Why AI is now HR’s businessCould 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 governance
2025年11月28日
AI governance
CHRO 的新战略机遇：生成式 AI 如何重塑组织的未来概要：74% 的 CEO 认为团队已准备好迎接 AI，但只有 29% 的 C-suite 同意。这一巨大认知差距既是风险，也是 CHRO 最关键的机会窗口。预计到 2025 年，77% 的初级岗位与超过 25% 的高管岗位都将因 AI 发生改变。未来三年，CHRO 必须从支持角色转变为组织未来的设计者，围绕三项任务展开：构建 AI 人才战略、重塑组织运营模式、建立 AI 治理框架。AI 时代的核心竞争力不再是技术本身，而是 CHRO 如何重塑组织能力与文化。抓住这个窗口期，组织才能真正迈向未来。
引言：迎接组织变革的“AI 时刻”
生成式 AI 与以往任何技术都截然不同，它正以前所未有的速度颠覆商业与社会，迫使领导者实时反思并重塑其核心战略。这场变革的核心并非技术本身，而是它对“人”与“工作方式”的根本性重塑。正如深度研究所指出的，“生成式 AI 的一切都与人有关——关乎工作如何完成”。
懂得如何用生成式 AI 赋能人才的领导者，将对业务产生“倍增效应”。在未来三年，首席人力资源官（CHRO）将迎来一个决定性的转折点，从传统的支持角色转变为驱动这一倍增效应的核心战略制定者。然而，当前仍有高达 60% 的高管将人力资源视为纯粹的行政职能，这一认知错位不仅是巨大的风险，更预示着一个前所未有的战略机遇。CHRO 必须抓住此刻，引领组织迎接未来。
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一、趋势洞察：生成式 AI 正在重塑工作的本质
1. AI 放大人类能力，而非取代人类
生成式 AI 的核心价值在于放大人类的专业能力。它通过自动化市场研究、内容创建、数据分析和代码开发等重复性任务，让员工得以专注于更高价值的创造性工作。例如，客服人员可以将常规问答交给 AI，从而专注于销售赋能；程序员可以摆脱繁琐的编程，聚焦于提升代码质量与安全性；HR 专家则能从日常流程中解放出来，全力投入于真正重要的人才发展。
企业的竞争优势不再仅仅来源于技术本身，而是来源于规模化员工的专业知识和扩展组织的能力。这催生了“AI 增强型劳动力”的概念。一个清晰的现实是：生成式 AI 不会取代人类，但使用生成式 AI 的人将会取代不使用它的人。
2. CEO 与组织间存在显著的“AI 准备度差距”
高管层对组织 AI 准备度的认知存在显著脱节，这种乐观情绪背后潜藏着巨大风险。数据显示：
74% 的 CEO 认为他们的团队已经为生成式 AI做好了技能准备。
然而，仅有 29% 的 C-suite 高管 同意这一观点。
这一巨大的认知鸿沟，代表了 CHRO 最为紧迫的行动指令。更值得警惕的是，AI 的影响是普遍的：到 2025 年，77% 的初级员工的岗位将发生转变，同时超过四分之一的高管也无法幸免。这使得 CEO 的盲目乐观尤为危险。CHRO 的核心机会在于，识别并弥合组织内部的人才与能力错配，确保组织具备驾驭变革的真实能力。
3. 未来关键能力：创造力与协作力超越技术力
在一个看似由技术驱动的变革时代，一个反直觉的真相浮出水面：人类独有的软性能力正变得空前重要。一项核心洞察指出：
高管们认为，到 2025 年，对组织最有价值的技能将是创造力。
当技术性工作可以被 AI 高效辅助时，企业的核心竞争力将从技术熟练度转向那些机器无法复制的能力。高管们认为，团队建设和协作能力与软件开发和编码同等重要，甚至领先于分析和数据科学。创造力，将成为引领未来的关键。
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二、CHRO 的三大新使命：未来 36 个月的行动框架
为应对挑战，CHRO 需要一个清晰、可执行的战略框架，围绕以下三大新使命展开行动。
1. AI 人才战略 (Talent Strategy for AI)
目标：重新设计人才的“选、育、用、留”体系，构建一支 AI 增强型团队。
行动建议：
重塑岗位与技能图谱：推动对现有岗位职责的重新定义，将工作重心从执行重复性任务，转向利用 AI 进行分析、创造和战略决策。
推动全员技能再培训：将 AI 技能提升视为员工重大的职业发展机遇。尤其要重点投资于高绩效员工，因为 AI 无法放大平庸的绩效，它带来的是一场革命而非演进，其真正价值在于将优秀人才的能力提升到全新高度。
将人力资源部作为战略试点：要让全员拥抱 AI，首先要从人力资源部开始。CHRO 应将 HR 部门打造为组织内 AI 转型的战略试点项目，率先对 HR 专业人员进行再培训，使其成为组织内 AI 应用的实践者、引领者和赋能者。
2. 组织运营模式重构 (Operating Model Redesign)
目标：打造更敏捷、更智能、更具创造力的组织模式，以释放 AI 的全部潜力。
行动建议：
聚焦高价值应用场景：避免被海量的可能性分散精力。集中资源投资于三到五个最具商业影响力的 AI 应用场景（“Focus on the top five. Or three.”），以点带面，实现价值最大化。
建立快速迭代与试错文化：鼓励团队以“快速失败”（fail fast）的方式进行小范围实验。建立跨部门的反馈循环机制，系统性地分享成功案例、失败教训和实践经验。
利用 AI 优化工作流程：应用 AI 增强的流程挖掘技术，深入分析现有工作流程，精准识别瓶颈与低效环节，并通过智能化改造加速决策效率。
3. AI 治理与伦理 (AI Governance)
目标：建立负责任的 AI 使用框架，确保技术向善，规避潜在风险。
行动建议：
建立明确的道德准则：制定并推行一套清晰的 AI 道德使用框架，其中包含明确的标准、指南和行为期望。
保障数据安全与隐私：在鼓励全员实验的同时，必须围绕数据保护和道德规范设立明确的护栏，确保创新在安全可控的范围内进行。
确保透明与公平：在招聘、绩效评估等关键人力资源环节应用 AI 时，必须建立有效的机制来管理算法偏见，确保决策过程的透明度与公平性。
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三、从战略伙伴到未来设计师：CHRO 的新定位
生成式 AI 正在推动 CHRO 的角色发生根本性演进。CHRO 必须从被 60% 高管视为被动的行政支持者，进化为主动的战略引擎，成为组织未来工作模式的总设计师和 AI 时代人力资本的管理者。CHRO 的新角色是通过前瞻性地引导 AI 在人才与组织层面的落地，主动重塑组织文化、决策模式和业务节奏。
在最高管理层中，CHRO 的新定位是连接技术、人才与业务战略的关键枢纽。AI 的成功绝非单一部门的责任，而需要建立一个由业务、IT 和人力资源负责人共同负责的问责模式。在这个领导力“三驾马车”中，CHRO 作为平等的战略伙伴，确保技术投资能够真正转化为组织能力和商业价值。
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决胜未来，重在组织能力的设计
生成式 AI 时代已经到来，领先的企业正在迅速采取行动。最终的成功者，将是那些能够围绕人才与技能建立灵活、深思熟虑的战略，并积极克服组织焦虑、奖励热情、拥抱包容与乐观的组织。
在生成式 AI 时代，决定企业未来竞争力的不是技术本身，而是 CHRO 对组织与人才能力的重新设计能力。
AI governance
2025年11月24日
AI governance
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
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