, reward systems, and leadership pipeline.” What’s more, Microsoft argues that in a Work Chart world, orchestrating the interplay between humans and AI agents—and getting the balance right—is going to be an emerging area of responsibility for HR. In discharging this duty, they will need to collaborate more closely than ever with technical teams. This shift may seem radical. But, as the aphorism has it, it's easy to underestimate the long-term effects of new technologies. Vyas believes this kind of business architecture will just be “the new normal—and sooner than we might think”.   原文：https://www.wired.com/sponsored/story/employment-hero-why-ai-is-now-hrs-business/
    AI adoption
    2025年11月28日
  • AI adoption
    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。 -------------------------------------------------------------------------------- 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。 -------------------------------------------------------------------------------- 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。 -------------------------------------------------------------------------------- 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。 -------------------------------------------------------------------------------- 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。
    AI adoption
    2025年11月24日
  • AI adoption
    2025 年人才留任新现实：员工选择“留下”，但企业是否真正留住了人？ 最新的《iHire2025 人才留任报告》揭示了一个核心洞察：员工留下来的理由并不仅是薪酬，更重要的是“他们能否在这里成长、归属、被看见”。报告显示，自愿离职率已降至 35.9 %，但其中许多员工是因为经济环境不确定而“抱岗”而非出于真正忠诚。 在过去三年里，美国职场经历了从“辞职潮（Great Resignation）”到“谨慎抱岗（Job Hugging）”的剧烈反转。《iHire 2025 人才留任报告》为这一变化提供了最新视角：离职率下降、满意度上升，看似一片稳定，但深层结构性问题并未消失，包括文化毒性、管理质量不足、反馈机制失灵等长期矛盾。 对于正在竞争全球人才的企业而言，这份报告揭示了一个关键问题：员工“留下来”并不等于真正被留住。2025 年的留任，更多反映的是经济环境的谨慎，而不是忠诚度回归。企业若误判这种“稳定”，将面临下一轮流失风险。 一、离职率下降：稳定是假象，谨慎是真相 2025 年自愿离职率降至 35.9%，连续两年下降，形成“求稳趋势”。若将其视为企业管理改善的结果，很可能是错觉。 背后的真实驱动力包括： 经济环境不确定，员工倾向“观望”； 企业招聘放缓，外部机会减少； AI 招聘筛选加强，跳槽难度提高。 换句话说，离职减少并非“组织吸引力增强”，而是“流动成本增加”。一旦经济复苏、新机会增加或企业内部矛盾积累到临界点，潜在流失可能集中爆发。 二、员工满意度回升，但“归属感差距”成为新裂缝 调研显示 56.3% 员工对当前工作满意，较去年略升。然而，真正决定是否留下的关键是“归属感”： 53.7% 感受到归属感 在感受不到归属感者中，57.2% 对工作“不满意” 归属感不是“氛围好不好”，而是： 是否被尊重？ 是否被倾听？ 是否认为自己的工作被看见、被重视？ 这意味着留任不再依赖“薪资 + 福利”组合，而是向“体验 + 情感连结 + 成长可能性”倾斜。 三、五大决定性留任因素：薪酬不在榜首 iHire 的数据清晰揭示：员工真正留下的前五大原因是： 积极的工作环境（81.5%） 健康保险（68.4%） 工作生活平衡（63.9%） 退休计划（59.4%） 职业发展机会（57.4%） 薪资并不在前五名中。这对习惯“靠加薪挽人”的企业是一个重要提醒。 尽管 55.2% 的企业提供加薪，但只有 34.3% 的加薪真正起到挽留作用，另有 19.5% 的加薪“无效”。说明薪酬是必要条件，却不是充分条件。 四、离职的真正原因被“低估”了：管理层感知严重偏差 员工离职的前三大真实原因： 有毒文化 26.8% 糟糕的领导层 24.2% 不佳的直属经理 22.8% 但企业怎么认为？ 只有 13.4% 的企业认为文化是主因 只有 10%–15% 的企业认为管理能力是问题 这形成典型的“管理盲区”。企业高层往往将离职归因于薪酬、竞争、个人原因，却忽略自身文化与管理质量。 当企业错误判断离职原因，所有后续的留任策略都会南辕北辙。 五、真正缺失的不是福利，而是“留任机制” 报告中最令人警醒的数据是：仅 30.5% 的公司做“留任访谈（Stay Interview）”。 大部分企业只在员工离职时做“离职访谈”，这时所有反馈已经无力回天。 优秀企业在做的，是： 入职 30 天访谈 90 天访谈 季度或半年 Stay Interview 一对一领导力反馈机制 主动识别离职信号（工作习惯变化、参与度下降） 留任是一场“提前预警”的管理，而非“事后补救”的管理。 六、AI 在留任中的应用仍极早期，但将成为下一波转折点 目前： 79.5% 企业尚未使用 AI 做留任管理 但已有一小部分企业开始用 AI 做： 员工参与度分析（9%） 个性化学习发展和成长路径（8.1%） 识别离职倾向行为 虽然比例不高，但趋势是明确的：AI 不会取代 HR，但会成为留任管理的“新雷达系统”。 越早采用，越能在未来获得竞争优势。 七、给企业的留任建议：2026 年 HR 需要的不是更多工具，而是更深的机制 结合 iHire 的数据，本次报告对企业提出了七大方向，我将其总结为三条核心战略： 1. 先把基础打牢：文化、福利、成长路径三件套 这是 81.5% 人留下的根源。 2. 建立“留任早期预警系统” 包括 Stay Interview、管理培训、员工反馈、数据监控。 3. 用好 AI：从“被动应对”转向“主动洞察” 未来留任竞争将是 AI 与管理能力的结合。 2025 的留任稳定不是真稳定，是“静默风险” 员工不跳槽，不代表他们满意、忠诚、投入。很多员工是在“不满意但不敢动”的状态中“被迫留下”。 它不会引发短期波动，却会在某一天集中爆发。 对企业而言，今年的关键不是问：“员工为什么留下？” 而是问：“我们是否真正让他们愿意留下？”   原文可以访问：https://www.ihire.com/resourcecenter/employer/pages/talent-retention-report-2025
    AI adoption
    2025年11月19日
  • AI adoption
    员工体验平台的演进：推动 AI 转型的关键引擎 Josh Bersin 公司发布新研究指出：员工体验平台（EXP）正在成为企业 AI 转型的关键基础设施。EXP 不再只是HR工具，而是推动组织学习、透明沟通和员工赋能的核心平台。研究提出五大战略：以人为本、自下而上、持续学习、透明沟通和实时优化。案例包括 Microsoft 的 HR AI 转型、ASOS 的 AI 自动化、Clifford Chance 的法律文书 AI 起草。EXP 赋能组织实现敏捷变革和AI落地。 AI 正在快速改变职场——不仅是技术，更是组织文化与工作方式的深刻变革。 人工智能（AI）的广泛应用为生产力、效率和业务增长带来了前所未有的机遇。然而，AI 转型并不仅仅意味着“部署新技术”，它实际上深刻地重塑了员工体验，影响着组织文化、团队协作方式与工作流程。 在这一转型过程中，员工体验平台（Employee Experience Platform，简称 EXP） 正逐渐从传统的 HR 工具，演进为推动企业成功实施 AI 的关键引擎。EXP 不再只是一个用于请假或查政策的门户，而是集成沟通、学习、协作、数据与自动化的智能化平台，帮助组织推动 AI 采纳、提升员工准备度，并确保 AI 真正带来业务价值。 员工体验平台的演进 EXP 的初始功能主要是处理事务性流程，如请假申请、薪资查询等。但如今，随着 AI 技术的发展，EXP 已演变为智能化的交互中心，集成以下核心功能： 跨系统的员工沟通与协作 提供关于 AI 使用和员工情绪的实时洞察 支持个性化的学习与技能建设 自动化重复任务，让员工专注于更有价值的工作 同时，得益于 AI Agent 的融入，如今的 EXP 变得更易使用，员工可通过自然语言与系统交互，实现跨系统流程操作，无需再进入多个事务性系统。 因此，EXP 不再是“可有可无”的系统，而是 企业 AI 成功转型的关键基础设施。 企业 AI 转型案例 我们调研了三家具有代表性的公司，探讨他们在 AI 转型中如何借助 EXP 实现落地与成效： 1. ASOS（线上时尚零售） 部署 Microsoft Copilot 与 Microsoft Viva 赋能多业务部门 用 AI 驱动 HR 案例处理工具，提升服务效率 通过自助服务门户精简事务流程 用自定义 AI bot 自动完成可持续认证流程 成果：员工生产力提升、参与度增强、AI 无缝落地 2. Microsoft（打造 AI 驱动的 HR 部门） 通过 Viva 学习模块开展 AI 培训 自助 HR 工具增强员工支持体验 实时分析 AI 使用情况，持续优化策略 成果：HR 效率显著提升，数千名 HR 领导参与 AI 社群 3. Clifford Chance（国际律所） 用 AI 起草法律文件，为律师提供初稿 借助 AI 语言工具跨越法律语境差异 利用 AI 管理法律知识，快速找出相关案例 成果：文书效率提升、知识共享加速、决策更精准 AI 转型的敏捷性要求 与传统变革不同，AI 推广不是一次性事件，而是一个 持续试验、迭代和适应的过程。因此，企业需具备“变革敏捷性”（Change Agility），用灵活的机制推动员工学习和组织协同。 借助 EXP 实现 AI 成功的五大战略 我们总结出五个成功企业在 AI 转型过程中普遍遵循的策略，而 EXP 是支撑这些策略实施的核心平台： 1. 以人为本与目标导向（Focus on People and Purpose） AI 的导入需与组织使命、价值观和员工需求保持一致。EXP 可确保所有 AI 工具围绕员工体验设计，提升参与度、工作效率和福祉。 ? 案例：Microsoft HR 借助 Viva Amplify 定制 AI 推广内容，让 HR 团队及时获取战略沟通信息，确保 AI 项目与业务目标保持一致。 2. 采用自下而上的迭代方法（Bottom-Up, Iterative Approach） AI 转型不能靠高层指令推动，而应依赖一线员工的反馈与试验。EXP 通过实时反馈与学习机制，让员工在实际工作中试用、迭代与优化 AI 工具。 ? 案例：ASOS 借助 Viva 社区功能发起“Work Smarter”活动，员工可在平台上公开交流 AI 使用案例，形成知识共享文化。 3. 鼓励透明沟通与试验精神（Transparent Communication and Experimentation） 员工需要明确知道 AI 工具的使用场景、目的与风险，才能建立信任并积极参与。EXP 提供结构化、公开的试验机制，确保过程透明。 ? 案例：Clifford Chance 在 Microsoft Viva 中嵌入 AI 工作流程，员工可以实时测试 AI 辅助起草功能，同时了解其运行逻辑。 4. 推动持续学习与技能建设（Continuous Learning and Skill-Building） 员工必须掌握 AI 基本素养，才能有效融入 AI 工具。EXP 提供基于角色定制的学习路径，支持技能升级与长期成长。 ? 案例：Clifford Chance 借助 Viva Learning 培训员工 prompt 工程、AI 素养与数据分析技能，为 AI 工具的使用打下基础。 5. 实现实时度量与持续优化（Real-Time Measurement and Improvement） 与传统 IT 项目不同，AI 推广必须持续监测并快速调整策略。EXP 提供实时分析能力，帮助企业追踪员工情绪、生产力与 AI 使用情况。 ? 案例：Microsoft HR 借助 Viva Insights 实时追踪 AI 使用频率、员工负荷减轻情况与情绪变化，以便动态调整 AI 战略。 HR 在 AI 转型中的新角色 在 AI 重构工作的过程中，HR 部门不再只是支持者，而是： 主导员工技能升级与再培训 协助重塑岗位定义与工作流程 在 HR、IT 与业务之间架起 AI 战略桥梁 落实负责任 AI 政策，确保 AI 应用符合伦理与企业文化 HR 将在未来的 AI 时代中扮演 “战略引导者 + 管理变革催化者” 的核心角色。 行动建议与未来展望 企业若想在 AI 转型中取得成功，应当： ✅ 采用“变革敏捷”思维，持续学习、实时迭代 ✅ 建立 AI 驱动的员工体验平台，支持流程与文化融合 ✅ 打破 HR、IT、业务之间的壁垒，实现跨部门协同 ✅ 实施实时度量机制，根据反馈不断优化 AI 战略 EXP 已成为企业迈入 AI 未来的基础设施。 AI 将持续重塑职场，但决定 AI 成败的关键并非技术本身，而是组织是否能让员工真正拥抱 AI、用好 AI。 EXP 不再只是一个 HR 工具，而是打造学习型组织、推动信任建设和灵活变革的“中枢神经系统”。企业若想在 AI 驱动的时代中保持竞争力，就必须把员工体验放在战略核心位置。 作者：Kathi Enderes | 全球研究与行业分析高级副总裁 | Josh Bersin Company
    AI adoption
    2025年07月19日
  • AI adoption
    Yes, HR Organizations Will (Partially) Be Replaced by AI, And That’s Good I adore the human resources profession. These folks are responsible for hiring, development, leadership development, and some of the most important issues in business. And despite the history of HR being considered a compliance function, the role is more important than ever. CHRO salaries, for example, have increased at 5-times the rate of CEO pay over the last twenty years, demonstrating how essential HR has become. That said, we have to be honest that AI is going to disrupt our role. This week IBM formally announced that 94% of typical HR questions are now answered by its AI agent, and the role of HR Business Partner is all but eliminated except for very senior leaders. As a result the CEO plans to reduce HR headcount and shift that budget towards sales and engineering. Let’s accept the fact that we are in a time of increasing acceleration. In other words, the capabilities of AI are growing much faster than our organizations” ability to adapt, so we have to lean forward and start redesigning our companies. In the case of HR, our Systemic HR model (which we launched two years ago) is now being fully automated by AI. I know IBM’s story well, and I think it explains where all HR teams are going. Many years ago Diane Gherson (prior CHRO) started AI projects to automate recruitment, pay analysis, and performance management. She spoke at our conference eight years ago and shared how IBM’s pay tool (CogniPay was launched in 2018) uses AI to make pay recommendations based on skill. This type of tool, which was years ahead of the “skills-based” strategies we see today, essentially automated many of the performance and pay decisions left to managers.   Since then IBM has gone much further, and in my last conversation with Nickle Lamoureux (current CHRO) she told me the AI agent helps write performance reviews, creates development plans, and coaches managers and senior leaders on a myriad of performance based decisions. I totally believe this because I see Galileo doing these kinds of things for companies every day. (Check out the Mercury release.) How does this impact the roles and jobs in HR? Well it definitely eliminates many. In the case of L&D or HR business partners, I believe we could see a 20-30% or more reduction in HR headcount per employee. And that means these individuals may wind up managing the AI platforms, moving into roles as change consultants (which AI still can’t do), or move into areas like org design, learning architect, and data management. I think this is all a good thing. While we all worry about AI taking our jobs, we have to remember that our real job is not to “do things” but to “add value” and bring complex problem solving skills to our companies. And in this journey to “crawl up the value curve,” we all have to learn to use AI, develop AI solutions, and think more systemically about how our companies go to market. I recently interviewed a brilliant HR leader (podcast coming) at WPP who explained how he and his team rationalized their job architecture from 65,000 job titles to only 600 by using new AI tools from OpenAI and Reejig (a work intelligence vendor). As you’ll hear in his story, this effort was a combination of data management, business analysis, change management, and leadership. The results of this work, which are still ongoing, is the opportunity for WPP to dramatically change its go to market strategy, innovation, and growth. That’s the kind of thing we want our HR teams to do. And as these various agents hit the market (see my latest view of the market below), HR professionals are going to have to train them, implement them, and “manage them” for long term success. This means analyzing the cross-functional data they produce, extend them into better decision-making, and move our thinking from dated concepts like “time to hire” and “course completion rates” to meaningful measures like “time to revenue” or “time to productivity” or “time to customer service excellence.” See where I’m going? In a time of increasing technology acceleration we have to “lean in” as hard as we can. Stop thinking about how much money we save on headcount (which is a fleeting benefit, by the way) and focus on value creation. That’s the big benefit of AI: customer service quality, time to market, and innovation. In many ways these “HR downsizing” stories are really stores of “HR crawling up the value curve,” which is really a good thing. And for HR professionals, it’s a time for personal reinvention.
    AI adoption
    2025年05月16日
  • AI adoption
    The best HR & People Analytics articles of March 2025 2025年3月的《Data Driven HR Monthly》由人力分析专家David Green主编，汇集了全球最新的HR与人力分析领域的重要洞察。文章聚焦于“技能驱动型组织”、“CHRO领导力崛起”与“生成式AI在HR中的落地应用”等核心主题。Insight222最新研究指出，若CHRO和高管团队以身作则地使用数据，HR人员在日常工作中应用人力分析的可能性将提高三倍。Mercer报告显示，高技能效能企业中有73%建立了系统的技能目录。此外，Deloitte《2025全球人力资本趋势》强调，应在“组织文化”“员工个人成长”“企业社会价值”三者之间平衡张力。McKinsey指出，25%的企业通过应用生成式AI，HR成本下降超过10%。Josh Bersin研究则揭示，13%的CHRO已跻身企业前五高薪高管，展现出其日益增强的战略地位。本期还涵盖了关于员工体验设计、DEI策略调整、混合办公模式下的设计思维、HR技术成熟度评估、员工聆听模型等多项实务建议，是HR从业者和决策者必读的专业内容合集。 I was reflecting this weekend that I have now been in the people analytics field for over a decade. Much has changed during that time, but three constants have been the Wharton People Analytics Conference, People Analytics World and UNLEASH. All have acted as a source of inspiration to me and an unmissable opportunity to connect with others in our field. As such, I am looking forward to attending and speaking at all three events in the coming weeks. First, I’m excited to be speaking for the first time at the Wharton People Analytics Conference in Philadelphia on April 10 and 11 on Unlocking the Power of Data: The Case for Analytics Democratization. Other speakers include: Amy Edmondson, Ravin Jesuthasan, Ben Waber, Jennifer Kurkoski, Guru Sethupathy, Siri Chilazi, and Michael Fraccaro. Next up, I’ll be co-chair and opening keynote speaker at People Analytics World in London on April 29 and 30, where I’ll be sharing some of the research and work we do at Insight222. Other speakers include: Dawn Klinghoffer, Alexis Saussinan, and Cole Nussbaumer. The week after, I’ll be heading back to the US for Unleash America, which takes place in Las Vegas, and where I’ll be moderating the Unleash Talent Summit on May 6, and the AI Track on May 7 and 8. Other speakers include; Adam Holton, Anshul Sheopuri, Sue Lam, Avani Prabhakar, Christy Pambianchi, and Amy Coleman. I hope to see some of you in Philadelphia, London and/or Las Vegas. This edition of the Data Driven HR Monthly is sponsored by our friends at Mercer Putting skills to work: Benchmarking skills-powered success The scale of skills gaps poses an existential threat to businesses’ ability to get work done. The velocity and volatility of change associated with these gaps stems from compounding trends across geopolitics, climate, demographics and the AI revolution. How can organizations keep pace when supply fails to meet shifting demand? Accelerating agility is one answer. By connecting the dots between skills and the specific tasks that are changing, employers can unlock new ways to connect people to work (beyond moving them from one job to another). A skills taxonomy lays the groundwork: Mercer’s 2024-2025 Skills Snapshot Survey Report shows that 73% of companies with high skills effectiveness have a skills catalog. While technology makes skills mapping easier, the overall journey can feel overwhelming. HR capacity concerns often stop teams from taking the first step to becoming skills-powered. To put skills to work in a manageable way, think big but start small with a pilot program. This may be for a specific talent process like internal mobility or talent acquisition in the context of a fast-changing business area. Find more strategic skills insights in Mercer’s 2024-2025 Skills Snapshot Survey report, including: Building the path to a skills-powered organization Mapping skills to employees Linking skills with rewards Overcoming obstacles Get the Snapshot Enterprises who realize the full potential of Skills-Powered Organization practices use skills to revolutionize how they work, modernize talent deployment, and rethink development and rewards. Their journeys are underpinned by a shared vision and a strong data foundation. To sponsor an edition of the Data Driven HR Monthly, and share your brand with more than 140,000 Data Driven HR Monthly subscribers, send an email to dgreen@zandel.org. MARCH ROAD REPORT March turned into a month of highs and lows. Focusing on the former, the first week of March witnessed the most successful and well-attended Peer Meeting yet for member companies of the Insight222 People Analytics Program®, hosted by NBC Universal at their iconic global headquarters at the Rockefeller Center in New York. A huge thank you to Jamie Nevshehir and Jennifer Mandelson for hosting as well as our speakers at the event: Dawn Klinghoffer, Lynette Carlson, Olga Dobromyrova, Geetanjali Gamel, Anshul Sheopuri and Jeremy Shapiro. March also saw me deliver two conference keynotes in my home city of London. First up, I had the privilege of delivering the closing keynote at HiBob’s Heartcore HR event in London (see here) – thanks to Emily Hanssen Arent for inviting me and Toby Hough for hosting. The following week, I had the pleasure of delivering another closing keynote – this time at the Workhuman Forum Live – on how data-driven storytelling can elevate HR’s impact and role in shaping the future (see here) – thanks to Maya Lane and Kathryn Santora for inviting me. Join me for an Insight222 webinar on April 2 on building data literacy in HR at scale. In our research at Insight222, we have found that when both the CHRO and the HR leadership team role-model the use of people data and analytics, HR practitioners are three times more likely to use those insights in their day-to-day work. That’s the kind of cultural shift that unlocks business impact, strategic alignment, and organisational capability. If you’re interested in learning more about why data literacy is central to the success of both the HR function and the wider business—please join Naomi Verghese along with Shannon Rutledge, Director of People Analytics & Data Solutions at T. Rowe Price, and me on 2 April 2025 at 4:00 PM BST for our upcoming webinar, “Upskilling the HR Profession – Building Data Literacy at Scale”. Share the love! Enjoy reading the collection of resources for March and, if you do, please share some data driven HR love with your colleagues and networks. Thanks to the many of you who liked, shared and/or commented on February’s compendium. If you enjoy a weekly dose of curated learning (and the Digital HR Leaders podcast), the Insight222 newsletter: Digital HR Leaders newsletter is usually published every other Tuesday – subscribe here – and read the latest edition. HYBRID, GENERATIVE AI AND THE FUTURE OF WORK HELEN POITEVIN - AI in HR: Hits, Misses and Growing Pains Skills-based talent management cannot scale or be sustainable long-term without AI-enabled skills management. Writing for Gartner, Helen Poitevin presents a AI use-case prism for human capital management (see FIG 1) before providing detailed insights on AI in HR across three key areas: recruiting, virtual assistants and skills in terms of what’s working and what isn’t as well as areas requiring more focus (growing pains) and what to expect next. For example, with AI-enabled skills management, AI is helping organisations to scale and personalise but is still struggling to incorporate unstructured skills data. Helen recommends starting with the teams that are most ready for using skills data alongside creating a long-term skills vision and ambition. She also highlights that growth in the use of AI based skills management tools is set to rise: “Gartner predicts that by 2028, 40% of large organizations will have invested in two or more AI-enabled skills management solutions with the aim of delivering business agility.” Thanks to Brian Heger for highlighting in his excellent Talent Edge Weekly newsletter. FIG 1: AI use-case prism for human capital management (Source: Gartner) McKINSEY - The state of AI: How organizations are rewiring to capture value The latest McKinsey Global Survey on AI finds that the use of AI (both generative and analytical) is increasing with three-quarters of organisations using AI in at least one business function. From a people and HR perspective there are a number of takeaways from the report including these five: (1) Just over 20% of companies have created a comprehensive approach to foster trust among employees in the use of GenAI. (2) 31% of large and 17% of small organisations have established capability-based training courses designed to help employees use GenAI appropriately. (3) AI is shifting the skills organisations need with roles on risk and ethics on the rise and those in data-visualisation reducing. (4) There is an increased focus on reskilling with companies expecting this to further increase in the next three years (see FIG 2). (5) Across industries 13% of companies report they are using GenAI regularly in HR with the media and telecom sector highest at 22%. (6) 25% of companies report cost reductions in HR of more than 10% in the second half of 2025. Kudos to the authors: Alex Singla, Alexander Sukharevsky, Lareina Yee, and Michael Chui, with Bryce Hall. FIG 2: Employee reskilling due to AI use (Source: McKinsey) DELOITTE - 2025 Global Human Capital Trends: Navigating complex tensions and choices in the worker-organization relationship Organizations that successfully increase the capacity of workers to grow personally, use their imagination, and think deeply are: 1.8 times more likely to report better financial results, 1.4 times more likely to say they are creating broad value for customers, community, and society, and 1.6 times more likely to say they provide workers with meaningful work. Deloitte’s annual Global Human Capital Trends report is always insightful, thought-provoking and forward-looking, and the 2025 edition does not disappoint. The introduction sets the scene and highlights the need for organisations and leaders to find a balance between competing tensions (see FIG 3). The report has eight chapters organised around three themes of work, workforce, and organisation and culture, and what it means to navigate the tensions in them. As ever, the report is packed full of insights, visualisations and data – I particularly found the analysis on AI’s potential silent impacts interesting (see FIG 4). Kudos to the authors who include: Susan Cantrell, David Mallon, Kevin Moss, Nicole Scoble-Williams GAICD, and Yves Van Durme. FIG 3: Navigating the tensions (Source: Deloitte) FIG 4: AI’s potential silent impacts (Source: Deloitte) PEOPLE ANALYTICS NAOMI VERGHESE - The Importance of Data Literacy Skills for HR Professionals By embracing people data and analytics, HR can move beyond traditional administrative functions and become a key driver of business success. Insight222’s most recent People Analytics Trends survey confirms that scaling data literacy is a strategic priority for CHROs, with 85% of companies confirming that the CHRO has emphasised people data and analytics as an essential component of the HR strategy. However, only 58% of companies report that they have a data-driven culture for people data and analytics today, and only 51% of companies report that HR Practitioners are actively developing their data literacy skills to become more data driven. In her article, Naomi Verghese provides examples of data literacy in practice (see FIG 5), and highlights five skills for HR professionals to develop data literacy (including being able to tell stories with data) FIG 5: Examples of data literacy in HR in practice (Source: Naomi Verghese, Insight222) MARTHA CURIONI - Analytical AI vs Gen AI – What’s the Difference? | PRABHAKAR PANDEY - Understanding the European Union's Pay Transparency Directive | ALEXIS FINK - The Power of Responding instead of Reacting | RICHARD ROSENOW - An (updated) interview with an unusual People Analytics Expert - ChatGPT 4.5 | SCOTT REIDA - Evaluating Talent Hubs: A Data-Driven Approach using GenAI w/Tableau In each edition of the Data Driven HR Monthly, I feature a collection of articles by current and recent people analytics leaders. These are intended to act as a spur and inspiration to the field. Five are highlighted in this month’s edition. (1) Martha Curioni provides a helpful primer on the differences between analytical AI and generative AI in a HR setting (see FIG 6).  (2) Prabhakar Pandey provides a detailed examination on the background, objectives, key provisions, and potential impacts of the EU’s Pay Transparency Directive on employers, employees, and the broader European economy. (3) Alexis Fink provides a timely guide on the power of responding instead of reacting. (4) Richard Rosenow fires a series of questions related to people analytics at ChatGPT 4.5, and gets a pretty good set of answers. (5) Scott Reida walks through a structured, GenAI-powered methodology for evaluating talent hubs using ChatGPT, which explains how to define clear objectives, select job families and locations, weight decision factors, and visualise results for smarter, faster insights. Thanks to Hung Lee and Toby Culshaw for highlighting Scott’s article. FIG 6: The differences between analytical and generative AI (Source: Martha Curioni) THE EVOLUTION OF HR, LEARNING, AND DATA DRIVEN CULTURE DAVE ULRICH - Six Actions for HR to Create More Stakeholder Value How can HR create more value for all stakeholders? That’s the question posed by Dave Ulrich at the start of his article. As he explains, answering this pivotal question enables HR leaders to make informed choices about where to prioritise their work and then intentionally share what they are doing and its business impact. In the article, Dave outlines HR’s key stakeholders and the outcomes they require, a human capability framework that integrates 38 initiatives into four pathways, how to focus on outcomes as opposed to activities, and how we can get more precise when it comes to prioritising our work. FIG 7: Six actions, questions, next steps to create stakeholder value from human capability KATE BRAVERY, JOANA SILVA, AND JENS PETERSON | MERCER - Workforce 2.0: Unlocking human potential in a machine-augmented world - Global Talent Trends 2024-25 The world of work is in full metamorphosis, forever changed by the seismic shifts of recent years and accelerated by the imminent human-machine teaming revolution. The rise of generative AI has been met with equal measures of unease and excitement, changing not only how people work but the work experience itself…Unlocking the potential of this new world of work means keeping people at the heart of the transformation agenda. These are an abridged version of the opening words from the Mercer Global Talent Trends report for 2024-25, which has recently been published. As ever, the study, which is based on a survey of 14,400 executives, HR leaders, employees, and investors, and is authored by Kate Bravery Joana Silva and Jens Peterson – with contributions from the likes of Jason Averbook, Ilya Bonic, Lewis Garrad, Ravin Jesuthasan, CFA, FRSA, Jean Martin and JESS VON BANK is an absolute must-read. As in previous years, the study highlights a disconnect between what HR is prioritising for the 2025 people agenda and the initiatives that executives believe will have the most impact on business growth (see FIG 8). The analysis also highlights that improving people managers’ skills (up from 9th in 2024 to 1st in 2025) and designing talent processes around skills (up from 8th to 3rd) are high on HR’s agenda. The study identifies and breaks down four priorities that firms that outpace their competitors are focusing on: (1) Driving human-centric productivity. (2) Anchoring to trust and equity. (3) Boosting the corporate immune system (including highlighting the importance of insights and analytics – see FIG 9). (4) Cultivating a digital-first culture. My tip to enjoy the study: find a couple of hours, make yourself a cup of tea and have a pen and paper to hand. FIG 8: HR priorities for the 2025 people agenda (Source: Mercer Global Talent Trends 2024-25) FIG 9: What gets measured gets managed (Source: Mercer Global Talent Trends 2024-25) JOSH BERSIN AND KATHI ENDERES - Secrets Of The High Performing CHRO The CHRO role is critical for business success, with CHROs serving as C-suite leaders first, and HR function leaders second. In his article previewing his new paper with Kathi Enderes, Understanding the Path to CHRO, Josh Bersin cites a recent study by Nick Bloom and Mert Akan (see here), which finds that 13% of CHROs are among the top five highest-paid executives in their organisations, a sharp rise from just 0.5% thirty years ago. The paper outlines the role of the CHRO, career trajectories, education, experiences, and high-level success drivers, along with the implications for leaders. Findings include: (1) More than 75% of CHRO appointments come from the outside, indicating a lack of CEO confidence in HR and/or a lack of succession planning for this job. (2) There are four major archetypes of CHRO (see FIG 10): Career CHRO (who change companies regularly), Company CHRO (who grow up inside the company), Business CHRO (who are rotated into the job from non-HR roles), and Operations CHRO (who come from legal, finance, or operations background). (3) Business CHROs drive the greatest change and impact. FIG 10: Four paths to the CHRO (Source: The Josh Bersin Company) WORKFORCE PLANNING, ORG DESIGN, AND SKILLS-BASED ORGANISATIONS MCKINSEY - The critical role of strategic workforce planning in the age of AI S&P 500 companies that excel at maximizing their return on talent generate an astonishing 300 percent more revenue per employee compared with the median firm In many cases, these top performing firms are using strategic workforce planning to stay ahead of their competitors in the talent race, treating talent with the same rigour as managing their financial capital. In their article, Neel Gandhi, Sandra Durth, Vincent Bérubé, Charlotte Seiler, Kritvi Kedia and Randy Lim, highlight how the emergence of generative AI is making strategic workforce planning even more important (see FIG 11), and discuss five best practices for building a holistic talent plan through SWP: (1) Prioritise talent investments as much as financial investments. (2) Consider both capacity and capabilities. (3) Plan for multiple business scenarios. (4) Take an innovative approach to filling talent gaps – by refocusing from hiring to reskilling and upskilling. (5) Embed SWP into business as usual: Strategic workforce planning should become a business-as-usual process, not just a one-off exercise in the face of a single threat to an organization’s talent pipeline or business goals. FIG 11: The impact of GenAI on tasks that previously had low potential for automation  (Source: McKinsey) JOSH TARR - Key Skills-Based Strategies for Building a More Agile and Resilient Workforce | WORKDAY – The Global State of Skills Skills-based strategies are transforming the workplace into a more dynamic, adaptable, and equitable environment. Josh Tarr shares key findings from Workday’s recently published The Global State of Skills report, which finds that 51% of business leaders are concerned about a looming talent shortage, with only 32% in agreement that their organisation possesses the skills needed for future success. The article examines three key skills-based strategies: (1) Skill Identification: Building an Accurate Picture of Workforce Capabilities. (2) Skills-Based Hiring: Focusing on What People Can Do, not Their Credentials. (3) Upskilling and Reskilling: Elevating the Workforce. Thanks to Sophie Barnes for highlighting. FIG 12: Top drivers and anticipated outcomes for becoming a skills-based organisation (Source: Workday) EMPLOYEE LISTENING, EMPLOYEE EXPERIENCE, AND EMPLOYEE WELLBEING PATRICK COOLEN AND SANDER DE BRUIJN - 7 Golden Rules For Improving Employee Experience Effective EX solutions are built on an iterative and evidence-based approach while co-creating with employees. In their article, Patrick Coolen and Sander de Bruijn of KennedyFitch share their experience and insights on how to do continuous employee listening and improve employee experience. They share seven ‘Golden Rules’ for improving employee experience including: (1) Applying the ‘Triple Diamond Model’ (see FIG 13) in order to capture, understand and act on your employees' needs and ambitions. (2) Ensuring strategic positioning (“EX is a strategic capability, so the responsible team should be positioned in HR accordingly”). (3) Aiming for hyper-personalisation (“By understanding employee differences, organisations can tailor experiences to be more personalised and meaningful”). Read the article to learn about the other golden rules as well as letting Patrick and Sander know what rules eight, nine and ten should be. FIG 13: The ‘Triple Diamond Model’ to drive employee experience (Source: Patrick Coolen and Sander De Brujin) DANIEL WENTZEL, ALICE MINET, STEFAN RAFF-HEINEN, AND JANINA GARBAS - How Remote Work Changes Design Thinking A key advantage of the design-thinking process over other innovation methods is its emphasis on the user experience. Design thinking and user centred design are critical tools in building an exceptional employee experience – and HR practitioners can learn much from how these tools are applied to customer experience. In their article for MIT Sloan Management Review, Daniel Wentzel, Alice Minet, Dr. Stefan Raff-Heinen, and Dr. Janina Garbas share advice for leaders on structuring the design-thinking process to exploit the best features of both physical and virtual environments for more effective ideation, customer experience research, and other design-thinking steps. As outlined in FIG 14, effectively combining physical and virtual formats throughout the design-thinking process allows innovation leaders to harness the distinct advantages of each setting. FIG 14: How to set up hybrid design thinking processes (Source: Wentzel et al) LEADERSHIP, CULTURE, AND LEARNING STUART L. HART - How to Embed Purpose at Every Level In his article, drawn from his book, Beyond Shareholder Primacy: Remaking Capitalism for a Sustainable Future, Stuart L. Hart presents a practical framework and approach for truly embedding societal purpose, drawing upon the experience of several innovative companies. This framework imagines the company as a house of transformational sustainability – see FIG 15 – where the shared values are the foundation, the roof is the company purpose, the middle floor is the core elements of strategy. The article examines of the elements of the corporate architecture in more depth, along with examples from the 15 companies Hart and his team studied as part of their work: (1) What We Believe: Values (“The transformational companies we examined established a strong foundation built on their organizations’ values”). (2) Why We Exist: Purpose. (3) What We Solve: Aspirations and Quests: (“Together, aspirations and quests serve as the fulcrum for change in leading-edge companies, translating purpose and intention into strategy and operating reality”). (4) How We Win: Strategies and Initiatives. (5) What We Track and How We Accelerate: Goals and Metrics, Rewards and Incentives. FIG 15: The House of Transformational Sustainability (Source: Stuart L. Hart) DIVERSITY, EQUITY, INCLUSION AND BELONGING DANIEL ZHAO – DEI Data Points on Glassdoor | JOELLE EMERSON – Analysis on EEOC Assessment of Unlawful DEI Initiatives | MEG A. WARREN – Amid DEI Rollbacks, Champion Allyship | JEREMIE BRECHEISEN, TERESA ALMEIDA AND NIKITA - When Does a Regional Approach to DEI Make Sense for Multinational Companies? | BRANDON DENON - In the US, DEI is under attack. But under a different name, it might live on With the continuing uncertainty around Diversity, Equity and Inclusion, as with the February edition of Data Driven HR Monthly, I wanted to share some of the resources I’ve consumed on this topic with readers: (1) Daniel Zhao shares a number of DEI related data points from Glassdoor, which perhaps not surprisingly has seen that conservations on DEI have surged on Glassdoor’s community platform (see FIG 16). (2) DEI expert Joelle Emerson provides an initial assessment of the EEOC’s recent guidance on unlawful DEI initiatives. (3) Meg Warren, Ph.D. presents research that finds that abandoning DEI initiatives can harm both performance and workplace culture – with inclusive workplaces being better for workers and our businesses. (4) Jeremie K Brecheisen, Teresa Almeida, and Nikita present findings from a study by Gallup and the London School of Economics that found that 77% of companies had centralised DEI operations, but that the companies with decentralised regional operations reported greater business impact. (5) Finally, in a BBC InDepth article, Brandon Drenon writes on how companies in the US are adopting different stances to Trump’s Executive Orders. FIG 16: The rise of DEI conversations on Glassdoor (Source: Glassdoor) HR TECH VOICES Much of the innovation in the field continues to be driven by the vendor and analyst community, and I’ve picked out a few resources from March that I recommend readers delve into: EMILY KILLHAM | PERCEPTYX - The State of Employee Listening 2025 – Perceptyx's annual analysis of employee listening, authored by Emily Killham, is always a compulsory read. The 2025 edition continues the high standard with highlights including (1) How the top barriers to listening and action have changed in the last 12 months. (2) The critical risks associated with increasing burnout of HR leaders. (3) An update to Perceptyx’s 4-stage maturity model that describes the progression of an employee listening and action program from its most fundamental to its most robust. FIG 17: Employee listening maturity model (Source: Perceptyx) PHILIP ARKCOLL - The AI Maturity Curve: Measuring AI Adoption in your Organization – Philip Arkcoll, CEO at Worklytics , sets out a compelling framework for measuring the impact of AI on your organisation – the AI Maturity Curve (see FIG 18), which is comprised of three stages: Adoption (focused on uptake), Proficiency (focused on impact), and Leverage (focused on productivity gains). FIG 18: Measuring the impact of AI on your organisation (Source: Worklytics) DIRK JONKER AND RALF BOVERS - How common are people analytics teams? – In a recent edition of Crunchr’s newsletter, The HR Crunch, Dirk Jonker and Ralf Bovers provide some illuminating insights into the size and location of companies that have people analytics teams (see FIG 19) with the US and larger companies leading the way. FIG 19: Companies with people analytics teams (Source: Crunchr) ERNEST NG - AI Holds the Potential to Lead Organizations Into an Era of Abundance – Workday’s Ernest Ng, PhD discusses how AI agents will impact how we think about the organisation and challenge common HR orthodoxies. His article outlines how we can reimagine the organisation with a ‘beginners mind’ if we were not bound by the limitations of time and human attention, why AI is potentially transformational, and where to go from here. FRANCISCO MARIN - Measuring the Impact of Organizational Network Analysis (ONA): From Insights to Tangible ROI - Francisco Marin and the Cognitive Talent Solutions team share a helpful primer on how to measure the ROI of organisational network analysis (ONA), which includes a table (see FIG 20) with example use cases and ROI estimates. FIG 20: ONA Use Cases & Hard Savings Estimations (Source: Cognitive Talent Solutions) PODCASTS OF THE MONTH In another month of high-quality podcasts, I’ve selected five gems for your aural pleasure: (you can also check out the latest episodes of the Digital HR Leaders Podcast – see ‘From My Desk’ below): DR. HOLLY LAM - Bridging the Chasm Between People Analytics & the Business – Holly Lam, PhD joins hosts Cole Napper and Scott Hines, PhD on the Directionally Correct podcast to discuss what it’s like to be decision maker in the business and move back to people analytics. BRENDA KOWSKE - Strategic Workforce Planning in the Age of AI – In an episode of Workplace Stories, hosts Stacia Sherman Garr and Dani Johnson speak with Brenda Kowske about how her people analytics and workforce planning team is breaking down traditional HR silos, integrating workforce planning into business decisions, and staying ahead of the curve with AI and skills-based planning at Boston Scientific. ARNE-CHRISTIAN VAN DER TANG – CHRO Insights – Arne-Christian Van Der Tang, CHRO at TomTom, joins Kathi Enderes on the What Works podcast to explain why the CHRO is no longer an HR leader, but now a business transformation executive. IAN WILSON - How Amazon Builds High-Performing Teams – Ian Wilson, VP HR at Amazon, speaks to Christopher Rainey on the HR Leaders podcast about how Amazon builds high-performing teams, the role of psychological safety, and HR’s role in driving business impact. BRYAN HANCOCK AND BROOKE WEDDLE - How to get return to office right - In this episode of McKinsey Talks Talent, Bryan Hancock and Brooke Weddle speak with host Lucia Rahilly about their recent research on the opportunities and challenges of RTO—and how leaders can drive productivity, collaboration, and innovation successfully. VIDEO OF THE MONTH AMIT MOHINDRA AND HEATHER WHITEMAN – People Analytics Career Skills Live! Two giants of people analytics – Amit Mohindra and Heather Whiteman, Ph.D., who both featured on the recent list of Top 20 People Analytics Influencers join forces as Amit shares his career journey, the key skills for success in people analytics, and a wealth of invaluable advice. The webinar includes a demonstration of how to leverage basic descriptive analytics to perform predictive analytics. BOOK OF THE MONTH KWEILIN ELLINGRUD, LAREINA YEE, AND MARÍA DEL MAR MARTÍNEZ – The Broken Rung: When the Career Ladder Breaks for Women and How They Can Succeed in Spite of It For every 100 men who are promoted to manager, only 81 women get promoted. This causes women to fall behind men early on – far below the ‘glass ceiling’. This is what Kweilin Ellingrud, Lareina Yee, and Maria del Mar Martinez have coined “the broken rung”. Their book is based on a decade of research, their own experiences as the first three chief diversity and inclusion officers for McKinsey, interviews with 50 leaders, and is a guide to help women accelerate their career growth. For a preview of the book, I recommend reading a recent article by the authors: How Women Can Win in the Workplace. RESEARCH REPORT OF THE MONTH FABRIZIO DELL’ACQUA ET AL - The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise Our results suggest that AI adoption at scale in knowledge work reshapes not only performance but also how expertise and social connectivity manifest within teams, compelling organizations to rethink the very structure of collaborative work. This new paper summarises the findings from a study of how AI transforms the core pillars of collaboration – namely performance, expertise sharing, and social engagement – through a field experiment with 776 workers at Procter & Gamble. The findings include: (1) AI significantly enhances performance, (2) AL breaks down functional silos. (3) AI’s language-based interface prompted more positive self-reported emotional responses among participants (see FIG 21). The paper is a collaboration between Fabrizio Dell'Acqua, Charles Ayoubi and Karim Lakhani from the Digital Data Design Institute at Harvard along with Hila Lifshitz, Raffaella Sadun, Ethan Mollick, and Lilach M., and Yi Han, Jeff Goldman, Hari Nair, and Stewart Taub from Procter & Gamble. You can also read Ethan Mollick’s article on the research: The Cybernetic Teammate. FIG 21: Working with AI leads to better emotional experiences (Source: Ethan Mollick) BONUS RESOURCES Some bonus resources to consume this month feature articles from five of my favourite newsletters: Lars Schmidt ’s personal and compelling Confessions of a Reluctant Thought Leader explains why he has shifted back from being an influencer to an operator. Much of this really resonates. In AI’s battle of the skills: upskilling vs deskilling, Laetitia Vitaud asks and then answers the question: “Does generative AI mostly amplify the skills of experienced workers, or does it level the playing field by enabling less experienced, less qualified workers to perform at higher levels?” Andrew Spence’s Workforce Futurist is consistently one of the most insightful newsletters out there – his latest: Seven Ways Technology is Making Us More Human, Not Less is a must-read. Serena H. Huang, Ph.D.’s From Data to Action has close to 10,000 subscribers, and it’s easy to see why as the latest edition: The Future of Work is Wellbeing—And It’s Broken Without Inclusion, tackles an important and timely topic in her typically insightful and personal style. Not many understand the world of HR Tech better than Thomas Otter as his excellent Work in Progress substack consistently testifies. In Explaining M&A through the lens of Income Statement v Balance Sheet analyses two very different recent acquisitions: ServiceNow and Moveworks. and Deel and the global payroll business of Safeguard. As an additional bonus, I also want to highlight the inaugural edition of Phil Kirschner’s The Workline, which features an exclusive interview with Annie Dean of Atlassian on their “Cost Per Visit” metric. See: Exclusive Case Study: Atlassian Humanized the Office with One New Metric. FROM MY DESK March saw the final four episodes of series 45 the Digital HR Leaders podcast, sponsored by our friends at Amazing Workplace, Inc. KATHERINE MACNAUGHTON - How Manulife Improved Employee Experience Through Transforming Its Organisational Culture - In this episode I talk to Katherine Macnaughton, CHRL, Vice President of Global Talent Management and Development at Manulife, about how Manulife is embedding purpose into every stage of the employee journey. SHON HOLYFIELD - Why Measuring Happiness Matters Just as Much as Engagement - Shon Holyfield, Founder and CEO of Amazing Workplace, Inc., joins me to explore how focusing on employee happiness can transform business outcomes. LUCY ADAMS - How HR Can Lead Successful Digital Transformation Initiatives – Lucy Adams, CEO of Disruptive HR and former CHRO at the BBC and Eversheds, joins me to discuss how HR can lead digital transformation and enable business leaders to be change champions. ANNA TAVIS - How to Drive Workforce Experience and Learning with Digital Coaching - Anna A. Tavis, PhD, Chair of the Human Capital Management Department at New York University and co-author (with Dr. Woody Woodward, PhD, PCC) of The Digital Coaching Revolution, joins me to explore how organisations can move from traditional coaching methods to scalable AI-powered solutions. LOOKING FOR A NEW ROLE IN PEOPLE ANALYTICS OR HR TECH? I’d like to highlight once again the wonderful resource created by Richard Rosenow and the One Model team of open roles in people analytics and HR technology, which – as Richard’s latest newsletter reveals - now numbers over 525 roles. Look out too for Richard's latest newsletter analysing the current job market. THANK YOU The Economic Times for including Excellence in People Analytics in their Top 20 books HR professionals should consider reading in 2025 Joachim Rotzinger for featuring me in the inaugural issue of his #OrgPeople series, which highlights individuals who are shaping the way we think about organisations and analytics: you can read Joachim’s post here. Chrishtica Sivakumar for including me in her list of 11 HR Professionals to follow and learn from. Similarly, K Nair for including me in his 25 Must-Follow LinkedIn Accounts for HR in 2025. Congratulations to Sukumaran Mariappan on 25 years of growth and gratitude – and thanks for including me as one of 20 people you highlight for having helped you on your journey. Marc Voi Chiuli. (MSc. HRM. Assoc CIPD. MIHRM.) for referencing Excellence in People Analytics in his recent article: HR Analytics Is Here! Are HR Practitioners Ready to Adopt this New Trend and Take Their Businesses to the Next Level? I always enjoy reading posts from listeners of the Digital HR Leaders podcast summarising their key takeaways and learnings from individual episodes. Two great examples (the first from the recent episode with Lucy Adams on HR’s role in transformation and the second with Anna Tavis on digital coaching come from Shrez Ghelani (here) and Olimpiusz Papiez (here). Finally, a huge thank you to the following people who either shared the February edition of Data Driven HR Monthly and/or posted about the Digital HR Leaders podcast, conferences or other content. It's much appreciated: Sam Streak, Anja Leschly, Thomas Kohler, Raja Sengupta, Brandon Merritt Johnson, Galo Lopez Noriega, Mike Madelin FCIPD, Megan Reif, Johann Cheminelle, Gerard Kiely, Charlotte Copeman, Clodagh Scannell, Matthew Phelan, Catriona Lindsay, Aurélie Crégut, Keji Fakeye, MS, CSM, Jose Luis Chavez Vasquez, Kouros Behzad, Jarret O., Callum MacRae, Dan George, Francesca Gabetti, Susana Pires, Felipe Jara, Laurent Reich, Bob Pulver, Megan Sherman, Ph.D., Diego Miranda ??, Amardeep Singh, MBA, Viktoriia Kriukova (Вікторія Крюкова), Krista V., David Simmonds FCIPD, Danielle Farrell, MA, CSM, Ian OKeefe, Sanja Licina, Ph.D., Deborah M. Weiss, Dean Carter, Dan Riley, Sibusiso Mkhize, Nitish Kumar, Aravind Warrier, Sarajit Poddar, Preetha Ghatak Mukharjee, Lewis Garrad, Greg Pryor , Kris Saling, Nick Lynn, Shirley Mariole, MPNGHRI, Richard Bretzger, Till Alexander Leopold, Kyle Forrest, Erik Samdahl, Ralf Buechsenschuss, David Boyle, Ben Berry, Amanda Nolen, Andrew Pitts, Swechha Mohapatra (IHRP-SP, SHRM-SCP, CIPD), Linpei Zhang, Moïra Taillefer, Sonia Mooney, Kathleen Kruse, Timo Tischer, Volodymyr Shevchenko Rebecca Ray, Anyuta Dhir, Tobias W. Goers ツ, John Guy, Kristin Saboe, Ph.D., Caitie Jacobson Mikulis, Hesham Ahmed, Daisy Grewal, Ph.D., Brian Elliott, Paola Alfaro Alpízar, Mila Pascual-Nodusso, John Golden, Ph.D., Heather Muir, Dan Lapporte, Tina Peeters, PhD, Frankie Close, Tonille Miller, Narelle Burke, Ying Li, Raquel Mitie Harano, Saumya Singh, Joseph Frank, PhD CCP GWCCM, John Perrian, Jill Larsen, Kelly Cartwright, Paul Boyle, Paulo Henrique Bolgar, Federico Bechini, Phil Inskip, Tammy Arnaud, Anushree Kabra Tatu Westling, Brad Hubbard, Marie-Hélène Gélinas, MBA (Cand.), Aimee Shirreffs, Delia Majarín, Jo Thackray FCIPD, Gishan Nissanka, Ali Nawab, Pedro Pereira, Natasha Ouslis, PhD, David Balls (FCIPD), Nikita D'Souza, Tanya Jain, Angela LE MATHON, Graham Tollit, Mino Thomas, Dave Millner, Ingi Finnsson ?, Maria Ursu, Craig Starbuck, PhD, Stela Lupushor, Dave Fineman, Monika Manova, Hanne Hoberg, Jacob Nielsen, James McKay, Morgan Baldwin, Mattijs Mol, Sebastian Knepper, Maria Alice Jovinski, Mariami Lolashvili, Shuang Yueh Pui, PhD, Ken Clar, Andrés García Ayala, Dr Philip Gibbs, Elizabeth Esarove, Higor Gomes, Olivier Bougarel, Ron Ben Oz, Louis Gordon, Jeff Wellstead, Agnes Garaba, Erik Otteson, Stephen Hickey UNLOCK THE POTENTIAL OF YOUR PEOPLE ANALYTICS FUNCTION THROUGH THE INSIGHT222 PEOPLE ANALYTICS PROGRAM At Insight222, our mission is to make organisations better by putting people analytics at the centre of business and upskilling the HR profession The Insight222 People Analytics Program® is your gateway to a world of knowledge, networking, and growth. Developed exclusively for people analytics leaders and their teams, the program equips you with the frameworks, guidance, learnings, and connections you need to create greater impact. As the landscape of people analytics becomes increasingly complex, with data, technology, and ethical considerations at the forefront, our program brings together over one hundred organisations to collectively address these shared challenges. Insight222 Peer Meetings are a core component of the Insight222 People Analytics Program®. They allow participants to learn, network and co-create solutions together with the purpose of ultimately growing the business value that people analytics can deliver to their organisations. If you would like to learn more, contact us today. ABOUT THE AUTHOR David Green ?? is a globally respected author, speaker, conference chair, and executive consultant on people analytics, data-driven HR and the future of work. As Managing Partner and Executive Director at Insight222, he has overall responsibility for the delivery of the Insight222 People Analytics Program, which supports the advancement of people analytics in over 100 global organisations. Prior to co-founding Insight222, David accumulated over 20 years experience in the human resources and people analytics fields, including as Global Director of People Analytics Solutions at IBM. As such, David has extensive experience in helping organisations increase value, impact and focus from the wise and ethical use of people analytics. David also hosts the Digital HR Leaders Podcast and is an instructor for Insight222's myHRfuture Academy. His book, co-authored with Jonathan Ferrar, Excellence in People Analytics: How to use Workforce Data to Create Business Value was published in the summer of 2021. MEET ME AT THESE EVENTS I'll be speaking about people analytics, the future of work, and data driven HR at a number of upcoming events in early 2025: April 10-11 - Wharton People Analytics Conference, Philadelphia April 16 - Delegation Rewired: What HR Can Stop Doing, Thanks To Agentic AI, Webinar organised by People Matters April 29-30 - People Analytics World, London May 6-8 - UNLEASH America, Las Vegas June 4-6 - TALREOS (Talent Analytics Leadership Roundtable Economic Mobility Summit), Chicago June 10-11 - Insight222 Q2 North American Peer Meeting, Toronto, (hosted by Royal Bank of Canada, and exclusive to the people analytics leader in member companies of the Insight222 People Analytics Program®) June 25-26 - Insight222 Q2 European Peer Meeting, London, (hosted by BT, and exclusive to the people analytics leader in member companies of the Insight222 People Analytics Program®) July 31 - August 1 - People Matters TechHR India 2025, Delhi October 7-9 - Insight222 Global Executive Retreat, Atlanta (exclusive to the people analytics leader in member companies of the Insight222 People Analytics Program®) October 15-16 - People Analytics World, New York October 21-22 - UNLEASH World, Paris More events will be added as they are confirmed.
    AI adoption
    2025年04月14日
  • AI adoption
    麦肯锡：AI赋能职场，企业如何跨越管理障碍，实现智能化未来？员工对 AI 的适应速度远超领导层的预期 AI 如何重塑职场？ 人工智能（AI）正在以惊人的速度重塑职场生态，许多企业正试图利用 AI 提高生产力、优化决策流程并增强市场竞争力。然而，AI 技术的广泛应用远非一蹴而就，企业的 AI 部署不仅涉及技术升级，更考验管理者的战略眼光和执行力。 麦肯锡的《Superagency in the Workplace》 这份报告深入研究了 AI 在职场中的应用现状，基于对 3,613 名员工和 238 名 C 级高管 的调查，揭示了企业在 AI 落地过程中的机遇与挑战。报告认为，AI 在职场的变革潜力堪比蒸汽机之于工业革命，但当前的最大障碍并非技术问题，而是领导层的行动力不足。 尽管 92% 的企业计划在未来三年增加 AI 投资，但只有 1% 认为自己 AI 发展成熟，表明大多数企业仍停留在 AI 试点阶段，尚未实现全面部署。更值得注意的是，报告发现员工对 AI 的接受度远超管理层的预期，但企业的 AI 发展速度依然滞后。领导者的犹豫和执行力缺失，正成为 AI 规模化应用的最大瓶颈。 本文将从员工接受度、领导层挑战、组织架构变革、AI 治理、商业价值实现等多个维度，介绍报告的核心观点，并补充对 AI 发展的进一步思考。 一、员工比领导更快接受 AI，企业行动缓慢 报告的核心发现之一是：员工已经在积极使用 AI，而领导者仍然低估了 AI 的普及度。 数据显示： 员工使用 AI 的频率比领导层预期高出 3 倍，但许多企业尚未提供系统性培训； 70% 以上的员工认为 AI 在未来两年内将改变至少 30% 的工作内容； 94% 的员工和 99% 的高管都表示对 AI 工具有一定熟悉度，但只有 1% 的企业认为 AI 应用已成熟。 这一现象表明，AI 在企业中的主要障碍并非员工适应能力，而是管理层的滞后决策。许多企业高管仍然停留在探索 AI 价值的阶段，而员工已经在日常工作中广泛使用 AI 工具，如自动生成文档、数据分析、代码编写等。员工在推动 AI 发展方面的主动性，远远超出管理层的认知。 然而，企业未能为员工提供足够的 AI 培训和资源，导致 AI 的应用仍然停留在浅层次，难以转化为真正的生产力提升。例如，48% 的员工认为 AI 培训是 AI 规模化应用的关键，但许多公司仍未建立 AI 学习机制。企业如果不采取措施缩小这一认知鸿沟，可能会错失 AI 带来的长期竞争优势。 二、AI 领导力挑战：速度焦虑与执行落差 尽管 AI 的发展潜力巨大，但报告指出，47% 的企业高管认为公司 AI 发展过于缓慢，主要原因包括： AI 技术成本的不确定性：短期 ROI（投资回报率）难以量化，导致企业不敢大规模投资； AI 人才短缺：AI 相关技术人才供不应求，企业缺乏相应的招聘和培养体系； 监管与安全问题：企业在数据隐私、算法透明度等方面的担忧阻碍了 AI 落地。 这种“速度焦虑”让企业在 AI 发展过程中陷入试点—停滞—观望的循环： 试点阶段：部分企业已启动 AI 试点项目，如客服自动化、数据分析等； 停滞阶段：由于短期收益不确定，试点项目难以规模化推广； 观望阶段：企业倾向于等待行业先行者经验，而非主动探索 AI 的商业价值。 报告强调，AI 的落地不仅是技术问题，更是企业管理问题。领导者需要具备更强的战略决心，加快 AI 投资，并明确 AI 在企业中的角色，才能真正推动 AI 规模化应用。 三、如何实现 AI 规模化落地？ 1. AI 人才培养 AI 的大规模应用依赖于系统性的 AI 人才培训。然而，报告发现，近一半的员工认为企业提供的 AI 支持有限。企业需要采取措施： 建立 AI 培训体系，涵盖 AI 基础知识、业务应用和 AI 伦理等内容； 推广 AI 试点项目，让员工亲身参与 AI 工具的开发和使用； 设立 AI 激励机制，鼓励员工利用 AI 提升工作效率。 2. 组织架构调整 AI 不能仅仅作为 IT 部门的创新项目，而应当成为企业整体战略的一部分。报告建议： 设立 AI 战略委员会，确保 AI 发展与企业长期战略保持一致； 推动 AI 在各业务部门落地，提升 AI 在实际业务流程中的应用深度； 强化 AI 风险管理，确保 AI 应用在数据安全和监管方面的合规性。 3. AI 治理：平衡速度与安全 虽然 AI 带来了极大的商业价值，但报告指出，企业在 AI 治理方面仍存在诸多挑战： 51% 的员工担心 AI 可能带来的网络安全风险； 43% 的员工关注 AI 可能导致的数据泄露； 企业需要建立 AI 伦理标准，确保 AI 透明、公正、合规。 四、AI 时代的商业价值：企业如何真正实现 ROI？ 尽管企业对 AI 充满期待，但报告显示，目前仅 19% 的企业 AI 投资带来了 5% 以上的收入增长，表明大多数企业的 AI 应用尚未转化为可观的商业回报。为了提升 AI 价值，企业需要： 从“技术驱动”转向“业务驱动”，确保 AI 应用直接创造商业价值； 优化 AI 目标设定，明确 AI 在核心业务中的定位； 加强 AI 应用场景探索，特别是在客户服务、供应链管理等高回报领域进行深入部署。 AI 成败的关键在于管理层 AI 的成功不仅依赖技术本身，更取决于企业领导者的执行力和战略眼光。企业若要真正迈向 AI 时代，需要： 加速 AI 战略落地，推动组织变革； 加强 AI 人才培养，提高员工 AI 适应能力； 建立 AI 治理体系，确保 AI 安全合规发展。 在 AI 时代，最危险的不是迈得太快，而是思考得太小、行动得太慢。 附录：《Superagency in the Workplace》 下载
    AI adoption
    2025年03月14日
  • AI adoption
    The top 5 HR trends today – and HR's guide to what's next SAP SuccessFactors 每年都会深入研究全球 HR 趋势，以帮助企业制定更有效的人才战略。2025 年，他们分析了来自 40 家全球权威媒体的 254 项预测，归纳出 5 大核心“元趋势”，展现 HR 在企业中的双重角色：既是变革的“指挥者”，也是政策落地的“引航者”。 1️⃣ 重新连接员工： 由于经济压力、决策争议和信任危机，员工体验恶化，57% 的员工认为如果公司不采取措施，他们的倦怠问题不会改善。HR 需关注心理契约，增强员工信任。 2️⃣ AI 从炒作走向实际价值： AI 进入大规模落地阶段，企业需明确 ROI 并平衡员工和领导者对 AI 价值的不同预期。46% 的员工认为 AI 省下的时间属于自己，而非公司。 3️⃣ 技能转型的平衡策略： 由于 AI 发展迅猛，企业技能鸿沟加剧。除了关注技能，薪酬激励成为推动学习的重要因素，54% 的员工表示，如果公司实施基于技能的薪酬体系，他们会更愿意学习新技能。 4️⃣ DEI&B 的分歧： 企业对多元化、公平性和包容性（DEI&B）态度不一，26% 的员工认为公司对 DEI&B 关注过多，而 33% 认为关注太少。HR 需明确 DEI&B 战略，以促进长期文化变革。 5️⃣ 混合办公的未来： 组织已基本确定办公模式，2025 年将验证其成效。54% 的员工愿意牺牲部分薪酬，以换取更大的工作灵活性。 这些趋势展现了 HR 在塑造未来工作模式中的关键作用，企业需借助创新技术和数据驱动的洞察来优化人力资源管理。 Each year, the HR Research Scientists at SAP SuccessFactors conduct research to understand the top HR and workforce trends facing organizations and share our perspective on what HR teams should consider as they look to help their companies address these trends. This year we aggregated and synthesized data from 40 global and regional reputable business press sources that put forward 254 individual trends and predictions grounded in their own research and data. We then conducted a content analysis of the trends sample to derive the five key themes, or “meta-trends.” While our annual report always includes some pointed commentary and critique about each trend based on our expertise in psychology, new this year is calling upon our own body of original applied research to incorporate datapoints and insights, resulting in a more evidence-based point of view. This year’s trends are in different stages of maturity and on different trajectories; therefore, the role that HR needs to play to help businesses tackle and capitalize on these trends is different. We’ve organized the trends into two sections aligned to the dual role HR will play in addressing them. First, HR will need to act as a Conductor, leading the orchestration of a strategy and associated change management across the business to realize the opportunities these trends offer: Trend #1: Reconnecting the disconnected employee: Contentious decisions, macroeconomic and sociopolitical stressors, and breached trust with leadership has led to employee stress and burnout – and consequently, a crisis of disconnect and counterproductivity. In the year ahead: Leaders must ruthlessly prioritize fulfilling their end of the “psychological contract” by meeting employees’ basic needs. People managers will be seen as a lifeline for employees drowning in disconnect. STAT: 57% of employees feel unless their companies make some serious changes, their burnout will not get better. Trend #2: Moving from AI hype to AI impact:Organizations are shifting from AI pilot projects to enterprise-wide rollouts, demanding proof of clear value and ROI. In the year ahead: Organizations will home in on their key value drivers for AI, revealing their true priorities. The body of research on the ROI of AI will be built this year. Organizations will find friction between leaders’ and employees’ goals for using AI. STAT: 46% of employees feel that the time that they save by using AI tools at work belongs to them, not their organization.​ Trend #3: Striking a balance to steer skills forward: Organizations continue to face pervasive skills gaps, in part due to rapid AI advancements. A more balanced approach is needed to see tangible progress in skills-based transformations this year. In the year ahead: “Skills-based” will no longer be the only goal. Pay will prove itself the missing piece of the upskilling puzzle. The human vs. technical skill debate will move from or to and. STAT: 54% of employees would be more motivated to learn new skills if their company instituted skills-based pay.​ Second, HR will need to act as a Navigator, leading the organization through precarious waters and circumventing obstacles to put policies into practice for the betterment of all stakeholders: Trend #4: Divesting or doubling down on diversity, equity, inclusions, and belonging (DEI&B): Some organizations remain committed to DEI&B goals, continuing to ask “How are we going to do this?” Others plan to divest, instead now asking “Are we going to do this?” In the year ahead: Some will shy away from DEI&B goals, but these approaches will vary. Taking a stand on DEI&B will change company cultures in the long term, but it’s not clear exactly how. STAT: 26% of employees say companies focus too much on DEI&B, 41% of employees say companies focus an appropriate amount on DEI&B, and 33% of employees say companies focus too little on DEI&B. Trend #5: Plugging into or pulling the plug on hybrid work: Now that organizations have determined their position on where their employees will work, it’s time to see if they achieve the outcomes they intended. In the year ahead: Those businesses choosing the return-to-office path will see whether their bets paid off this year. Those choosing the hybrid or remote path will take it a step further, integrating autonomy as a core value in other aspects of work design. STAT: 54% of employees would consider being paid less if they could have more flexibility in where and when they work. Read the report to see what’s now and what’s next for each trend, along with some fast facts that uplevel the nerdiness of this year’s trends report. We also include a section on how SAP SuccessFactors solutions can help organizations address the 2025 HR trends.
    AI adoption
    2025年03月07日
    • 12
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