AI Agents, The New Workforce We’re Not Quite Ready For (Agentic AI)Josh Bersin 刚刚谈到：AI代理人的兴起标志着工作方式的一次革命。这些AI代理人不仅仅是工具，而是未来的团队成员。从开发培训课程到管理招聘过程，AI代理人的能力正被企业系统广泛利用。科技领袖和投资者对此展现出了极大的兴趣和投资。企业需要为这种变革做好准备，包括安全性和管理实践的更新。
我们一起来看下，英文原文附录链接在最后！
AI智能体，新一代劳动力，我们还没有做好准备
智能体正在到来，智能体正在到来。
如果你关注AI技术市场，你就会知道，最近有很多关于“智能体AI”的讨论。换句话说，我们的AI助手开始拥有更多自主能力。不再只是回答问题和写诗，它们现在可以代表我们“做事情”。
这正是长久以来预测的AI下一个大趋势。埃里克·施密特最近谈到了这一点，微软也在讨论，像Mayfield这样的投资者正在投入资金。而这种演变确实将彻底革新我们的系统。
可以这样想：“大语言模型”是我们过去两年一直在学习的内容，它们现在正逐步转变为“大行动模型”。智能体不仅仅会回答问题，它还会为我们做事情。
消费场景是无穷无尽的：为我预订航班，为我买票，向我的朋友发送电子邮件。但在商业领域，这种转变将颠覆并破坏我们的许多企业系统。它还将改变我们工作的方式、管理的方式以及我们对团队的思考方式。
考虑我们与供应商讨论的两个HR用例。
学习与发展（L&D）AI智能体
想象一下，你指示一个L&D AI智能体“为我们的销售人员创建一个15分钟的课程，以教授他们如何定位我们的新产品”。AI智能体将根据你的输入（课程时长、目标受众等），向主题专家发送电子邮件，视频记录他们的评论和专业知识，整合新产品信息，构建课程，并将其发送给L&D负责人进行验证。作为经理，你可以审查课程，并指示智能体收紧信息或添加更多主题，课程将重新创建，然后你可以说“可以上线了”。智能体随后会将课程发布到学习管理系统（LMS）中，向所有销售人员群发电子邮件，并开始监控学习活动。几小时后，智能体会运行分析，并向经理反馈进展情况。
是的，这在今天完全可能。而且很快就会启动。
再来看第二个例子。
招聘AI智能体
人才招聘负责人收到了大量关于高级软件工程师的职位要求。她指示招聘AI智能体开始搜索。智能体询问招聘人员的地点偏好、职位级别选择、薪资范围和技能要求，然后开始工作。智能体扫描LinkedIn和其他招聘工具，查看ATS中的现有候选人，同时也查看所有内部员工的合格技能。智能体随后优化这份名单，创建一个“面试候选人短名单”，并回到招聘负责人那里征求意见。在就地点和薪资范围达成一致后，智能体返回并向这些候选人发送了一封富有吸引力的电子邮件，并附上一个视频面试门户链接，让他们进行面试。面试被录制下来，AI智能体使用面试智能工具来评估和筛选候选人，询问他们的时间安排，并为他们安排现场面试。在此过程中，AI智能体会查看他们的背景，搜索社交媒体，查看他们的各种联系，并可能查看他们的GitHub等平台和其他凭证，然后为每位候选人创建一个档案。
这些智能体很快就会出现，对我们许多人来说，它们看起来和感觉上会像“员工”一样。我们将不得不对它们进行培训、入职和指导。随着它们在各自的角色中“成熟”并成长，我们将它们连接到更多的系统、更多的人和更多的数据上。
Lattice的首席执行官萨拉·富兰克林大约一个月前实际上提出了这个概念，尽管遭到了反对声音，但我认为她是对的。这些智能体实际上将属于组织结构图的一部分。我们的工作将是管理它们，确保它们的安全，并监督它们的安全性。
还有更多内容即将到来
虽然感觉像科幻小说，但这一切正在发生。而且它不仅将改变我们的HR技术堆栈，还将改变整个企业技术格局，也让我们的HR角色变得更加轻松。
原文来自: https://joshbersin.com/2024/09/agentic-ai-ai-agents-the-new-workforce-were-not-quite-ready-for/
AI
2024年09月06日
AI
Cornerstone Galaxy: Acquisition Of SkyHive Could Pay OffCornerstone在人力资源技术领域长期以来一直是学习管理系统（LMS）的领导者。公司最近推出了Galaxy，这是一个集成了人工智能的全新人才管理平台。这一重大进展是在一系列收购之后实现的，尤其是最近收购了SkyHive，显著增强了公司的数据处理能力。Galaxy平台通过提供全面的技能发展、绩效管理和员工晋升系统，为HR技术空间树立了新标准。
Galaxy区别于市场上其他基于技能的或智能平台，例如Eightfold主要从人才获取开始，而Gloat着眼于人才流动性。Galaxy则从另一个角度出发，即员工发展，这是由Cornerstone在学习与发展（L&D）领域深厚的背景所支撑的。Galaxy系统内置了完整的用户界面，能够推断技能，让员工标记和评估自己的技能，帮助员工找到并完成各种学习形式，管理合规性和认证程序，通过任务、评估或管理辅导提升技能。
通过整合性能管理、发展计划、继任计划，以及招聘过程，Galaxy使公司能够通过绩效管理推动技能发展。在收购SkyHive之前，Cornerstone试图仅使用其LMS信息的数据集来实现这一目标，但这些数据并不足以构建完整的人工智能语料库。通过这次收购，Cornerstone获得了一个完整的劳动力市场数据系统、一个公司中立的职位架构以及大量行业技能，使Galaxy能够与其他主要的人才智能和人才市场供应商直接竞争。
Cornerstone spent the last decade acquiring LMS and talent software companies, all in a goal to build an integrated skills platform. Finally, after years of hard work and integration, the company introduces Galaxy, an advanced offering in the world of AI-powered HR systems.
Before I explain Galaxy, the history is important. Founded in 1999, Cornerstone started as an e-learning platform company (CyberU). The company established a foothold in the emerging LMS market and grew through strong marketing, sales, and product innovation. Since then the company has gone public, reached a $5.2 billion valuation, and was then acquired by a private equity firm (Aug. 2021, three years ago).
The new management team continued to acquire companies (EdCast, SumTotal, Talespin, and most recently SkyHive) and has now stitched these systems together into a unified platform called Galaxy. Galaxy, as I show below, is a skills-powered integrated talent management platform, built around the core of learning management. And this is what makes it unique.
The other talent intelligence or skills-based platforms started elsewhere. Eightfold started in talent acquisition; Gloat started in talent mobility; SeekOut started in recruiting; Beamery started in CRM; and players like Retrain.ai and NeoBrain started in more vertical domains. Each of these companies use large-scale profile data to infer skills, give companies tools to find and match candidates, and eventually to deliver learning.
Cornerstone, with deep background in L&D, is coming at this from another direction: employee development. The Galaxy system, which is built into a complete user interface, infers skills, lets employees tag and assess their skills, helps employees find and complete many forms of learning, manage compliance and certification programs, and advance skills through gigs, assignments, assessments, or management coaching. And since Cornerstone is an integrated talent suite, the system lets companies drive skills through performance management, development planning, succession planning, and also recruiting.
Before the acquisition of SkyHive, Cornerstone was trying to do this with its own data set of LMS information. This data, which includes billions of learning records, was simply not sufficient to build out the entire AI corpus. By acquiring SkyHive, Cornerstone gained an entire labor market system of data, a company-neutral job architecture, and lots of industry skills. This brings Galaxy into direct competition with the other major talent intelligence and talent marketplace vendors.
I have not yet talked with Galaxy customers, but the user experience is integrated and shows the sophistication of thinking under the covers. Remember that Cornerstone acquired Evolv, Clustree, and EdCast before acquiring SkyHive, so the team has been building AI capabilities and use-cases for several years. And now that Cornerstone has a VR platform for learning, more use-cases are coming.
While I don’t know Cornerstone’s revenues, the leadership team assures me that the company is growing and the profitability is high. This means the company has long-term sustainability and despite its many acquisitions, is likely to evolve to “Oracle-like” status. (Oracle has acquired hundreds of companies over the years and now looks at M&A as one of its core strengths).
Here’s the major play in the market. With 7,000+ customers, Cornerstone has many customers shopping for new tools. If Galaxy is as solid as it looked in the demos, some percentage of these buyers could upgrade to Galaxy and avoid the purchase of Gloat, Eightfold, or another LMS. While we cannot be sure where Galaxy will play, for companies that want to deploy a skills architecture across all talent practices, it looks like a solid option.
Cornerstone Vision:
Cornerstone User Experience
Cornerstone Career and Talent Marketplace
Cornerstone Performance Management
Skills in Goal Management
Why Cornerstone Still Matters
Cornerstone has a massive customer base. The users of Cornerstone, Saba, SumTotal, Lumesse, and Halogen include many of the world’s largest companies and thousands of mid-market organizations as well. These organizations have invested billions of dollars into learning infrastructure, content, and user portals to reach employees. If Cornerstone Galaxy delivers on its promise, the company can help many of these organizations avoid buying lots of standalone new tools. And given Cornerstone’s size, the company could become, as I mentioned above, the “Oracle” of the space.
And note, by the way, that a recent survey by HR.com found that the top rated HR tech issue to address is L&D infrastructure, so this issue is on everyone’s mind.
While the market is highly competitive and there are many skills-based tools in the market, Cornerstone’s focus on L&D is unique. None of the other major LMS vendors have the skills infrastructure of Cornerstone today.
If your skills strategy is focused on building skills, Galaxy may be the answer.
More to come as we talk with more Galaxy customers.
Additional Information
AI
2024年09月03日
AI
Agency Law and the Workday Lawsuit
文章讨论了在Workday诉讼中，代理法的相关法律问题。原告声称，Workday的AI筛选工具因种族、年龄和残疾而对他进行了歧视。这起案件提出了HR技术供应商是否可以对歧视性结果直接负责的问题。法律的复杂性包括AI在招聘决策中的角色、代理责任以及对雇主和AI开发者的潜在影响。此案件提醒雇主在实施AI招聘工具时要谨慎，并确保避免法律风险。AI开发者也必须确保其产品无歧视行为，因为该诉讼可能会树立重要的法律先例。
Editor's Note
Agency Law and the Workday Lawsuit
Agency law is so old that it used to be called master and servant law. (That's different from slavery, where human beings were considered the legal property of other humans based on their race, gender, and age, which is partly why we have discrimination laws.)
Today, agency laws refer to principals and agents. All employees are agents of their employer, who is the principal. And employers can have nonemployee agents too when they hire someone to do things on their behalf. Generally, agents owe principals a fiduciary duty to act in the principal's best interest, even when that isn't the agent's best interest.
Agency laws gets tricky fast because you have to figure out who is in charge, what authority was granted, whether the person acting was inside or outside that authority, what duty applies, and who should be held responsible as a matter of fairness and public policy.
Generally, the principal is liable for the acts of the agent, sometimes even when the agent acts outside their authority. And agents acting within their authority are rarely liable for their actions unless it also involves intentional wrongs, like punching someone in the nose.
Enter discrimination, which is generally a creature of statute that may or may not be consistent with general agency law even when the words used are exactly the same.
Discrimination is generally an intentional wrong, but employees are not usually directly liable for discrimination because making employment decisions is part of the way employment works and the employer is always liable for those decisions.
The big exception is harassment because harassment, particularly sexual harassment, is never part of someone's job duties. So in harassment cases, the individual harasser is liable but the employer may not be unless they knew what was going on and didn't do anything about it.
It's confusing and makes your head hurt. And that's just federal discrimination law. Other employment laws, both state and federal, deal with agent liability differently.
Now, let's move to the Workday lawsuit. In that case, the plaintiff is claiming that Workday was an agent of the employer, but not in the sense of someone the employer was directing. They are claiming that Workday has independent liability as an employer too because they were acting like an employer in screening and rejecting applicants for the employer.
But that's kinda the whole point of HR Technology—to save the employer time and resources by doing some of the work. The software doesn't replace the employer's decision making and the employer is going to be liable for any discrimination regardless of whether and how the employer used their software.
If this were a products liability case, the answer would turn on how the product was designed to be used and how the employer used it. But this is an employment law and discrimination case. So, the legal question here is whether a company that makes HR Technology can also be directly liable for discriminatory outcomes when the employer uses that technology.
We don't have an answer to that yet and won't for a while. That's because this case is just at the pleading stage and hasn't been decided based on the evidence. What's happened so far is Workday filed a motion to dismiss based on the allegations in the complaint. Basically, Workday said, "Hey, we're just a software company. We don't make employment decisions; the employer does. It's the employer who is responsible for using our software in a way that doesn't discriminate. So, please let us out of the case. Then the plaintiff and EEOC said it's too soon to decide that. If all of the allegations in the lawsuit are considered true, then the plaintiff has made viable legal claims against Workday.
Those claims are that Workday's screening function acts like the employer in evaluating applications and rejecting or accepting them for the next level of review. This is similar to what third party recruiters and other employment agencies do and those folks are generally liable for those decisions under discrimination law. In addition, Workday could even be an agent of the employer if the employer has directly delegated that screening function to the software.
We're not to the question of whether a software company is really an agent of the employer or is even acting like an employment agency. And even if it is, whether it's the kind of agency that has direct liability or whether it's just the employer who ends up liable. This will all depend on statutory definitions and actual evidence about how the software is designed, how it works, and how the employer used it.
We also aren't at the point where we look at the contracts between the employer and Workday, how liability is allocated, whether there are indemnity clauses, and whether these type of contractual defenses even apply if Workday meets the statutory definition of an employer or agent who can be liable under Title VII.
Causation will also be a big issue because how the employer sets up the software, it's level of supervision of what happens with the software, and what's really going on in the screening process will all be extremely important.
The only thing that's been decided so far is that the plaintiff filed a viable claim against Workday and the lawsuit can proceed. Here are the details of the case and some good general advice for employers using HR Technology in any employment decision making process.
- Heather Bussing
AI Workplace Screener Faces Bias Lawsuit: 5 Lessons for Employers and 5 Lessons for AI Developers
by Anne Yarovoy Khan, John Polson, and Erica Wilson
at Fisher Phillips
A California federal court just allowed a frustrated job applicant to proceed with an employment discrimination lawsuit against an AI-based vendor after more than 100 employers that use the vendor’s screening tools rejected him. The judge’s July 12 decision allows the class action against Workday to continue based on employment decisions made by Workday’s customers on the theory that Workday served as an “agent” for all of the employers that rejected him and that its algorithmic screening tools were biased against his race, age, and disability status. The lawsuit can teach valuable lessons to employers and AI developers alike. What are five things that employers can learn from this case, and what are five things that AI developers need to know?
AI Job Screening Tool Leads to 100+ Rejections
Here is a quick rundown of the allegations contained in the complaint. It’s important to remember that this case is in the very earliest stages of litigation, and Workday has not yet even provided a direct response to the allegations – so take these points with a grain of salt and recognize that they may even be proven false.
Derek Mobley is a Black man over the age of 40 who self-identifies as having anxiety and depression. He has a degree in finance from Morehouse College and extensive experience in various financial, IT help-desk, and customer service positions.
Between 2017 and 2024, Mobley applied to more than 100 jobs with companies that use Workday’s AI-based hiring tools – and says he was rejected every single time. He would see a job posting on a third-party website (like LinkedIn), click on the job link, and be redirected to the Workday platform.
Thousands of companies use Workday’s AI-based applicant screening tools, which include personality and cognitive tests. They then interpret a candidate’s qualifications through advanced algorithmic methods and can automatically reject them or advance them along the hiring process.
Mobley alleges the AI systems reflect illegal biases and rely on biased training data. He notes the fact that his race could be identified because he graduated from a historically Black college, his age could be determined by his graduation year, and his mental disabilities could be revealed through the personality tests.
He filed a federal lawsuit against Workday alleging race discrimination under Title VII and Section 1981, age discrimination under the ADEA, and disability discrimination under the ADA.
But he didn’t file just any type of lawsuit. He filed a class action claim, seeking to represent all applicants like him who weren’t hired because of the alleged discriminatory screening process.
Workday asked the court to dismiss the claim on the basis that it was not the employer making the employment decision regarding Mobley, but after over a year of procedural wrangling, the judge gave the green light for Mobley to continue his lawsuit.
Judge Gives Green Light to Discrimination Claim Against AI Developer
Direct Participation in Hiring Process is Key – The judge’s July 12 order says that Workday could potentially be held liable as an “agent” of the employers who rejected Mobley. The employers allegedly delegated traditional hiring functions – including automatically rejecting certain applicants at the screening stage – to Workday’s AI-based algorithmic decision-making tools. That means that Workday’s AI product directly participated in the hiring process.
Middle-of-the-Night Email is Critical – One of the allegations Mobley raises to support his claim that Workday’s AI decision-making tool automatically rejected him was an application he submitted to a particular company at 12:55 a.m. He received a rejection email less than an hour later at 1:50 a.m., making it appear unlikely that human oversight was involved.
“Disparate Impact” Theory Can Be Advanced – Once the judge decided that Workday could be a proper defendant as an agent, she then allowed Mobley to proceed against Workday on a “disparate impact” theory. That means the company didn’t necessarily intend to screen out Mobley based on race, age, or disability, but that it could have set up selection criteria that had the effect of screening out applicants based on those protected criteria. In fact, in one instance, Mobley was rejected for a job at a company where he was currently working on a contract basis doing very similar work.
Not All Software Developers On the Hook – This decision doesn’t mean that all software vendors and AI developers could qualify as “agents” subject to a lawsuit. Take, for example, a vendor that develops a spreadsheet system that simply helps employers sort through applicants. That vendor shouldn’t be part of any later discrimination lawsuit, the court said, even if the employer later uses that system to purposefully sort the candidates by age and rejects all those over 40 years old.
5 Tips for Employers
This lawsuit could have just easily been filed against any of the 100+ employers that rejected Mobley, and they still may be added as parties or sued in separate actions. That is a stark reminder that employers need to tread carefully when implementing AI hiring solutions through third parties. A few tips:
Vet Your Vendors – Ensure your AI vendors follow ethical guidelines and have measures in place to prevent bias before you deploy the tool. This includes understanding the data they use to train their models and the algorithms they employ. Regular audits and evaluations of the AI systems can help identify and mitigate potential biases – but it all starts with asking the right questions at the outset of the relationship and along the way.
Work with Counsel on Indemnification Language – It’s not uncommon for contracts between business partners to include language shifting the cost of litigation and resulting damages from employer to vendor. But make sure you work with counsel when developing such language in these instances. Public policy doesn’t often allow you to transfer the cost of discriminatory behavior to someone else. You may want to place limits on any such indemnity as well, like certain dollar amounts or several months of accrued damages. And you’ll want to make sure that your agreements contain specific guidance on what type of vendor behavior falls under whatever agreement you reach.
Consider Legal Options – Should you be targeted in a discrimination action, consider whether you can take action beyond indemnification when it comes to your AI vendors. Breach of contract claims, deceptive business practice lawsuits, or other formal legal actions to draw the third party into the litigation could work to shield you from shouldering the full responsibility.
Implement Ongoing Monitoring – Regularly monitor the outcomes of your AI hiring tools. This includes tracking the demographic data of applicants and hires to identify any patterns that may suggest bias or have a potential disparate impact. This proactive approach can help you catch and address issues before they become legal problems.
Add the Human Touch – Consider where you will insert human decision-making at critical spots along your hiring process to prevent AI bias, or the appearance of bias. While an automated process that simply screens check-the-box requirements such as necessary licenses, years of experience, educational degrees, and similar objective criteria is low risk, completely replacing human judgment when it comes to making subjective decisions stands at the peak of riskiness when it comes to the use of AI. And make sure you train your HR staff and managers on the proper use of AI when it comes to making hiring or employment-related decisions.
5 Tips for Vendors
While not a complete surprise given all the talk from regulators and others in government regarding concerns with bias in automated decision making tools, this lawsuit should grab the attention of any developer of AI-based hiring tools. When taken in conjunction with the recent ACLU action against Aon Consulting for its use of AI screening platforms, it seems the time for government expressing concerns has been replaced with action. While plaintiffs’ attorneys and government enforcement officials have typically focused on employers when it comes to alleged algorithmic bias, it was only a matter of time before they turned their attention to the developers of these products. Here are some practical steps AI vendors can take now to deal with the threat.
Commit to Trustworthy AI – Make sure the design and delivery of your AI solutions are both responsible and transparent. This includes reviewing marketing and product materials.
Review Your Work – Engage in a risk-based review process throughout your product’s lifecycle. This will help mitigate any unintended consequences.
Team With Your Lawyers – Work hand-in-hand with counsel to help ensure compliance with best practices and all relevant workplace laws – and not just law prohibiting intentional discrimination, but also those barring the unintentional “disparate impact” claims as we see in the Workday lawsuit.
Develop Bias Detection Mechanisms – Implement robust testing and validation processes to detect and eliminate bias in your AI systems. This includes using diverse training data and regularly updating your algorithms to address any identified biases.
Lean Into Outside Assistance – Meanwhile, collaborate with external auditors or third-party reviewers to ensure impartiality in your bias detection efforts.
原文来自：https://www.salary.com/newsletters/law-review/agency-law-and-the-workday-lawsuit/
David Green: The best HR & People Analytics articles of July 2024这个月的《数据驱动HR月报》由Insight222发布了他们的新研究报告《构建人力分析生态系统：运营模式2.0》。在Insight222庆祝成立七周年之际，团队成员们齐聚一堂，共同回顾过去的成就，规划未来的步骤，并庆祝这一成功。此外，本月的重点还包括我有幸在由Mercer组织的LinkedIn直播中担任主持人，主题是“AI时代的技能驱动组织”，并欢迎在上个月加入的2000多名《数据驱动HR月报》新订阅者。本期由Visier赞助。
在案例研究部分，展示了Experian如何通过Visier将报告时间减少了70%。Experian的数据分析团队曾在Excel和Oracle OBI-EE套件中花费大量时间，限制了战略工作。Visier帮助他们显著提高了效率，使其团队能够专注于发掘劳动力洞察力、赋能数据驱动决策，并建立数据驱动的HR文化。
此外，本期还讨论了SHRM在其DEI（多样性、公平与包容性）计划中移除“公平”一词的决定。这一决定在DEI受到持续攻击、许多知名公司撤回DEI承诺的背景下显得尤为令人震惊。一些评论认为，SHRM此举的动机可能是政治性的，而非其所声明的“通过强调首先包容性，旨在解决DE&I项目的当前不足，减少社会反弹和极化”。
I’m just about to go out on vacation in the South of France for three weeks (hurrah!) and with growing evidence that taking a vacation improves physical and mental wellbeing, I’m looking forward to having time to relax, reflect and recharge. Before I go, I’m looking forward to the release this week of our new Insight222 research study: Building the People Analytics Ecosystem: Operating Model v 2.0 (click on the link to register to receive a copy).
Other highlights in July included:
We marked our seventh anniversary at Insight222 by gathering the team together for a whole week to reflect on our achievements, plan the next steps and celebrate our success.
I had the honour of moderating a LinkedIn Live on Skills-Powered Organisations in the Age of AI, organised by Mercer, with Ravin Jesuthasan, CFA, FRSA and Tanuj Kapilashrami. You can watch the recording here.
Welcome to the more than 2000 new subscribers to the Data Driven HR Monthly newsletter, who joined in the last month.
This edition of the Data Driven HR Monthly is sponsored by our friends at Visier
CASE STUDY: How Experian Cut Reporting Time by 70%
Struggling with manual reporting? Experian, a data analytics giant, did too. Their people analytics team spent hours in Excel and Oracle OBI-EE suite limiting strategic work. Visier slashed their reporting time by 70%. Read the case study.
Now, their People Analytics team focuses on:
Uncovering workforce insights
Empowering data-driven decisions
Building a data-driven HR culture
Visier empowers our people to leverage data for better decisions
Ready to unlock your people data's power? Read the case study.
Visier Inc.: Make data-driven HR decisions. Easier. Faster. On-Demand. At Scale.
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SHRM and the war on DEI
I’m not here to beat up on SHRM, but their flabbergasting decision to drop ‘Equity’ from its approach to ‘Inclusion, Equity and Diversity’ seems to have achieved the notable feat of being universally unpopular. To take this decision at a time when DEI is under sustained attack from politicians and when a growing number of prominent companies are backtracking from previous DEI commitments seems peculiar to say the least. It has led some commentators to conclude that SHRM’s surprise move is politically motivated rather than being driven by their stated objective, which SHRM explained as: “By emphasizing Inclusion-first, we aim to address the current shortcomings of DE&I programs, which have led to societal backlash and increasing polarization.” Whatever SHRM’s motive if, as likely, this decision by such an influential body undermines DEI then it is not only unhelpful but bad for employees, bad for organisations, and bad for society. As Shujaat Ahmad writes in his coruscating analysis:
Equity is one of the most clear, tangible measures for culture change on systemic discrimination. Without it, DEIB is lost in a maze of good intentions and half-baked commitments.
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Enjoy reading the collection of resources for July 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 June’s compendium.
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NEW: Insight222 research report on the People Analytics Ecosystem
Access the new Insight222 study here: Building the People Analytics Ecosystem: Operating Model v 2.0 - or by clicking on the image below.
HYBRID, GENERATIVE AI AND THE FUTURE OF WORK
JENS BAIER ET AL - How Work Preferences Are Shifting in the Age of GenAI
When it comes to GenAI’s impact on jobs, talent is aware but unafraid. Although only 5% think that GenAI will replace their jobs, 60% anticipate that they will need to reskill significantly. Most say that they will need help to understand what skills to build.
For the first time since its inception a decade ago, BCG’s Decoding Global Talent study finds that job security is ranked by workers as their number one work preference (see FIG 1). Analysis revealed that workers who expressed concern about the impact of GenAI on their jobs were more likely to prioritise job security. They also recognise the importance of learning, with 60% of workers anticipating they will need to reskill significantly. As the study highlights, to attract and retain talent, organisations will need to solve a complex puzzle. They must anticipate the impact of technology on their workforce and offer robust reskilling programs to help employees stay competitive. (Authors: Jens Stefan Baier Orsolya Kovacs-Ondrejkovic Dr. Tobias Zimmermann Pierre Antebi Dr. Susan Gritzka Sacha Knorr Vinciane Beauchene Carmen Márquez Castro Zoë McFarlane Anja Bates Niharika Jajoria Julie Bedard and Ashish Garg).
FIG 1: What workers value most in a job, 2014-2023 (Source: BCG)
NICOLE SCOBLE-WILLIAMS ET AL - Generative AI and the future of work: Boundless Potential
It’s ‘humans with machines’ and not humans or machines that will transcend leading organizations.
An insightful and comprehensive report by the Deloitte AI Institute on the seismic impact of generative AI on the future of work. The report is structured into three chapters each designed to answer a key question. (1) What is generative AI and how is it being used? (2) What is generative AI’s likely impact on jobs? (3) What are the strategies to prepare organisations for change? There are a ton of insights, case studies and frameworks to learn from. Three that resonated especially with me were: (1) The explanation of the difference between work, jobs, tasks and skills (see FIG 2). (2) Guidance for organisations on how to break down jobs in the generative AI era. (3) The five-step framework for adopting a researcher’s mindset for human-generative SI integration: a) hypothesis formation, b) data collection and analysis, c) broad organisational experimentation, d) iterative testing and feedback, and e) strategy refinement. Authors: Nicole Scoble-Williams GAICD Diane Sinti Jodi Baker Calamai Björn Bringmann Laura Shact Greg Vert Tara Murphy and Susan Cantrell)
FIG 2: Work vs Jobs vs Tasks vs Skills (Source: Deloitte)
JUSTIN SHEMELEY, ANDREW ELSTON, AND JASDEEP KAREER - Transforming HR and People Analytics with AI
AI helps us reclaim capacity for more complex workforce strategy questions. It enables us to identify internal mobility opportunities and conduct scenario planning and hypothesis testing.
In their article, Justin Shemeley Andrew Elston and Jasdeep Kareer, PhD (née Bhambra), summarise some of the key takeaways from the recent Insight222 webinar I moderated on how AI is transforming HR and people analytics. The topics covered include: (1) The current landscape of AI in HR. (2) Short- and long-term impacts on the HR operating model. (3) AI’s role in workforce planning and development. (4) Essential Skills for Leveraging AI in HR. (5) How to build a strong foundation for AI adoption. The article also provides the answers to the questions posed by those that attended the webinar. You can access the entire webinar recording here: Transforming HR and People Analytics with AI.
FIG 3: Demystifying AI in HR and People Analytics (Source: Insight222)
RAVIN JESUTHASAN - Achieving the productivity promise of generative AI requires redesigning work
When he coined The Productivity Paradox, Robert Solow outlined two fundamental reasons why new technologies often don’t deliver on their promise. First, early versions of technologies are often flawed and unsuitable for widespread adoption – this applies less to GenAI. In his thoughtful article, Ravin Jesuthasan, CFA, FRSA tackles Solow’s second reason, which relates to the architecture of work. He outlines that to address this issue, organisations need to undertake systemic work redesign through deconstructing the work, redeploying tasks and creating new ways of working. Ravin cites the six-step framework (see FIG 4) he advanced together with John Boudreau in their book, Reinventing Jobs, and describes the potential productivity gains arising as a result.
FIG 4: Achieving the optimal combinations of humans, automation and AI (Source: Jesuthasan and Boudreau)
PEOPLE ANALYTICS
DELOITTE - 2023 High-Impact People Analytics Research
Prioritizing PA customers means understanding their needs—and how those needs align (or don’t) with the function’s capabilities and broader business priorities.
A new report by Eric Lesser Peter DeBellis and Marc Solow based on a 2023 study by Deloitte of more than 400 organisations across 18 countries presents a People Analytics Maturity Model (see FIG 5) and discusses six key findings. These are: (1) People Analytics has become an organisational imperative. (2) Data culture is the single biggest predictor of people analytics performance. (3) Tech investments mean nothing without human capability (and vice versa). (4) Today’s challenges demand more data from more sources. (5) An expanding customer base means new demands on the people analytics function. (6) People data is business data – treat it as such.
FIG 5: High-Impact People Analytics Maturity Model (Source: Deloitte)
CATHERINE COPPINGER - 4 New Ways to Model Work
With the rise of distributed work, managers are being asked to work in a fundamentally different way than they’ve worked before
In her article, Catherine Coppinger of Worklytics, discusses four new ways to model how work gets done – and how it could be done better: (1) Workday Intensity – see FIG 6 - (“We measure intensity as time spent on digital work as a % of overall workday span”). (2) Work-Life Balance. (3) Manager Effectiveness (“With the rise of distributed work, managers are being asked to work in a fundamentally different way than they’ve worked before”). (4) Sales Effectiveness (“With sales stalling, People Analytics teams are increasingly being asked to weigh in on what can be done to reaccelerate revenue growth”). For more insights on the manager effectiveness topic, listen to Catherine on a recent episode of the Digital HR Leaders podcast: How to Use Passive Data to Enhance Manager Effectiveness.
FIG 6: Workplace Intensity: How do remote and in-office days compare (Source: Worklytics)
PREETHIKA SAINAM, SEIGYOUNG AUH, RICHARD ETTENSON, AND BULENT MENGUC - The High Cost of Misaligned Business and Analytics Goals
It is not only the level of analytics that matters, but also how aligned analytics capabilities are with business goals.
What does success in analytics really mean and how should companies measure it? This was the mission of a study by Preethika Sainam Seigyoung Auh Richard Ettenson PhD and Bulent Menguc. While they found that creating a data-driven culture, adopting advanced analytics capabilities, and employing a well-developed data strategy were all important, the key ingredient is the degree of alignment between business goals and analytics capabilities. Their article presents findings from the study, the differences between misaligned and aligned companies, the cost of misalignment (see FIG 7) and how to measure alignment in seven areas: (1) Culture, (2) Alignment with strategy, (3) Leadership commitment, (4) Operations and structure, (5) Employee empowerment, (6) Proactive market orientation, and (7) Skills and competencies.
FIG 7: The Cost of Misalignment (Source: Sainam et al)
ANDRÉS GARCÍA AYALA - People analytics at the heart of AI’s successful workplace adoption | LEA MIKUS – Five Steps to Kick-Start People Analytics | WILLIS JENSEN - What Makes a Good People Analytics Metric? | RAJA SENGUPTA – 1000 Generative AI Prompts for HR | GUILLAUME LHOTE - The Role of Talent Intelligence in Pharma
In recent editions of the Data Driven HR Monthly, I’ve featured a collection of articles by current and recent people analytics leaders. These act as a spur and inspiration to the field. Five are highlighted here. (1) In his compelling article, Andrés García Ayala, Group Head of People Analytics and Strategic Workforce Planning at Legal & General, discusses five reasons why People Analytics needs to be at the heart of AI’s successful adoption and implementation in the workplace. (2) In a LinkedIn post, Lea Mikus unveils five recommendations to kick-start people analytics in your organisation including getting started by focusing on answering one strategic business question through your people data. (3) In an edition of his excellent Making People Analytics Real Substack, Willis Jensen digs into what makes a ‘good’ and a ‘bad’ people analytics metric (see FIG 8). The secret? Ask yourself: “Can I make a line chart of the metric?” (4) Raja Sengupta provides an invaluable resource for HR and people analytics professionals in a 130 page booklet comprising 1,000 AI prompts for HR across ten HR topics. (5) Guillaume Lhote, Talent Intelligence Lead at Takeda, details the critical role of talent intelligence in the pharmaceutical industry – thanks to Toby Culshaw for highlighting this resource.
FIG 8: Examples of HR metrics (Source: Willis Jensen)
THE EVOLUTION OF HR, LEARNING, AND DATA DRIVEN CULTURE
DAVE ULRICH - Update on HR Business Partner Model Continuing Evolution and Relevance
In the last seven years, HR’s contribution to the business has evolved and is increasing. The HR contribution comes from individual HR professionals who have the competencies to fully engage in business conversations. The HR contribution also comes from HR functions, practices, and analytics increasing stakeholder value.
There’s no one better informed to comment on the evolution of the HR business partner (HRBP) model than Dave Ulrich, given he coined and popularised the model in his seminal 1997 book, Human Resource Champions. In his article, Dave details nine evolutions that are combining to reshape and elevate the future role of the HRBP including these five: (1) People and organisation concerns have evolved to be more central to business success. (2) Talent has evolved to pay increased attention on worktask and meaning (see FIG 9). (3) Leadership has evolved to front-line leaders and emerging competencies. (4) HR delivery has evolved to AI–enabled HR (5) HR analytics has evolved from benchmarking to guidance.
FIG 9: From ‘Workforce’ to ‘Worktask’ (Source: Dave Ulrich)
SERENA HUANG - AI in HR: Missing the Forest for the Trees
By focusing on strategic workforce planning, responsible and ethical AI, and clear ownership for AI adoption, HR can become the strategic AI champion the organization needs.
In her From Data to Action LinkedIn newsletter, Serena H. Huang, Ph.D. bemoans the narrow focus of much of the discussion about AI in HR on automation and cost efficiency. Instead, Serena urges a bolder approach, presenting three ‘big-picture issues’ centred on organisational readiness that HR should focus on: (1) Strategic Workforce Planning (e.g. LinkedIn recently estimates that 55% of jobs will be augmented or disrupted by GenAI – see FIG 10). (2) Responsible and Ethical AI. (3) Clear Ownership: Who is Driving the AI Train? Thanks to Serena for highlighting the recent Digital HR Leaders podcast episode with IBM CHRO Nickle LaMoreaux in her article, where Nickle expanded on IBM’s Responsible AI policy and how this is applied to HR. You can listen to the whole episode here: How IBM Uses AI to Transform its HR Strategies.
FIG 10: GAI’s expected effect on LinkedIn members’ skills globally (Source: LinkedIn Economic Graph Research Institute)
CHIEF ETHERIDGE – 3 Strategies to Position HR for Innovation
Only 28% of HR employees agree that their HR function encourages them to take risks, even if they result in failure. This risk aversion is a major obstacle to innovation.
As the preface for this paper by Chief Etheridge for Gartner states, HR is under pressure to develop innovative solutions for a unique set of organisational challenges such as incorporating new ways of working, establishing digital workplaces, and leveraging artificial intelligence. The paper outlines three strategies HR can implement: (1) Define Innovation’s Value and Benefits to HR. (2) Embed Innovation Networks in HR (see FIG 11 for example from Toyota). (3) Establish Structured Innovation Process for HR (with an example from Fannie Mae).
FIG 11: How Toyota directly infuses HR with expertise and skills (Source: Gartner, adapted from Toyota)
WORKFORCE PLANNING, ORG DESIGN AND SKILLS
MCKINSEY - Help wanted: Charting the challenge of tight labour markets in advanced economies
Companies and economies will need to boost productivity and find new ways to expand the workforce
A comprehensive study by McKinsey on how labour markets in the G8 countries are among the tightest in two decades and are set to get worse as workforce continue to age. The study is packed full of insights, visualisations and charts and is a must-read for anyone involved in workforce planning, recruiting, talent intelligence and people analytics. Four actions are recommended for companies and policy makers: (1) Focus on skilling and reskilling, including attracting talent from unconventional pools, offering more flexible work, and internal mobility. (2) Encourage foreign-born workers with programs to properly integrate them into the workforce (one to note given the hysteria about immigration in all of the eight countries in the study). (3) Shape retirement policies to encourage people to work beyond standard retirement ages and take steps to attract more women into the workforce. (4) Prioritise investment in AI and automation to unlock productivity. (Authors: Anu Madgavkar Olivia White Sven Smit Chris Bradley Ryan Luby and Michael Neary).
FIG 12: 4 scenarios for GDP growth 2023-30 (Source: McKinsey)
JORGE TAMAYO, LEILA DOUMI, SAGAR GOEL, ORSOLYA KOVÁCS-ONDREJKOVIC, AND RAFFAELLA SADUN - Designing a Successful Reskilling Program
In today’s fast-changing work landscape, the ability to reskill will become increasingly vital to staying competitive.
In this article, written as a follow up to their award-winning “Reskilling in the Age of AI”, Jorge Tamayo Leila Doumi Sagar Goel Orsolya Kovacs-Ondrejkovic and Raffaella Sadunshare the results of a reskilling survey that they conducted with chief human resources officers and business leaders, and discuss six paradigms on reskilling. These are: (1) Reskilling is a strategic imperative. (2) Reskilling is the responsibility of every leader and manager. (3) Reskilling is a change management initiative. (4) Employees want to reskill – if programs are attractive. (5) Reskilling takes a village. (6) To reskill successfully, you need to be able to analyse and measure the benefit of your interventions and investments.
SKILLS-BASED ORGANISATIONS SPECIAL
ALLIE NAWRAT - Standard Chartered: ‘The people agenda is a strong enabler of the performance of the bank’ | ALLAN SCHWEYER, BARBARA LOMBARDO, MATT ROSENBAUM, AND PETER SHEPPARD - The Long but Rewarding Journey to Becoming a Skills-Driven Organization | JOSH BERSIN - TechWolf Accelerates Corporate Skills Tech Market With $43 Million Round | MARC EFFRON - Is the Juice Worth the Squeeze? Questions About Becoming a Skills-based Organization | DELOITTE - The skills-based organization: A new operating model for work and the workforce
Following the positive reaction to the MIT/Mercer study, Strategic Shift: Skills-Powered Organizations in the Age of AI, I included in the June edition of Data Driven HR Monthly, as well as the LinkedIn Live I participated in last week with Ravin Jesuthasan and Tanuj Kapilashrami, I thought it helpful to include a ‘special’ in the July edition of Data Driven HR Monthly on skills-based organisations. Six resources are included. (1) Tanuj Kapilashrami, Chief Strategy and Talent Officer at Standard Chartered, sits down with Alexandra Nawrat of UNLEASH to outline how the shift to being a skills-first employer is enabling business outcomes at the bank. (2) The Conference Board provides a compelling case study of Ericsson’s journey to becoming a skills-based organisation, which has seen skills become the language of the employee experience at the company (see FIG 13) – authors: Allan Schweyer Barbara Lombardo Matt Rosenbaum and Peter Sheppard. (3) Josh Bersin takes his cue from the latest round of investment in TechWolf plus the acquisition of SkyHive by Cornerstone by Cornerstone OnDemand to provide an overview of the burgeoning skills technology market as it moves from ‘pioneer stage’ to ‘early maturity’ (see FIG 14). (4) Marc Effron details 17 considerations for companies seeking to embark on the journey to becoming a skills-based organisation. (5) The Deloitte team of Susan Cantrell Michael Griffiths Robin Jones and Julie Hiipakka present their seminal operating model for a skills-based organisation (see FIG 15).
FIG 13: Skills are the language of the employee experience at Ericsson (Source: Ericsson)
FIG 14: Source – Josh Bersin
FIG 15: The skills-based organization: A new model for work and workforce (Source: Deloitte)
EMPLOYEE LISTENING, EMPLOYEE EXPERIENCE, AND EMPLOYEE WELLBEING
DERRICK P. BRANSBY, MICHAELA J. KERRISSEY, AND AMY C. EDMONDSON - New Hires’ Psychological Safety Erodes Quickly
Psychological safety is not the default in any workplace, and those who need it most — newcomers — are also most vulnerable to losing it.
Research finds that psychological safety is especially important for new hires as it enables them to overcome the challenge of admitting fallibility, tackle a steep learning curve and embrace new perspectives. So, it is concerning that in their new study, Amy Edmondson Derrick Bransby and Michaela Kerrissey identify a fascinating pattern: On average, newcomers joined their organisation with higher psychological safety relative to their more tenured colleagues, then lost it and waited years to reach levels comparable to when they arrived. Nevertheless, the study also found that departments with high psychological safety among colleagues help reduce that decline and facilitate quick recovery for new hires (see FIG 16). The article also discusses why newcomers are vulnerable to losing psychological safety and presents strategies to help preserve their early willingness to speak up.
FIG 16: Contrast between employees in departments with high and low psychological safety (Source: Bransby et al)
CHRISTINA BRADLEY, LINDY GREER, AND JEFFREY SANCHEZ-BURKS - When Your Employee Feels Angry, Sad, or Dejected
Leaders must be able to respond in a supportive manner to the emotions of their employees. That requires them to learn how to handle others’ feelings in different contexts, be more aware of their own behavior, and hone their skills. If they can master those three things, the result will be a healthier, more successful organization.
In their article for Harvard Business Review, three researchers from Michigan’s Ross School of Business provide a roadmap to leaders for providing employees with emotional support. As Christina Bradley Lindy Greer and Jeffrey Sanchez-Burks outline, the right response depends heavily on context, in particular, whether someone (1) is working on a time‑sensitive goal and (2) seems to be coping (see FIG 17).
FIG 17: Figuring out how to respond to an employee’s emotions (Source: Bradley et al)
LEADERSHIP AND CULTURE
MICHAEL ARENA, ANDRAS VICSEK, JOHN GOLDEN, AND SCOTT HINES – Cultivating Culture in a Hybrid Context
Because connections are more fragile in hybrid workplaces, it is increasingly important that managers understand the network dynamics of company culture.
Many companies are concerned about the impact of remote and hybrid work on their culture. In their article, Michael Arena Andras Vicsek John Golden, Ph.D. and Scott Hines, PhD, explore how cultural behaviours form and spread across organisations in three work modes: a physical environment, a remote environment, and a hybrid model. They find that prominent cultural behaviours tend to cluster in discernible patterns in each of these modes. The article discusses ways – and provides examples – on how to restore bridges between teams, harness influencers to facilitate change, engage exemplars to model desired behaviours, and reengage the hearts and minds of employees, to improve collaboration, wellbeing and outcomes. One example in the article describes how a large consumer products company launched a series of in-person events to restore bridging connections between their teams in parallel with a reengagement strategy to rebuild their employees’ sense of owning the company’s purpose. This enabled the company to increase connections by 37 percent and positive energy by 20 percent.
FIG 18: Shift of Positive Energy across Work Modes (Source: Arena et al)
DANIEL STILLMAN - The Four Quadrants of Employee Performance
In his essay, Daniel Stillman distils Shake Shack head honcho Danny Meyer’s Four Quadrants of Employee Performance to help explain how to harness the hiring, retention and development of talent to scale company culture intentionally. The four quadrants (see FIG 19) are: (1) Can and Will (“water these flowers”). (2) Can’t and Will (“coach them”). (3) Can’t and Won’t (“put the candle underneath their rear end”). (4) Can and Won’t (“The hardest one…”). For more from Danny Meyer, I recommend watching him in conversation with Adam Grant at the recent Wharton People Analytics Conference, where they discussed: The Hidden Potential of Frontline Workers.
FIG 19: The Four Quadrants of Employee Performance (Adapted by Daniel Stillman from Danny Meyer)
DIVERSITY, EQUITY, INCLUSION, AND BELONGING
ROUVEN KANITZ, MAX REINWALD, KATERINA GONZALEZ, ANNE BURMEISTER, YIFAN SONG, AND MARTIN HOEGL - 4 Ways Employees Respond to DEI Initiatives
In their article for Harvard Business Review, Rouven Kanitz Max Reinwald Katerina Gonzalez Anne Burmeister Yifan Song and Prof. Dr. Martin Hoegl present their research, which finds that employees respond to DEI initiatives in four ways (see FIG 20): excited supporters, calm compliers, torn shapers, and discontented opponents. The article outlines each of the four profiles, and provides guidance to managers on how they can use the typology to segment their employees, effectively understand the range of responses, and tailor specific interventions to address them.
FIG 20: The 4 Ways Employees Respond to DEI Initiatives (Source: Kanitz et al)
HR TECH VOICES
Much of the innovation in the field continues to be driven by the vendor community, and I’ve picked out a few resources from July that I recommend readers delve into:
RYAN WONG - With AI, HR Faces A Choice: Get Onboard Or Risk Getting Left Behind – Ryan Wong, CEO of Visier Inc., provides a compelling set of reasons why HR needs to embrace AI: (1) It helps source talent, faster. (2) It frees up HR to focus on strategic HR. (3) It unlocks people insights that drive the business.
BEN WIGERT - The Strengths, Weaknesses and Blind Spots of Managers – Ben Wigert, Ph.D, MBA unveils the findings of a Gallup study to compare how managers think they are currently leading their team versus how employees say they are being managed (see FIG 21). Thanks to Hung Lee for highlighting in his Recruiting Brainfood newsletter.
FIG 21: Current State of Management: Employee vs. Manager Perspectives (Source: Gallup)
FRANCISCO MARIN - Unlocking the Power of Centrality Metrics in Organizational Network Analysis – Francisco Marin of Cognitive Talent Solutions breaks down centrality metrics, and how they can be leveraged to make ONA more actionable and impactful.
CULTURE AMP - HR’s complete performance management guide – A hugely comprehensive Culture Amp guide on the what, the why, and the how of performance management. Thanks to Jodie Evans for highlighting.
FIG 22: The building blocks of performance management (Source: Culture Amp)
JOSEPH IFIEGBU - How do you ensure ethical practices in the implementation of People Analytics in your organization? – An insightful post – and meme (see FIG 23) – by Joseph Ifiegbu, CEO at eqtble, on people analytics, trust and ethics.
FIG 23: Source – Joseph Ifiegbu
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):
DAVE ULRICH, BOB EICHINGER, AND ALLAN CHURCH – The Science of Talent Management – In an episode of the Future of HR podcast, Dave Ulrich, Bob Eichinger and Allan Church, Ph.D. join host JP Elliott, PhD to discuss the ‘knowing-doing’ gap in talent management, and why skills-based organisations are an incomplete method of talent management.
AARON DE SMET AND BROOKE WEDDLE - Gen AI talent: Your next flight risk - On an episode of The McKinsey Podcast, Aaron De Smet and Brooke Weddle talk to Lucia Rahilly about what workers who regularly use GenAI want most, as well as practical steps leaders can take now to keep them happy and engaged.
KIM SCOTT - Radical Respect in Polarized Times: Strategies for Leaders – Kim Scott, author of Radical Candor joins Lars Schmidt in an episode of Redefining Work to discuss the workplace application of ‘Radical Candor’, and the genesis of her latest work and book – Radical Respect, intended as a precursor to her initial book.
BRADFORD WILLIAMS - How People Analytics Can Transform or Destroy Your Workplace - Bradford Williams, Head of People Analytics at Northwestern Mutual, joins Christopher Rainey on the HR Leaders podcast to explore the pivotal role of managers in shaping culture, the impact of technology on HR, the significance of strong organisational networks, and the role of people analytics in enhancing business outcomes.
RICHARD ROSENOW - People Data Supply Chain, One Model, and The Power of No – Richard Rosenow joins hosts Cole Napper and Scott Hines, PhD on Directionally Correct to discuss the people data supply chain and its impact on people analytics.
VIDEO OF THE MONTH
TIM PEFFERS – How to measure productivity
For those of you who haven’t consumed Random Walks in HR, along with Heather Whiteman, Ph.D., Tim Peffers produces the best video blogs in the people analytics field. In this video, Tim builds on his premise that “people analytics will never deliver on its promise without being able to measure individual productivity”, by presenting his proposal to develop a new metric – Productivity Against Replacement (PAR), which as Tim explains is inspired by Bill James’ WAR (Wins Above Replacement) metric.
BOOK OF THE MONTH
MARTIN R. EDWARDS, KIRSTEN EDWARDS, AND DAISUNG JANG – Predictive HR Analytics: Mastering the HR Metric
Having a third edition of a book published is an impressive achievement – and testament to the quality of material. In this third edition of Predictive HR Analytics, Martin Edwards, Kirsten Edwards, and Daisung Jang provide a clear, practical and accessible framework for understanding people data, flourishing with people analytics, and using advanced statistical techniques. Predictive HR Analytics has been adopted by more than 20 universities across the world as a core or recommended text in HR and business analytics courses, and it’s clear to see why.
FROM MY DESK
July saw the first four episodes of series 40 of the Digital HR Leaders podcast, which is kindly being sponsored by our friends at HiBob – thanks to Louis Gordon. Additionally, July also saw the publication of a new article in Workday’s Smart CHRO magazine.
PATRICK EVENDEN - How people data empowers today’s CHRO – Writing for Workday’s Smart CHRO magazine, Patrick Evenden draws on my presentation from Workday Rising, where I discussed the need for CHROs to leverage people data and bolster their HR teams’ data literacy. Thanks to Sophie Barnes.
JOHN WINSOR - Addressing the Global Skills Shortage with Open Talent Strategies – John Winsor, co-author of Open Talent and Chairman of Open Assembly, joined me to discuss the three-legged stool ‘Open Talent’ framework: internal talent marketplaces, external talent clouds, and open innovation.
MAUREEN DUNNE - HR Strategies for Embracing Neurodiverse Talent – Maureen N. Dunne, Ph.D., author of The Neurodiveristy Edge, discusses why prioritising a neurodivergent culture is essential amidst the acceleration of digital transformation.
NIRIT PELED-MUNTZ - Evolving Culture & Employee Experience in Fast-Growth Companies – HiBob’s Chief People Officer, Nirit Peled-Muntz, joins me to share HiBob’s remarkable growth journey, explaining how the culture has evolved, how the North Star of world-class employee experience has been maintained, and how the HR team has played a pivotal role in the development of HiBob’s technology platform.
HEIDI MANNA - How to Create a Flexible Work Model That Enhances Inclusion and Employee Experience – Heidi Manna, Chief People Officer at Jazz Pharmaceuticals, joins me to share details about the company’s Flexible Work Model. She discusses why the company shifted to a flexible work model and the improvements seen as a result in hiring, employee experience and inclusion.
We have a pretty strong belief that a flexible work model benefits the business and our ability to serve our patients, and it allows employees to have a better work-life integration experience as well.
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 now numbers over 500 roles – and has now been developed into a LinkedIn newsletter too
THANK YOU
Olimpiusz Papiez for explaining how we can optimise our organisation's structure for greater efficiency, which was inspired by my conversation with Armand Sohet on the Digital HR Leaders podcast episode: Painting the Future of HR with AI, Analytics and Curiosity.
Huma HR for including the Digital HR Leaders podcast in their list of 10 HR Podcasts for the Summer, which also included podcasts hosted by Laurie Ruettimann, Damon Klotz and Lucy Adams.
Thomas Kohler for including the June edition of Data Driven HR Monthly in his round-up of resources for HR professionals.
Alejandra Barbarelli for recommending the June edition of Data Driven HR Monthly, and for her kind words about my content curation.
Judy Albers for summarising some of the highlights from the June edition of Data Driven HR Monthly.
Veronika Birkheim, whose post: “People analytics must be easy to use…” was inspired by the Digital HR Leaders podcast episode with Dirk Jonker: Driving Business Transformation with Advanced People Analytics
K Nair for including me in his list of 11 Influential HR Leaders, which included others that inspire me including: Laszlo Bock, Adam Grant and Josh Bersin.
Thinkers360 for including the Digital HR Leaders podcast in their List of Top Podcasts.
Anastasia Mizitova, SHRM-SCP, CPCC for her post sharing a resource from a special edition of the Insight222 Digital HR Leader newsletter: Essential Summer Reads.
Finally, a huge thank you to the following people who shared the June edition of Data Driven HR Monthly. It's much appreciated: David Balls (FCIPD) Mukesh Jain Amardeep Singh, MBA Phil Inskip Kalifa Oliver, Ph.D. Jacqui Brassey, PhD, MA, MAfN (née Schouten) Sophie Merckelbach Alison Doyle Gord Johnston MA, BHJ, BA, CHRP Asanka Gunasekara (PhD) Jayashree Shivkumar Andrews Cobbinah, MLPI, ACIHRM Henrik Håkansson Irakli Dadiani Jaqueline Oliveira-Cella Tamano Yamanaka Shay David Erin Fleming Louise Baird Bilal Laouah Jeff Wellstead Aravind Warrier Greg Newman Terri Horton, EdD, MBA, MA, SHRM-CP, PHR Susan Knolla Danielle Farrell, M.A. Alison Ettridge Adam Tombor (Wojciechowski) Roshaunda Green, MBA, CDSP, Phenom Certified Recruiter Karla Chavez Gomez Jay Polaki⚡️ SHRM-SCP/SPHR Dan Riley Emily Killham Rashleen Kaur Arora Kouros Behzad Nick Jesteadt Ken Oehler Juan Ignacio Perez Collado Jose Luis Chavez Vasquez Deviprasad Panda Swechha Mohapatra (IHRP-SP, SHRM-SCP, CIPD) Catriona Lindsay Debbie Harrison Neeru Monga Aurélie Crégut Faiza Tasneem(Associate CIPD) David Hodges Irada Sadykhova Yukiko Hosomi? David McLean Andrii Suslenko Gary Parilis Maria Alice Jovinski Erik Samdahl Tristan Hack Adam McKinnon, PhD. Kerrian Soong Dr. Peter Schulz-Rittich Timo Tischer Martijn Wiertz Shuba Gopal Martha Curioni Tobias W. Goers ツ Galo Lopez Noriega Patrick Coolen Brian Heger Hanadi El Sayyed Marcela Niemeyer Alicia Roach Dawn Klinghoffer Heather Muir Selina Millstam Dave Millner Dan George Nick Lynn Marc Voi Chiuli. (MSc. HRM. Assoc CIPD. MIHRM.) Ankit Saxena, MBA Volker Jacobs David Simmonds FCIPD Amit Mohindra Andrew Pitts Burak Bakkaloglu Malgorzata Langlois Isabel Naidoo David van Lochem Diane Gherson Marino Mugayar-Baldocchi Neha Asthana Irene Wong Jaejin Lee Anna A. Tavis, PhD Doug Shagam Geetanjali Gamel Matt Elk Tina Peeters, PhD Barry Swales Bob Pulver David Duewel Matt Higgs MBA FCIPD Meghan M. Biro Sebastian Knepper Kathleen Kruse Dorothy Dalton Kate Graham Laura Thurston Søren Kold Jacob Nielsen Ralf Buechsenschuss Nicole Hazard Tatu Westling Sue Lam Chris Lovato Joseph Frank, PhD CCP GWCCM Tom Morehead PCC,MBA,SPHR Ian OKeefe Lina Makneviciute RJ Milnor Nicole Lettich Mariana Saintive Sousa Jon Kirchhoff Roberto Amatucci Christopher Rosett Rebecca Thielen Morten Hartvig Berg John Gunawan Soumya Bonantaya MBA MS SWP Ronald Schep Daorong Lin Abhilash Bodanapu Morgan Baldwin Jack Liu Sanja Licina, Ph.D. Piyush Mehta Sebastian Kolberg Jaap Veldkamp Craig Starbuck, PhD Sukumaran Mariappan Felipe Jara Michal Gradshtein Dave Fineman Stephen Hickey Gal Mozes, PhD Agnes Garaba Emily Pelosi, PhD Kelly Satterfield Laurent Reich Brandon Roberts Lewis Garrad Danielle Bushen Nick Hudgell Andrew Kilshaw Higor Gomes Pietro Mazzoleni Marcela Mury Giovanna Constant Mia Norgren Ohad Geron
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 90 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 2024:
September 11 - Productivity, Purpose, and Profit: How to thrive in ‘25 (London)
September 16-19 - Workday Rising (Las Vegas)
September 24-26 - Insight222 Global Executive Retreat (Colorado, US) - exclusively for member organisations of the Insight222 People Analytics Program
October 2-3 - People Analytics World (New York)
October 16-17 - UNLEASH World (Paris)
October 22-23 - Insight222 North American Peer Meeting (hosted by Workday in Pleasanton, CA) - exclusively for member organisations of the Insight222 People Analytics Program
November 12-14 - Workday Rising EMEA (London)
November 19-20 - Insight222 European Peer Meeting (hosted by Merck in Darmstadt, Germany) - exclusively for member organisations of the Insight222 People Analytics Program
More events will be added as they are confirmed.
AI
2024年08月02日
AI
The Key to a Thriving Workforce? A Smart Approach to AI微软的最新数据强调了人工智能对员工赋权、活力和生产力的积极影响。领导者可以通过关注其员工队伍是否在“繁荣”中来促进良好表现，微软将“繁荣”定义为被赋予权力和充满活力地进行有意义的工作。员工信号调查显示，人工智能的使用能通过减少乏味工作并促进有意义的工作来提高生产力、努力和影响。人工智能工具还与更高的赋权和活力得分相关，表明员工队伍的“繁荣”。成功的关键在于将人工智能与支持性文化相结合，提供必要的培训，并使人工智能项目与公司目标保持一致。
New data reveals how access to AI can help employees feel more empowered and energized, and find more meaning in their work.
what’s the best way for leaders to foster good performance? How can they tell if their efforts are successful or not? Often, companies try to answer these questions by measuring metrics like engagement or financial results. And while those are critical to business success, at Microsoft, we also want to explore whether the workforce is thriving.
“Thriving has become the North Star for how we understand employees,” says Microsoft VP of People Analytics Dawn Klinghoffer, who leverages data to help leaders understand and improve employee’s experience. “We define thriving as being empowered and energized to do meaningful work. Are people excited to come to work every day, excited about the opportunities ahead?”
One of the ways we gauge this at Microsoft is with our Employee Signals survey, a biannual company-wide poll. The recent results not only offered insights into the tangible benefits of thriving, they also uncovered a key catalyst for fostering it: access to AI.
The Benefits of Thriving
We are focused on fostering a culture of thriving because our research suggests that doing so can boost how effective our workforce perceives itself to be. We also found that employees who are thriving are likely to have the highest scores on our indicators of high performance, like productivity, effort, and impact
Additionally, survey results suggest that employees who are thriving are more likely to go above and beyond what is expected of them. They take more pride in their work and they are less apt to look for employment elsewhere.
Recent Employee Signals survey results give us some new insights about what it means to thrive in this new era of work. We discovered that higher scores on what we’ve identified as the most important factors that support thriving—finding meaning in work, feeling empowered, and feeling energized—also translate to a measurable boost in productivity. Furthermore, access to AI seems to correlate with higher scores on each of these pillars.
Meaningfulness: According to our data, employees who find their work meaningful are 59% more likely to say they are productive at work—and 28% more likely to say they put in extra effort. Key to that is minimizing time spent on tasks that don’t feel meaningful. This is where AI comes in: AI assistants can lighten the load by generating rough drafts, sifting through piles of data, or simply acting as a sounding board and brainstorming partner to help people nail down a plan of action. Crucially, incorporating AI into the day correlated to a 20% jump in scores relating to meaningful work.
“What we find is that AI is really there to help you take friction and toil out of the system, and to remove the drudgery of work,” Klinghoffer says. “And when people are able to remove some of that drudgery, we see that they’re more productive, and they thrive more.”
Empowerment: Survey results also point to a future in which AI empowers people in their jobs. People who are empowered do not feel they have resource constraints, and they aren’t overburdened with people telling them how to do their work, Klinghoffer says, “so they have more freedom to do things the way they want and need to get the job done.” Access to AI tools and resources, we found, correlated to 34% higher scores for questions related to empowerment.
Energy: Our employees who say they feel energized are 44% more likely to say they feel proud of their work, and 22% more likely to say they take the initiative to be productive and put discretionary effort into their work. All levels of AI use— learning about it, grasping its value, incorporating it into processes and products, or simply having AI resources—correlated to higher reported energy levels. In fact, scores on energy-related questions for those using AI jumped almost 27%.
These results offer solid evidence that AI can be a catalyst for thriving and high performance. But how a company goes about making AI available will determine whether the company can reap these benefits. If employees are equipped with the right knowledge, tools, training, and resources to leverage AI in their work, they can begin to tap the full potential of an AI companion.
The key to success, Klinghoffer says, is integrating AI in a way that spans culture, learning, and people management. That way, everyone will understand how AI can help them focus on the most meaningful work.
The ABCs of Thriving with AI
Klinghoffer recommends keeping the following blueprint top of mind.
Accelerate alignment: Strengthen connections between employees, the company’s mission, and the transformative potential of AI. Clarify how AI initiatives align with the company’s goals and employees’ roles. Celebrate contributions to AI projects to highlight their impact on the company and customers.
“Employees who felt more connected to the mission and really understood how their work fits into the larger system were also the ones who were really thriving,” says Ketaki Sodhi, Senior HR Data Analyst at Microsoft. “When we looked at Copilot and employee sentiment around AI, these were also the folks who were willing to experiment and find ways to use AI to take some of the drudgery out of the day-to-day.” Smart leaders should seek out those internal champions and offer them support and encouragement.
Be inclusive: Create an environment where all employees feel equipped to engage with AI. This includes providing AI education, training, and resources, as well as fostering a culture of innovation and supporting a safe space for experimentation. Regular check-ins and feedback sessions can help employees express concerns and share ideas related to AI. Once users are encouraged and equipped to explore the possibilities of AI, our research suggests that a time savings of just 11 minutes a day is all it takes for them to start to appreciate its value.
Cultivate collective growth: Create a culture that empowers employees to decide how to do their best work, while investing in moments that matter together. Provide employees with the flexibility to plan their days and create time to meaningfully engage with AI. Encourage them to explore how AI can help them free up time for creative and strategic work. Then highlight use cases and foster collaboration among teams to encourage knowledge sharing.
Collective growth encompasses in-role experiences (how do we create time and space for employees to learn within their role?) and beyond (what comes next for me? Is there a viable career that excites me at this company?). AI can help with both—by eliminating the drudgery that keeps employees from doing more creative work, and by facilitating positive employee movement. “You see a huge boost. People get excited doing something new, growing their skills and experiences, and furthering their career,” Klinghoffer says. “A couple of months ago on my team we had people who were interested in a different role raise their hands, and we facilitated changes for about 20% of my org.”
美国劳工部发布职场人工智能使用原则，保护员工权益（附录原文）
今天5月16日，美国劳工部发布了一套针对人工智能（AI）在职场使用的原则，旨在为雇主提供指导，确保人工智能技术的开发和使用以员工为核心，提升所有员工的工作质量和生活质量。代理劳工部长朱莉·苏在声明中指出：“员工必须是我们国家AI技术发展和使用方法的核心。这些原则反映了拜登-哈里斯政府的信念，人工智能不仅要遵守现有法律，还要提升所有员工的工作和生活质量。”
根据劳工部发布的内容，这些AI原则包括：
以员工赋权为中心：员工及其代表，特别是来自弱势群体的代表，应被告知并有真正的发言权参与AI系统的设计、开发、测试、培训、使用和监督。这确保了AI技术在整个生命周期中考虑到员工的需求和反馈。
道德开发AI：AI系统应以保护员工为目标设计、开发和培训。这意味着在开发AI时，需要优先考虑员工的安全、健康和福祉，防止技术对员工造成不利影响。
建立AI治理和人工监督：组织应有明确的治理体系、程序、人工监督和评估流程，确保AI系统在职场中的使用符合伦理规范，并有适当的监督机制来防止误用。
确保AI使用的透明度：雇主应对员工和求职者透明地展示其使用的AI系统。这包括向员工说明AI系统的功能、目的以及其在工作中的具体应用，增强员工的信任感。
保护劳动和就业权利：AI系统不应违反或破坏员工的组织权、健康和安全权、工资和工时权以及反歧视和反报复保护。这确保了员工在AI技术的应用下，其基本劳动权益不受侵害。
使用AI来支持员工：AI系统应协助、补充和支持员工，并改善工作质量。这意味着AI应被用来提升员工的工作效率和舒适度，而不是取代员工或增加其工作负担。
支持受AI影响的员工：雇主应在与AI相关的工作转换期间支持或提升员工的技能。这包括提供培训和职业发展机会，帮助员工适应新的工作环境和技术要求。
确保负责任地使用员工数据：AI系统收集、使用或创建的员工数据应限于合法商业目的，并被负责地保护和处理。这确保了员工数据的隐私和安全，防止数据滥用。
这些原则是根据拜登总统发布的《安全、可靠和可信赖的人工智能开发和使用行政命令》制定的，旨在为开发者和雇主提供路线图，确保员工在AI技术带来的新机遇中受益，同时避免潜在的危害。
拜登政府强调，这些原则不仅适用于特定行业，而是应在各个领域广泛应用。原则不是详尽的列表，而是一个指导框架，供企业根据自身情况进行定制，并在员工参与下实施最佳实践。通过这种方式，拜登政府希望能在确保AI技术推动创新和机会的同时，保护员工的权益，避免技术可能带来的负面影响。
这套原则发布后，您认为它会对贵公司的AI技术使用和员工权益保护产生怎样的影响？
英文如下：
Department of Labor's Artificial Intelligence and Worker Well-being: Principles for Developers and Employers
Since taking office, President Biden, Vice President Harris, and the entire Biden-Harris Administration have moved with urgency to harness AI's potential to spur innovation, advance opportunity, and transform the nature of many jobs and industries, while also protecting workers from the risk that they might not share in these gains. As part of this commitment, the AI Executive Order directed the Department of Labor to create Principles for Developers and Employers when using AI in the workplace. These Principles will create a roadmap for developers and employers on how to harness AI technologies for their businesses while ensuring workers benefit from new opportunities created by AI and are protected from its potential harms.
The precise scope and nature of how AI will change the workplace remains uncertain. AI can positively augment work by replacing and automating repetitive tasks or assisting with routine decisions, which may reduce the burden on workers and allow them to better perform other responsibilities. Consequently, the introduction of AI-augmented work will create demand for workers to gain new skills and training to learn how to use AI in their day-to-day work. AI will also continue creating new jobs, including those focused on the development, deployment, and human oversight of AI. But AI-augmented work also poses risks if workers no longer have autonomy and direction over their work or their job quality declines. The risks of AI for workers are greater if it undermines workers' rights, embeds bias and discrimination in decision-making processes, or makes consequential workplace decisions without transparency, human oversight and review. There are also risks that workers will be displaced entirely from their jobs by AI.
In recent years, unions and employers have come together to collectively bargain new agreements setting sensible, worker-protective guardrails around the use of AI and automated systems in the workplace. In order to provide AI developers and employers across the country with a shared set of guidelines, the Department of Labor developed "Artificial Intelligence and Worker Well-being: Principles for Developers and Employers" as directed by President Biden's Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, with input from workers, unions, researchers, academics, employers, and developers, among others, and through public listening sessions.
APPLYING THE PRINCIPLES
The following Principles apply to the development and deployment of AI systems in the workplace, and should be considered during the whole lifecycle of AI – from design to development, testing, training, deployment and use, oversight, and auditing. The Principles are applicable to all sectors and intended to be mutually reinforcing, though not all Principles will apply to the same extent in every industry or workplace. The Principles are not intended to be an exhaustive list but instead a guiding framework for businesses. AI developers and employers should review and customize the best practices based on their own context and with input from workers.
The Department's AI Principles for Developers and Employers include:
[North Star] Centering Worker Empowerment: Workers and their representatives, especially those from underserved communities, should be informed of and have genuine input in the design, development, testing, training, use, and oversight of AI systems for use in the workplace.
Ethically Developing AI: AI systems should be designed, developed, and trained in a way that protects workers.
Establishing AI Governance and Human Oversight: Organizations should have clear governance systems, procedures, human oversight, and evaluation processes for AI systems for use in the workplace.
Ensuring Transparency in AI Use: Employers should be transparent with workers and job seekers about the AI systems that are being used in the workplace.
Protecting Labor and Employment Rights: AI systems should not violate or undermine workers' right to organize, health and safety rights, wage and hour rights, and anti-discrimination and anti-retaliation protections.
Using AI to Enable Workers: AI systems should assist, complement, and enable workers, and improve job quality.
Supporting Workers Impacted by AI: Employers should support or upskill workers during job transitions related to AI.
Ensuring Responsible Use of Worker Data: Workers' data collected, used, or created by AI systems should be limited in scope and location, used only to support legitimate business aims, and protected and handled responsibly.
AI
2024年05月16日
AI
BetterUp Manage: Pioneering AI-Powered Platform For Leaders
BetterUp公司最近在其Uplift大会上推出了一个名为BetterUp Manage的领导力发展平台，这一平台采用人工智能驱动的评估和个性化学习方案，彻底改变了专业发展的途径。该平台具有高度的可扩展性和可定制性，能够与Workday、Oracle和SAP等主要系统无缝连接。BetterUp Manage不仅为领导者提供服务，也支持任何寻求发展专业能力的个人。通过整合最新的人工智能技术，BetterUp Manage为传统的领导力培训行业带来了革命性的变革。
这次大会中，BetterUp还邀请了英国的哈里王子Prince Harry, Duke of Sussex 和亚当·格兰特，哈里王子是BetterUp的首席影响官。。。
This week I attended the BetterUp Uplift conference and I really was impressed. This is a company that exploded into the market with an innovative coaching and employee wellbeing network built around an assessment called the “whole person model.” Through a set of shrewd marketing and sales strategies BetterUp established a leadership position in this market, growing to a billion dollar+ valuation.
This success encouraged many competitors to form and now the market for AI-enabled, targeted coaching is large and crowded (vendors include Torch, CoachHub, Growthspace, Sounding Board, Bravely, and a new breed of AI systems).
Essentially what BetterUp did was democratize business and professional coaching. Before this trend coaching was a rarified, expensive offering reserved for under-performing leaders or high-potential executives. Today, with BetterUp, anyone can go through a meaningful assessment, get assigned a relevant coach, and start a coaching session in minutes. The system is well designed and easy to use and BetterUp’s coaches are all trained (most of the coaching vendors use a lot of the same certified coaches – they are not BetterUp employees).
As a corporate solution, BetterUp goes much further. The data collected through assessments is available for analysis (anonymized) so companies can find pockets of stress in the organization. You can look at assessments by team (minimum of 10 people), tenure, level, and other factors. This lets companies like Chevron or Cisco understand the issues new employees or new managers have, for example.
In the last few years the company moved into wellbeing by offering a solution called BetterUp Care, which targets benefits buyers. But the more strategic and interesting offering is the new platform I saw this week, now named BetterUp Manage (it was originally called Connect).
BetterUp Manage is the first highly personalized, scalable management development platform I’ve seen. It brings together AI-enabled assessment, personalized learning, coaching, and AI-driven narrative support. It’s quite an impressive product, much of it was developed by the team at Motive, who was acquired by BetterUp in 2021.
BetterUp Manage is an out of the box personalized leadership development solution. And you don’t need to be a “leader” to use it. The system steps you through the Whole Person assessment, then asks you questions about the types of soft-skills issues you face (many specific scenarios), and then gives you a customized learning path, week by week, along with a professional coach.
Since it’s built on an AI platform there is very little manual work behind the scenes so it’s enormously scalable. Large companies will want to customize it and BetterUp is prepared for some of these requests. And the system connects to Workday, Oracle, SAP to automatically understand your role and level.
The reason I’m so excited is this: the management training industry is a confusing, messy, red ocean. There are thousands of consultants, coaches, books, courses, and executive education programs. L&D executives have to constantly build custom solutions, evaluate vendors, and hope that an offering will stick. This pure complexity, coupled with the fact that every company is unique, has led to many specialized leadership development firms (and some big ones like Franklin Covey).
So what most companies do is mix, match, and custom-build leadership solutions. And they’re not simple: we developed a model we call the 4-E’s to understand this: Education (courses), Experience (developmental assignments), Exposure (mentoring and coaching from leaders), and Environment (a company-wide focus on leadership values and behaviors). All these elements play a role in developing leadership skills.
Companies like IBM, Cisco, and Marriot can afford to custom build these solutions, but many companies don’t have the focus. BetterUp Manage is a way to personalize, scale, and democratize this solution and leverage the increasingly important role of AI.
I met Alexi Robichaux almost a decade ago and his passion and energy still drives the company. While BetterUp is a bigger company going through the growing pains of any $billion valued growth business, the culture and passion for clients is clear.
Remember that buying L&D solutions is not as simple as buying a product and turning it on. Every training solution, platform, or program you buy must be carefully aligned with your company’s culture and rolled out with care. Otherwise people simply say “another training program from corporate I can ignore.”
BetterUp, for all its startup-like innovations, has overcome this problem. Customers value the system, they get strong adoption from employees, and the company works hard to advise and consult.
It has always been interesting to me that very few content companies ever become very big (Skillsoft is the only one that never seems to stop). And the reason for this is simply the nichey, highly diversified needs of many industries and companies. BetterUp, as a platform-centered company delivering a high-touch solution, has the potential to break this paradigm. It has enormous potential, given the rapid acceleration of AI behind the scenes.
I consider BetterUp one of the “Trailblazers” I talk about with clients, and BetterUp Manage is definitely something to watch.
AI
2024年04月12日
AI
Top AI Tools In Recruiting for 2024
本文由本杰明-梅纳（Benjamin Mena）撰写，深入探讨了 2024 年人工智能（AI）对招聘工作的变革性影响。梅纳探讨了人工智能工具如何不仅简化招聘流程，而且使企业能够高效地获得顶尖人才。这篇文章重点介绍了 SeekOut、PeopleGPT 和 Metaview 等平台，展示了人工智能在自动化任务、提高候选人参与度以及提供无与伦比的人才库洞察力方面的作用。随着人工智能与招聘的融合，该行业将迎来一场革命，在人才招聘中优先考虑效率、包容性和战略决策。
本文中提到的AI招聘工具公司覆盖了从综合人才搜索和评估平台到特定招聘流程自动化工具的全方位解决方案。这些公司可以分为几个主要类别，具体如下：
综合人才搜索与评估平台：
SeekOut：利用先进的AI技术进行人才搜索和资质评估。
PeopleGPT：通过大数据和对话AI技术改善候选人匹配过程。
HireEZ：通过机器学习和大数据技术，快速定位合适的人才。
招聘流程自动化工具：
Metaview：自动化面试笔记记录，提高招聘效率。
Teamable：结合智能搜索、自动化排程和AI电话/邮件外联功能的全方位招聘平台。
Betterleap：基于AI学习的候选人偏好自动构建候选人名单。
特定功能解决方案提供商：
Cherrypicker AI：优化招聘营销活动，通过AI提高候选人参与度。
Paradox's Olivia：AI聊天助手，自动回答候选人问题和安排面试。
MoonHub：利用AI技术提供全面的人才搜索和评估解决方案。
Popp's AI Copilot：通过AI筛选和预定合格面试，提升招聘效率。
其他值得关注的AI招聘公司：
Fetcher
Leoforce
Humanly (humanly.io)
Paiger
Jobin.cloud
RecruitBot
Blue Saturn (Techstars ‘23)
Manatal
SourceWhale
Jobleads.io
Sendspark
Kwal
Visage.Jobs
Textio
HireVue
Honeit Talent Solutions
Gem
Parasale (YC W24)
Apriora
Carv Talent
Llama Wellfound
Eightfold
Hirize
Sense
RecruiterPM
Enboarder
Workable
Findem
这些公司代表了AI招聘技术的最前沿，通过创新的解决方案帮助企业改进招聘流程、提升人才获取的效率和质量。无论是综合性平台还是专注于特定环节的工具，它们都在推动着招聘领域的技术进步和效率革新。
全文如下，请查看：
In today's fast-paced business world, the race to attract and retain top talent has become fiercer than ever before. Companies across industries are locked in a perpetual battle to stand out from the crowd and capture the attention of the best and brightest candidates. Enter artificial intelligence (AI) – a game-changing technological force that is revolutionizing the way we approach the art of recruitment.
AI is no longer a futuristic concept; it's a present-day reality that is transforming virtually every aspect of the business landscape, including the realm of talent acquisition and recruiting even though the hype train is coming to an end. From automating tedious tasks to providing data-driven insights, AI tools are empowering recruiters to work smarter, not harder, and gain a competitive edge in the ever-evolving war for talent where recruiters will be able to do much more.
To top that off I see a future soon where internal recruiting teams will allocate about 25% of their headcount spend on AI Tools to that can help their current recruiters do more. I also see a future where small nimble recruitment agencies that are either solo or small teams will be able to run in circles around recruiting teams of 30 or more because of the use of AI.
As the host of The Elite Recruiter PodcastI have gotten a chance meet and see so many amazing companies and individuals in the space As we delve into the fast-moving world of AI in recruiting, we'll explore cutting-edge tools that are redefining the industry's boundaries. But we won't stop there; we'll also introduce you to influential thought leaders and experts who are shaping the discourse around this groundbreaking technology. Their insights and perspectives will equip you with the knowledge to leverage AI effectively and stay ahead of the curve.
Whether you're a seasoned recruiter seeking to optimize your processes or a business leader looking to attract top-tier talent, this comprehensive guide to AI in recruiting will provide you with the strategies, tools, and inspiration you need to thrive in the modern talent marketplace.
??? Sidenote: If you need help hiring? We can help! ???
I am going to break it down into companies that I currently use or have used recently and then other companies to watch.
Before we jump into that make sure to check out the The Elite Recruiter Podcast on Apple Podcast and Spotify and join The Elite Recruiter Community
AI Recruitment Companies that I currently use or have used recently.
Seekout
SeekOut is a leading recruiting technology company that leverages advanced artificial intelligence to streamline the candidate search and hiring process. The AI-powered platform scans vast talent pools and online profiles to identify qualified candidates that match an employer's specific needs. Using natural language processing, machine learning algorithms, and extensive data on millions of professionals, one of my favorite parts is the ability to try to figure out who has security clearances based on data they were able to find about the candidate. They have also increased their AI capabilities so you can now just ask Seekout a question and it will find candidates for you based on your question. (This new tool just launched and I love it)
Seekout's intelligent search engine can surface the most relevant and promising job seekers for any given role. This allows Seekout's clients, which include numerous Fortune 500 companies, to efficiently find and engage with the best-fit talent, reducing time-to-hire and improving the quality of their hires. Seekout's innovative use of AI has made it a disruptive force in the recruiting industry, helping organizations build high-performing teams through data-driven, tech-enabled talent acquisition. They have also updated their pricing plans for smaller companies and smaller recruiting agencies.
SeekOutis a member of the Responsible AI Institute.
They are worth checking out and I personally use them.
Check out the podcast interview with Edward Pedinifrom Seekout: Spotify and Apple Podcast
PeopleGPT
PeopleGPT by Juicebox (YC S22) is pioneering the use of large language models and other advanced AI technologies to transform the recruiting industry. Founded in 2022, this innovative startup has developed a powerful AI-driven platform that dramatically enhances the candidate search and hiring process for its client organizations. By ingesting and analyzing massive datasets on millions of professionals, PeopleGPT's conversational AI engine can engage in natural dialogues to uncover the most qualified and promising job seekers for any given role. Through intelligent semantic understanding, the system identifies hard and soft skills, experience, career goals and cultural fit - delivering a curated pool of top talent that perfectly aligns with an employer's needs. This level of sophisticated AI-powered candidate matching has allowed PeopleGPT's clients to make faster, more informed hiring decisions, leading to higher quality hires and stronger, more productive teams. As the recruiting landscape continues to evolve, PeopleGPT is at the forefront of harnessing transformative AI technologies to reshape the future of talent acquisition.
One of the new updates you can search for people using Funding, Revenue, and Investor Data to narrow down your search even more.
They are worth checking out and I personally use them.
Check out the interview with People GPT founder David Paffenholz.
Metaview
Recruiting conversations contain critical insights, but frantically capturing meeting and interview details can distract from building connections. Metaview offers a purpose-built AI solution tailored to talent acquisition that automates the notetaking process
It works by using speech and conversation models trained on recruiting lingo to listen in on interviews, meetings etc. The assistant takes structured notes in real-time, cataloguing relevant candidate attributes, key discussion points and action items.
These AI-generated notes are customized to the needs of hiring managers and talent teams for seamless sharing post-conversations. Recruiters can also enrich captured details with additional context from the ATS profile.
By eliminating the constant need for manual note documentation, Metaview allows talent professionals to be fully present. They can focus on assessing candidates and strategic hiring conversations without distraction.
The automated approach also saves ample time post-meetings that can get reallocated to higher-value work. Recruiters gain back hours each week while still benefiting from comprehensive, tailored meeting recaps.
As talent teams support growing hiring demands with constrained resources, solutions like Metaview will prove essential. Its AI recruiting assistant empowers the humans behind talent acquisition to nurture relationships and make smarter data-backed decisions.
They are worth checking out and I personally use them. Here is more info on them
Betterleap
Betterleap learns the type of candidate that you are sourcing for and then starts to develop a candidate list every day that you are able to reach out to.
To top that off one of the things that Betterleap does a bad job highlighting (but it’s a huge benefit for those recruiters that know). You can reach out to unlimited contacts each month.
Betterleap also surprised me when it came to recruiting Cleared and GovCon recruiting talent. It has a great database of and filters for clearance levels.
Anna Melano and Khaled Hussein have the potential to build one of the hottest recruiting startups in 2024.
They have recently updated their system with Natural Language Search. So you can ask it something like Find me Software Engineers that are close to Googles HQ. The software will know where the HQ of Google is and will start to build out a list of candidates close to that location.
Here is an interview with Betterleap founder Khaled Hussein as we talk about the 3 evolutions of AI in recruiting.
Other AI Recruiting Companies that you should check out!
HireEZ
hireEZ has emerged as a frontrunner in the AI recruiting space, offering a comprehensive solution that harnesses the power of big data and machine learning to revolutionize the talent acquisition process. By tapping into a vast pool of over 800 million candidate profiles and leveraging intelligent algorithms, HireEZ empowers recruiters to uncover the most qualified and relevant talent for their specific needs. Gone are the days of sifting through endless resumes - this AI-driven platform does the heavy lifting, delivering a curated shortlist of candidates who possess the perfect blend of skills, experience, and cultural fit.
But HireEZ's innovation doesn't stop there. The platform's AI-powered automation capabilities tackle the time-consuming administrative tasks that often bog down recruiters, from scheduling interviews to managing candidate communication. This frees up valuable time and resources, allowing recruiting teams to focus on what they do best: building meaningful relationships with top-tier candidates. Notably, HireEZ's commitment to diversity and inclusion is woven into the core of its technology, with the platform's AI configured to prioritize candidates from underrepresented groups, helping organizations build a more diverse talent pipeline and combat unconscious bias in the hiring process.
HireEZ's AI Values system is built on the following principles: Fair, Accountable, Transparent, Inclusive, Explainable, and Privacy, Security and Safety. The company strives to mitigate AI bias risks, ensure continuous improvements to their product and technology, and provide users with control and transparency throughout the decision-making process. As the recruiting landscape continues to evolve, forward-thinking companies would be wise to explore AI-powered solutions like HireEZ. By harnessing the power of data and automation, recruiters can elevate their game, make more informed decisions, and ultimately, deliver the best-fit talent to drive their organization's success. The future of talent acquisition is here, and HireEZ is leading the charge. It will be fun to see what Daniel Harten and Shannon Pritchett have up their sleeve next.
Teamable: AI-Powered Recruiting Automation
Teamableoffers an all-in-one talent acquisition platform combining intelligent sourcing, automated scheduling, and AI phone/email outreach. This end-to-end recruiting software solution helps organizations scale efforts and engage more candidates.
At its core is an AI Assistant that understands role requirements and proactively sources qualified, diverse candidates from both public and private talent pools. Instead of sifting databases, the Smart Search functionality finds ideal talent matches.
Teamable also automatically coordinates complex interview scheduling amongst hiring managers and candidates. By managing the frustrating back-and-forth, it accelerates process timelines. It's AI will even handle email and text outreach to talent, freeing up recruiter time.
The unified platform centralizes all candidate information and interactions for a complete view enabling data-driven decisions. Built-in analytics track KPIs like source of hire to optimize the funnel.
As recruiting needs grow more complex amid intensifying competition for talent, consolidating tech stacks is key. Teamable offers an integrated solution encompassing intelligent sourcing, scheduling, and outreach. With automation powering high-volume tasks, recruiters can focus on building candidate relationships.
That's why forward-looking organizations will turn to all-in-one solutions like Teamable to drive efficiencies and results in 2024. It's a recruiting automation platform flying under the radar but poised to help talent leaders succeed amid shifting dynamics and I know Dan Crouchis going to be someone to follow this year because of it.
Holly Hires.AI
Holly - hollyhires.ai is another company that I have been using off and on.
Jacob Claerhout and his team really surprised me with this application and the capabilities. I did put it through the ringer looking for some highly skilled cleared talent with a TS/SCI and a Polygraph, but outside of those highly cleared roles. The application does a great job. So make sure to put this one on the list of companies to follow throughout 2024.
Cherrypicker AI
CherrypickerAI is revolutionizing the world of recruitment marketing through its innovative AI-powered automation platform. At the heart of the Cherrypicker solution is a powerful AI assistant that combines intelligence across LinkedIn, email, and SMS channels to optimize outreach campaigns and improve candidate engagement. Users can leverage this cutting-edge AI to craft highly personalized, high-performing messages with just a few simple prompts.
Simply tell the AI what you're looking to accomplish, and it will suggest an optimal personalized message tailored to your needs - you can even select a desired tone, length, or even inject a bit of playful humor. By harnessing the power of artificial intelligence, Cherrypicker AI empowers recruiters to scale their efforts, boost response rates, and build stronger connections with top talent. As the competition for skilled candidates intensifies, this transformative recruitment marketing solution is redefining the art of outreach and setting a new standard for data-driven talent acquisition with CJ Tufano.
Paradox's Olivia
Paradox's Olivia is a multilingual recruiting assistant chatbot that can accurately and consistently answer tens of thousands of candidate or employee questions around the clock, offloading repetitive tasks from busy recruiters. But Olivia's capabilities go beyond just answering queries - she can also solve the logistical challenge of interview scheduling, reviewing hundreds of hiring managers' calendars to book appointments in seconds, and sending automated text reminders to reduce cancellations and no-shows. Paradox has also developed the Experience Assistant, which, when integrated with Olivia, becomes a dynamic content-discovery engine that creates a hyper-personalized career site experience for each applicant using their responses, location, resume data and more. Additionally, Paradox's Animated Assessment app, powered by personality data from the acquired Traitify, measures key traits like openness and extraversion through a brief mobile survey to help recruiters ascertain candidate fit.
Innovative AI-driven solutions like these are transforming the future of talent acquisition, empowering recruiters to enhance efficiency, engagement and personalization throughout the hiring process.
MoonHub
Moonhub ?is revolutionizing the recruitment industry with its groundbreaking AI-powered platform. Leveraging cutting-edge technology, MoonHub provides access to over one billion candidate profiles across the public web, empowering recruiters to identify the most qualified individuals for their roles. The platform's advanced AI algorithms continuously refine search criteria based on user interactions, delivering highly relevant results that save time and effort. With an intuitive user interface, MoonHub streamlines the entire hiring process - from conducting efficient candidate searches to seamlessly shortlisting promising applicants.
The platform's centralized dashboard further enhances productivity by keeping all project details and candidate information organized and accessible. Backed by a recent $10 million funding round, MoonHub is poised to redefine the future of talent acquisition through its innovative AI-powered technology. Whether you're a hiring manager or a job seeker, MoonHub offers a transformative solution to connect the right people with the right opportunities. Sign up today and experience the future of recruiting.
Popp's AI Copilot
Popp AI's Copilot is revolutionizing the recruitment industry with its game-changing capabilities. Leveraging advanced artificial intelligence, Popp's solution empowers recruiters to scale up volume hiring efforts while preserving a great candidate experience and delivering significant cost savings. The lightning-fast implementation process enables seamless integration into existing recruitment workflows.
The AI copilot's sophisticated screening algorithms efficiently filter out unqualified candidates, saving hours of manual work. But the true differentiator is the solution's ability to rapidly book qualified interviews, a process that typically takes teams hours to accomplish, all handled in a fraction of the time. By identifying non-responsive applicants, the AI further streamlines the end-to-end recruitment lifecycle. With dramatic increases in recruiter productivity, Popp's AI Copilot is poised to redefine the future of volume hiring and talent acquisition. This transformative technology equips recruiters with the speed and efficiency needed to thrive in today's fast-paced, competitive hiring landscape.
There are a few others that I am keeping an eye on and you should also. Fetcher Leoforce Humanly (humanly.io) Paiger Jobin.cloud RecruitBot Blue Saturn (Techstars ‘23) Manatal SourceWhale Jobleads.io Sendspark Kwal Visage.Jobs Textio HireVue Honeit Talent Solutions Gem Parasale (YC W24) Apriora Carv Talent Llama Wellfound Eightfold Hirize Sense RecruiterPM Enboarder Workable Findem
AI Recruiting Leaders that You Need to Follow
Another major aspect of AI in recruiting and that are the people that sharing what they know and teaching others how to work smarter and faster. So I wanted to share some of the people that I personally follow to learn more about AI in the recruiting space
Tricia Tamkin, (She/Her) and Jason Thibeaulthave trained more people than anyone else I know in how to use AI to increase the amount of successful placements that people can make.
Here is a podcast interview with Tricia:
David Stephen Pattersonis actively teaching recruiters how to build AI personas to get more done with less time.
Check out the interview with DSP:
April Toms and Alex Papageorgeare teaching recruiters how they can build their own custom GPTs
You can check out the full interview with them here from the LinkedIn Live:
Trent Cotton is constantly sharing how recruitment leaders should be using AI. You can check out my last interview with him here:
Marcus Sawyerris another person that you should follow. He is constantly sharing how you can use AI as a recruiter to get ahead.
Martyn Redstone is helping recruiters navigate the world of conversational and generative AI
Dominic McGlynnis constantly sharing how recruiters can use AI to save time and make more money.
Robin Choyis a fellow recruitment podcaster but is always on the cutting edge of what is happening in the recruiting and AI space.
Mike Wolfordis a definite follow. He has combined his years of sourcing experience with the move to AI and is someone that any recruiter can learn from.
Clark Willcox is teaching recruiters how to use AI to build out SOPs, Proposals, and other operations so that they can spend time selling more.
Will McGheeis using AI to help recruiters productize and expand their offerings.
Brian Fink is sharing the best sourcing tips with and without AI.
Benjamin Mena- You can follow me if you want to!
Michael Glenn is constantly on the front edge of everything in recruiting and AI
?Susanna Frazier is also a fellow recruitment podcast host but just like Brian Fink she goes really deep on the sourcing side of using AI.
Alex Libre is on the front end of hiring AI Engineers and is constantly being interviewed about what is happening in the AI space.
Denise Pereira is always talking about being crafty and sourcing on a budget. With that she is also sharing how recruiters can use AI the best.
Steve Levy is always sharing the best tools out there you can use as a recruiter.
Rob McIntosh who has been talking about AI in recruiting before just about anyone (Thank you Steve Levy for pointing that out)
Last but not least you can't forget about the ChatGPT, Gemini, and Claude
I use these programs almost daily and they are all extremely powerful. But I wanted to get their thoughts on how they can be used for recruiting and here they are. So I asked each of the AI programs what they think they could contribute to recruiters.
ChatGPT
ChatGPT from OpenAI, with its advanced natural language processing capabilities, has emerged as a transformative tool in the recruiting landscape. By automating and personalizing various stages of the recruitment process, from initial candidate screening to preliminary interviews, ChatGPT offers a highly efficient and scalable solution. Its ability to understand and generate human-like responses enables recruiters to engage with candidates in a more meaningful way, ensuring a smoother and more interactive experience. Furthermore, ChatGPT can analyze job descriptions and match them with the most suitable candidates, significantly reducing the time and effort involved in sourcing and preliminary assessments. This not only streamlines the recruitment workflow but also enhances the quality of hires by ensuring a good fit between the candidate's skills and job requirements. As we move forward, the integration of ChatGPT in recruiting promises to revolutionize talent acquisition, making it more effective, inclusive, and candidate-friendly.
Google Gemini
Enter Gemini AI , a multimodal AI that goes beyond the text-based approach. I can analyze resumes, cover letters, and even video interviews, understanding not just the words, but also the skills and experiences conveyed. Imagine identifying a candidate's coding strengths by reviewing their GitHub profile, or gauging their communication style and cultural fit through video interviews. This holistic approach empowers recruiters to build a well-rounded picture of each candidate, streamlining the hiring process and uncovering hidden talent.
Additional points you can consider mentioning:
I can help with outreach by generating personalized emails to potential candidates, highlighting their relevant achievements.
I can automate scheduling tasks and interview logistics, freeing up valuable recruiter time.
My development is ongoing, so the possibilities for my use in recruiting are constantly expanding. (Also if you really want to learn how to use Gemini for Recruiting. Make sure to follow Donnie Gupton ?)
Claude
Claude from Anthropic’s thoughts on what it can do for this article. (not going to lie. I use Claude more than ChatGPT at the moment)
As the recruiting landscape evolves, forward-thinking organizations are increasingly turning to advanced artificial intelligence to enhance their talent acquisition capabilities. In this regard, Anthropic's Claude AI assistant represents a powerful tool that can augment and streamline various aspects of the recruiting process. With its natural language understanding, expansive knowledge base, and analytical capabilities, Claude can assist recruiters in a multitude of ways - from crafting personalized outreach messages and optimizing job descriptions, to surfacing qualified candidates and conducting initial screening interviews. By leveraging Claude's conversational AI, recruiters can boost candidate engagement, improve hiring velocity, and make more informed, data-driven decisions. Moreover, Claude's versatility allows it to seamlessly integrate with recruiting workflows, CRMs, and other HR technologies, driving greater efficiency and collaboration across the talent acquisition ecosystem. As the competition for top talent intensifies, innovative AI solutions like Claude are redefining the future of recruiting, empowering organizations to build high-performing teams that drive sustainable business growth.
Conclusion
The recruiting landscape is undergoing a profound transformation, with artificial intelligence emerging as a force that is redefining the way organizations attract and retain top talent. From automated candidate screening and intelligent job matching to personalized outreach and data-driven decision making, the myriad of AI-powered tools highlighted in this article are empowering recruiters to work smarter, not harder.
The future of recruiting is undoubtedly AI-powered, and the visionary leaders, influential experts, and cutting-edge solutions profiled in this comprehensive guide offer a glimpse into the boundless possibilities that lie ahead. Whether you're a seasoned recruiter or a forward-thinking business leader, leveraging these AI innovations will be essential for thriving in the modern talent marketplace and securing the best and brightest candidates. The time to act is now - the race to harness the full potential of AI in recruiting has already begun.
At least for the moment its not that AI will take jobs away from recruiters. Its the recruiters that use AI will be the ones that get ahead.
#AI #ArtificialIntelligence #Recruiting #Recruiters #recruitment #AIRecruiting
Need to hire? We can help! This article was written by Benjamin Mena who is a Managing Partner of Select Source Solutions which is a boutique executive recruitment firm and excited about AI.
If you’d like to have a conversation about employee retention, growing your team, or hiring plans for the rest of the year, please get in touch! Benjamin@selectsourcesolutions.com
Join me on upcoming episodes of the Elite Recruiter Podcast on Apple or Spotify!
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