Is The HR Profession As We Know It Doomed? In A Strange Way, Yes.I just spent a week in London meeting with several dozen companies and most of the discussion was about AI. The overwhelming majority of the conversations were about how companies are struggling, pushing, and agitating about the implications of AI, both within HR and within their teams.
Coming from the CEO and CFO, HR team are under intense pressure to automate, improve their services, and reduce headcount with AI. Yes, we know AI is a technology for growth and scale, but the main message right now is “hurry up and do some productivity projects.”
And “Productivity,” as you know, is a veiled way of saying “Downsizing.”
So before I get back to HR, let me discuss downsizing.
It’s absolutely true that almost every company we work with has too many people. Why?
We have a sloppy way of hiring people, allocating resources, and managing work. We delegate “headcount” to managers and they go out and hire as many people as they can.
We don’t really teach (or incent) managers how to build “productivity,” we actually do the opposite. We tend to reward them for “hiring more people.”
The result is a problem I just talked about with a large advertising company: too many weird jobs and no consistency or structure to our work. This particular company has around 100,000 employees and more than 60,000 job titles. In other words almost every job is “invented for this person.” It’s insane.
The whole reason we have companies (and not individual craftsmen) is to build scale. If we expect every individual manager to figure out how to scale, we’re more or less designing low productivity into the business.
There are some simple models we use: call centers, global services groups, shared services, capability communities, and centers of excellence. But that kind of high-level productivity design is now becoming obsolete. In this new era of high-powered multi-functional agents, we need to go much further.
Elon Musk likes the “first principles” approach. Fire everyone and start from “first principles,” only hiring the people you urgently need to build, sell, and support your product. That may work in small companies but when you’re big there are too many “support services” to consider.
One of the companies we are working with has “program managers” and “project managers” and “analysts” sprinkled all over the organization in random places. In other words, their core staff don’t know how to manage projects, programs, or data. So there’s a bunch of overhead staff doing this for them. Drives me crazy. This took place because there was no discipline in hiring, so each group “bulked up” with staff.
This is really business as usual. Organization design is an old, crusty, under-utilized domain so most companies barely think about it. IBM told me a few years ago that their “org design” strategy is to “hire a high performing executive and let him or her figure it out.” I hear that, it’s quite common.
The bottom line is this: if we want to get a sound ROI from all these AI tools and agents we have to get a lot smarter about “work design.” And that is not building org charts, it’s the basics of figuring out our workflows, areas of common and uncommon process, and where and how we can automate.
Most of our clients have tons of productivity systems already (ServiceNow, Salesforce, Workday, whatever), but they either don’t know how or don’t have the discipline to use them well. So they just keep hiring people.
As an engineer I see this visibly all the time. It’s very easy to delegate a “problem” to a person, and not think about it as “plumbing.” But it is plumbing. As Tanuj Kapilashrami from Standard Charter put it, we need to focus on plumbing first, then we figure out where to apply AI.
This means we can’t just cross our fingers and hope that the Microsoft Copilot is going to make everyone more productive. We need to look at business processes and skills at the core, and then literally reinvent our companies around these new AI tools.
And skills are very important. The reason companies hire a bunch of “analysts” and “project managers” is because individuals and existing managers just aren’t good at their jobs. We all need to learn how to project manage, schedule, and analyze work. That way these high-powered specialists can work on big things, not sit in staff meetings taking notes (where AI note-takers do this well).
(By the way, I have to guess that we’ll soon have AI agents for project management, program management, and functional analytics, so those staff jobs are going to be automated next!)
How Does This Impact HR
Let’s get back to HR. Given this massive effort to re-engineer and implement AI, where does HR fit?
Well fundamentally HR is tasked to build process, expertise, and advisory services around the “people processes” in the company. That means hiring, developing, managing, paying, rewarding, and supporting people. It’s a big mission, and when we start to focus on “productivity” then HR must be involved.
The general belief is that a “well run” HR team has about a 1:100 ratio to the company. In other words, if you have 10,000 employees you’re going to have around 100 HR people. And the HR team doesn’t just run around doing things, they buy and build HR technology for scale. So HR itself, as a “plumbing” type of operation, needs to be “lean and mean.”
If your CEO wants you to hire 50 top notch AI engineers you can’t just start phoning everyone you know: you must decide precisely how you’re going to do this in a scalable, efficient, and highly effective way. (AI engineers are rare, they’re hard to hire!)
So your little HR team has to think about productivity. Should we outsource this? (Which is a cheap and dirty way to look productive.) Should we buy a talent intelligence or sourcing system? Should we hire three high-powered recruiters? You know where I’m going. We have to find a way to “be productive” while we try to “make the company productive.”
This means we, as a support and advisory function (HR professionals spend a lot of time coaching and supporting managers) have to stop creating forms and checklists and implement AI agents as fast as we can. Why? Because so much of our work is transactional, workflow-oriented, and administratively complex. And AI can do a lot of amazing things, like “assessing the skills of an AI engineer” for example.
(Our AI Galileo can literally evaluate a recorded interview and give you a pretty good assessment of an individuals skills, mapped against the Lightcast, SHL, and Heidrick functional and leadership models.)
Let’s assume we do this well, and HR technology vendors give us good products. We wind up with amazing recruiting agents, AI agents for employee training, onboarding, and coaching, AI agents that help with performance management, AI agents for succession and careers, and AI agents that deal with all the myriad of personal benefits and workplace questions people have. Where do we end up?
Do we “automate away” our own jobs?
Well, in a way the answer is yes.
AI, through its miraculous data integration and generation capabilities, can probably do 50—75% of the work we do in HR.
All this is far from built out yet, but it’s clearly coming.
(We just talked with a large pharmaceutical company that is “all-AI” and they manage a team of 6,000+ scientists and manufacturing experts with only ten people in learning and development. They’ve automated training, compliance tracking, onboarding, leadership support, and all the details of training operations.)
Could you do all that for a fast-growing 6,000 person company with 10 people? I doubt it. Most companies would have more than 10 people in sales training and sales enablement alone.
So here’s my point. HR, like other functional areas in our companies, is going to have a real-life identity crisis. If you can’t figure out how to move your HR function up the maturity level quickly (check out our Systemic HR maturity model) someone’s just going to cut your headcount (the Elon Musk approach). Then you’ll be figuring out AI in a hurry.
(Galileo can assess your HR maturity with its “consulting mode,” by the way.)
I’m not saying this is easy. The AI products we need barely exist yet. But the pressure is on.
You shouldn’t wait for the CFO to point his “productivity gun” in your face, you have to get ahead of this wave. Start pushing yourself to fix plumbing, check out the new tools in the market, get your IT team involved, and redesign your work using your own expertise. Many surprisingly good things will happen.
Let me give you an example.
A few years ago Chipotle adopted an AI-based agent system for recruiting, effectively automating a complex workflow for hiring. Not only did it save millions of dollars, the “speed and quality” of hiring went up so high the CEO talked about it as their top “revenue driver” with Jim Cramer on CNBC.
In other words this “identity crisis” in HR is a good thing.
Our recruiting, training, and employee services groups are too big. AI can automate enormous amounts of this work. So my advice is this. As the AI wave sweeps across your company, get out your old “org design” book and start redesigning how your HR team operates right now. Then you can go to the AI vendors and tell them what you want. That’s the secret to keeping HR in tip-top shape.
Will HR go away? Well a lot of the process, data management, and support roles will absolutely change. And yes, employees and job candidates will happily use intelligent bots instead of calling their favorite HR manager.
But as a Superworker, you, as an HR professional will do more interesting things. You’ll become a consultant; you’ll manage and train AI systems; and you’ll have much more real-time information about the strength and weaknesses of your company. We’re just going to have to lean into this AI wave to get there.
As AI agents arrive, it’s time to seriously re-engineer HR. And this time it’s not a transformation, it’s a reinvention.
Bottom line is this. Don’t wait for Workday, SAP, or some other vendor to “invent” a tool that changes your HR operation. You should do it yourself first and bring your IT people with you. That way you’ll buy and build the AI systems you need, and the result will be a new career, an even better HR function, and the opportunity to help your company move from “hiring” to “productivity” in the future.
我刚刚在伦敦与数十家企业进行了为期一周的交流，大部分讨论都围绕着AI展开。绝大多数对话的主题是：公司在应对AI带来的影响时，感到焦虑、推动、甚至焦躁不安，这种焦虑不仅体现在HR部门，也体现在各业务团队中。
在CEO和CFO的压力下，HR团队正被要求加速自动化、优化服务、并通过AI实现人员精简。虽然我们都知道AI是一种能够促进增长和规模化的技术，但当前传递出的主要信息是：“赶紧推动生产力项目。”
而所谓的“生产力”，实际上就是“裁员”的委婉说法。
先谈谈裁员
几乎我们接触的每一家企业，都的确存在人员过剩的问题。这是为什么呢？
因为我们的招聘、资源配置和工作管理方式本身就非常低效。我们将“编制名额”下放给各级管理者，而他们则倾向于尽可能多地招聘人员。
我们并没有真正教导或激励管理者如何构建高效的生产力，反而往往奖励他们“扩大团队规模”。结果就是，像我最近在一家大型广告公司看到的那样，组织中充满了各种各样的职位，但缺乏统一性和结构性。这家公司有约10万名员工，却设有超过6万个不同的岗位头衔——几乎每个职位都是为某个人量身定制的，这种做法显然荒谬。
企业存在的根本目的，是为了实现规模化。如果每个部门经理都各自为战，自行搭建团队架构，那无异于将低效深植于企业之中。
虽然我们有一些基本的组织效率模型，比如呼叫中心、全球服务中心、共享服务、能力中心等，但这些传统设计在当下正逐渐过时。在高性能多功能AI代理全面普及的时代，我们必须走得更远。
从“第一性原理”重构组织？
Elon Musk 推崇“第一性原理”方法——即解散现有团队，只从零开始招聘最核心、最迫切需要的人员。这种方法在小型公司或许奏效，但在大型企业中，由于存在大量“支持服务”，简单地“砍掉重建”并不可行。
现实中，很多公司在各个角落散布着项目经理、程序经理、分析师等职位，因为核心员工缺乏管理项目、推进计划、或进行数据分析的能力。由于招聘过程中缺乏严格的标准和规划，各部门纷纷自行扩编，导致组织臃肿、效率低下。
组织设计本来就是一门古老且被严重忽视的学问，多数公司对此缺乏系统化思考。IBM 曾表示，他们的组织设计策略是“聘请一位高绩效高管，让他/她自己摸索出解决方案”——这实际上是行业普遍现象。
AI真正改变的，是“工作设计”
如果我们希望从AI工具和代理中获得真正的投资回报率，就必须彻底重新思考“工作设计”——不仅仅是画组织结构图，而是要厘清工作流程、标准化与非标准化的业务环节，并找出可以自动化的领域。
尽管大多数企业已经部署了大量的生产力系统（如ServiceNow、Salesforce、Workday等），但由于缺乏使用这些系统的能力或纪律，反而持续地通过“增加人手”来解决问题。
作为一名工程师，我对此体会尤深。将问题推给某个人远比优化底层“管道”来得容易。然而，管理工作流程就像修建城市水管系统——如果基础设施不合理，再先进的AI工具也无济于事。
正如渣打银行Tanuj Kapilashrami所说：“必须先修好管道，才能合理应用AI。”
这意味着，我们不能指望微软Copilot之类的工具神奇地提升员工生产力。我们必须从根本上重新审视业务流程与员工技能，并围绕AI重新设计整个企业运作模式。
员工技能，未来的关键
企业之所以聘请大量“分析师”和“项目经理”，往往是因为普通员工和管理者缺乏项目管理、时间安排、数据分析等基本技能。未来，所有人都需要掌握这些能力，而不再依赖大量辅助人员。高阶专业人才应当专注于重大事务，而不是出席会议做会议记录（AI记录工具早已能胜任此事）。
（顺便提一句，我预测很快就会出现AI项目经理、AI程序经理、AI数据分析师——这些岗位也将逐步被自动化！）
那么HR会怎样？
回到HR领域，当企业致力于重塑流程、导入AI时，HR的角色至关重要。
HR的本质任务是构建并管理围绕“人”的各项流程：招聘、培养、管理、薪酬、激励与支持等。这项使命极为庞大，当公司将焦点转向“提升生产力”时，HR必须积极参与。
一般认为，一个运作良好的HR团队与公司整体人数的理想比例是1:100。也就是说，一家拥有1万名员工的公司，大约需要100名HR人员。而优秀的HR团队不仅自己高效运作，更会采购、搭建技术系统，以实现规模化管理。
举例来说，如果CEO要求你招聘50名顶尖AI工程师，你不能只是随便打几个电话，而是要设计一套高效、可扩展的方法。这可能包括外包、引进人才情报系统、招聘高端猎头，等等。总之，HR自身也必须成为高效运作的样板。
因此，HR团队必须迅速引入AI代理，取代大量重复性事务，尤其是那些依赖工作流、流程管理和行政性处理的工作。比如，我们的Galileo系统已经可以自动评估候选人的面试表现，并将其技能映射到Lightcast、SHL和Heidrick的领导力模型。
未来，HR工作会消失吗？
某种程度上，答案是肯定的。
凭借出色的数据整合和生成能力，AI可以完成50%-75%的HR工作。目前这些AI系统尚未完全成熟，但趋势已经非常明显。
我们刚刚与一家大型制药企业交流，他们已经基本实现了“全AI化管理”，以仅10人规模的学习与发展团队，服务6000多名科学家和制造专家。他们通过AI自动完成了培训、合规追踪、入职辅导、领导力支持等任务。对于大多数公司来说，这种效率简直是难以想象的。
HR将迎来身份危机
未来，HR必须迅速向更高的成熟度迈进（可以参考我们提出的Systemic HR Maturity Model）。否则，就会像Elon Musk那样，被大规模裁员，并被迫在短时间内仓促上马AI项目。
我并不是说这条路轻松易行。事实上，市面上真正成熟的AI HR产品还非常有限。但压力已经到来。
HR不能等着CFO拿着“生产力枪”指着自己，必须主动出击，修好内部“管道”，试用新工具，联合IT团队，重新设计工作模式。这样，你将能主动选择适合自己公司的AI系统，并构建一个全新的、充满机遇的职业未来。
结语：HR的重塑与再创造
让我们看看Chipotle的案例。他们通过部署基于AI的招聘代理，成功自动化了复杂的招聘流程，不仅节省了数百万美元，还大幅提升了招聘速度和质量。甚至在接受CNBC采访时，CEO将这一成果称为公司的“主要营收驱动因素”。
这场HR身份危机，其实是一个难得的机遇。
我们今天的招聘、培训、员工服务团队规模普遍过大。AI将能够自动化其中大量工作。我的建议是：在AI浪潮席卷而来之前，立即拿起你尘封已久的组织设计手册，重新设计HR团队的运作方式。这样，当面对AI供应商时，你可以主动提出自己的需求，而不是被动接受他们的产品。
未来HR不会消失，但大量传统流程、数据管理与支持岗位将发生剧变。员工与候选人也会越来越习惯通过智能机器人，而非人力HR来解决问题。
不过，真正优秀的HR专业人士，将会变成超能型人才（Superworker）——你将成为企业战略顾问、AI系统训练师，并且能够实时掌握公司人才与流程的整体健康状况。
这次，不再是简单的“转型”，而是真正意义上的“再创造”。
学习与发展
2025年04月26日
学习与发展
2024年组织中人力资源部门的21个关键角色-来自AIHR
组织中人力资源部门的21个关键角色，分为“关键角色”、“合规角色”和“新兴角色”三个部分，如下所示：
关键角色
吸引候选人：开发和执行策略以吸引合适的候选人。
选择候选人：从众多申请者中挑选出最适合的候选人。
内部和外部招聘：内部晋升和外部招聘的管理。
绩效评估：对员工的工作表现进行评估。
薪酬：设计和实施薪酬策略。
员工福利管理：设计和管理员工福利计划。
学习与发展：确保员工技能与组织需求保持一致。
合规角色
晋升：晋升机制的设计与实施。
问题解决小组：创建和管理解决问题的小组。
全面质量管理（TQM）：实施全面质量管理以提高服务或产品质量。
信息共享：确保重要信息能够及时传达给所有员工。
组织发展：通过战略性的人力资源管理提升组织效能。
调查管理：管理各种员工调查，收集反馈以改进工作环境。
合规管理：确保公司遵守所有相关法律和规章制度。
商业合作伙伴：HR作为管理层的战略合作伙伴，提供人力资源解决方案。
新兴角色
数据与分析管理：使用数据分析来支持决策过程。
人力资源技术管理：管理和优化HR相关的技术和系统。
变更管理：领导和管理组织变更。
员工体验：设计和改进员工的整体工作体验。
多元化、公平、包容和归属感（DEIB）：推广和实施多元化和包容性策略。
公关：管理公司的公共形象和应对公关危机。
原文来自：https://www.aihr.com/blog/human-resources-roles/
Attracting candidates, Selecting candidates, Hiring from within and from outside, Performance appraisals, Compensation, Employee benefit management, Learning & development, Promotions, Problem-solving groups, Total quality management (TQM), Information sharing, Organizational development, Survey management, Compliance management, Business partnering, Data & analytics management, HR technology management, Change management, Employee experience, DEIB, PR
吸引候选人、选择候选人、内部和外部招聘、绩效评估、薪酬、员工福利管理、学习与发展、晋升、问题解决小组、全面质量管理 (TQM)、信息共享、组织发展、调查管理、合规管理、业务合作、数据与分析管理、人力资源技术管理、变革管理、员工体验、DEIB、公共关系
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