The best HR & People Analytics articles of July 2025HR如何在AI时代掌握主动？David Green发布的7月《Data Driven HR Monthly》汇集全球顶尖报告与实践，聚焦“技能+任务”新范式、AI对员工体验与倦怠的双面影响，以及CHRO在企业AI战略中的领导地位。BCG数据显示，印度AI使用率达92%，但全球员工对AI培训满意度仅36%。Upwork报告揭示：高效AI用户更易疲惫离职。McKinsey与Gartner呼吁HR重构组织模型与人才规划体系。本期还探讨神经多元、NASA人才图谱与“Vibe Coding”等创新实践。
I always enjoy spending time in India, so I was delighted to arrive in Delhi yesterday ahead of People Matters Tech HR later this week. I’ll be delivering the opening keynote on how HR leaders can ace the next curve of change as well as leading a workshop on the science of better decisions. I’m looking forward to catching up with fellow speakers such as Jason Averbook (tip: subscribe to his Now to Next blog, if you don’t already), Pushkaraj Bidwai, Mukesh Jain, and Shefali Raias well as immersing myself in what is happening in the Indian HR tech scene.
In this month’s edition of the Data Driven HR Monthly, which comes against the backdrop of CEOs flexing on the impact of AI on jobs, I’ve included new research from BCG and Upwork on AI at work, and the role of HR. Marc Effron is spot on here with his assessment that CHROs need to be leading the strategic conversation with the executive team on their desire to reduce costs through job reduction enabled by AI: “CHROs can lead this conversation through organization, operating model and job design, where we should be experts.”
I expect plenty of discussion at Tech HR on this topic as well as the wider impact of AI on work, the workforce, and the workplace. One of the messages, I’ll look to get across in my keynote is:
AI guides, but humans decide. We must prioritise the ‘H’ in HR.
This edition of the Data Driven HR Monthly is sponsored by our friends at TechWolf
Skills, Tasks, and Workforce Intelligence: Navigating the AI Transformation
This month’s edition highlights an important conversation from the TechWolf Podcast, recorded live in New York, featuring Marc Steven Ramos, global learning leader with 25+ years’ global transformation experience with Google, Microsoft, Accenture, Novartis, Oracle, and Cornerstone, and Jeroen Van Hautte ?, CTO & Co-Founder of TechWolf.
The discussion explores how task-based intelligence complements skills data to create a complete view of workforce capabilities, empowering organizations to navigate one of the largest business transformations in history: the AI-driven redefinition of work.
Skills without context can be ambiguous. Tasks ground them in real work, and that’s where change, productivity, and AI come together — Marc Ramos
Why This Matters Now:
The pace of change in the workforce is unprecedented. Leading enterprises are already recognizing that workforce intelligence - the ability to understand, predict, and act on how work is changing in real time - is no longer optional.
From skills to skills + tasks + jobs: Combining these data points allows organizations to connect individual capabilities to tangible outputs and outcomes.
AI as a catalyst: AI is accelerating job evolution, making real-time visibility into tasks and skills essential for workforce planning and redeployment.
Strategic urgency for boards: Workforce automation isn’t a distant trend — it is reshaping workforces today, creating pressure on executives to act on reskilling, redeployment, and workforce design at speed.
To really understand a skill, you need to understand the context in which it’s applied — the tasks. And that’s where AI can add transformative clarity — Jeroen Van Hautte
For HR leaders, this is an opportunity to lead. With skills and tasks as the foundation, HR is uniquely positioned to drive cultural alignment, manage change, and deliver on the board-level mandate to prepare workforces for the AI era.
Listen to the Episode: ?️ Marc Ramos & Jeroen Van Hautte on Tasks, Skills & the Future of Work (TechWolf website summary)
To sponsor an edition of the Data Driven HR Monthly, and share your brand with more than 145,000 Data Driven HR Monthly subscribers, send an email to dgreen@zandel.org.
JULY ROAD REPORT
Until flying to Delhi yesterday, as mentioned above for Tech HR India later this week, July had been a light month of travel other than a short trip to Switzerland to run an AI workshop with the HR leadership team of one of the companies that are part of the Insight222 People Analytics Program. For those interested, one of my speaking engagements from earlier this year, at the Wharton People Analytics Conference, is now available to view (see below). In the talk, I explore the critical role of data democratisation and adoption in driving workforce insights, enhancing decision-making, and scaling HR’s strategic impact. I also share best practices from our work and research at Insight222 for making people analytics accessible to leaders and employees alike, the challenges of adoption, and the key investments required to unlock the full potential of workforce data. Enjoy!
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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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HYBRID, GENERATIVE AI AND THE FUTURE OF WORK
BCG - AI at Work: Momentum Builds, but Gaps Remain | JOHN BRAZIER AND NICK SOUTH - BCG’s AI at Work 2025 report: Four takeaways for HR leaders
Companies are realizing that merely introducing AI tools into existing ways of working isn’t enough to unlock their full potential. The real magic happens—and value generated —when businesses go further and reshape their workflows end-to-end.
BCG’s annual AI at work global survey of employees is packed full of insights and guidance for business and HR leaders looking to maximise value, adoption and employee experience with AI. The key takeaways include: (1) AI is now part of our daily work lives: 72% of respondents are regular AI users (although adoption amongst frontline employees has stalled at 51%). (2) Investment in training, leadership support and access to the right tools can break this ceiling: Yet only 36% of employees are satisfied with their AI training. (3) The Global South is showing higher adoption of AI. India leads the pack with 92% of regular users compared to the US (64%), UK (68%) and Japan (51%). (4) The next frontier: from adoption to value with end-to-end redesign. One-half of respondents say their company is starting to reshape processes. These companies also invest more in their people – and it pays off (see FIG 1). (5) AI agents are not widely deployed. Only 13% see agents integrated into broader workflows (see FIG 2). Kudos to the authors: Vinciane Beauchene, Sylvain Duranton, Nipun Kalra, and David Martin. For HR leaders, I also recommend reading John Brazier’s interview with BCG’s Nick South about the implications of the report’s findings for HR on the UNLEASH blog.
FIG 1: The relationship between workflow redesign due to AI and investment in people (Source: BCG)
FIG 2: Use of AI agents (Source: BCG)
GABBY BURLACU AND KELLY MONAHAN - From Tools to Teammates: Navigating the New Human-AI Relationship
Full time employees getting the most done with AI are also the most burned out, disengaged, and disconnected from their teams.
In their study for the Upwork Research Institute, Gabriela (Gabby) Burlacu and Kelly Monahan, Ph.D. identify a crucial message for the future of work: while AI is undeniably boosting productivity – with a reported 40% jump for many workers – it's also creating a human paradox. Alarmingly, top AI performers are experiencing high burnout (88%) and are twice as likely to leave, often feeling disconnected from strategy and even trusting AI more than human colleagues (see FIG 3 and 4). The report offers three urgent calls to action for business leaders: (1) Redesign work for human-centered, AI-empowered talent and workflows, prioritising autonomy, trust and psychological safety. (2) Cultivate flexible and resilient talent ecosystems, combining full-time employees, freelancers, and AI capabilities to create agile, resilient, and high-performing teams. (3) Redefine AI strategies to focus on the end-to-end human experience, including new roles, norms, and governance. For HR leaders, these findings are a wake-up call. We must prioritise the relational side of AI, ensuring human connection, well-being, and purpose are augmented, not eroded. It's about preventing burnout in our most productive AI users, fostering alignment, and learning from agile models like freelancers to build a truly sustainable human-AI collaborative future.
FIG 3: The human cost of AI productivity (Source: The Upwork Research Institute)
FIG 4: The rise of human-like relationships with AI (Source: The Upwork Research Institute)
COBUS GREYLING - Do AI Agents Substitute Human Workers — Or Enable Humans To Succeed In New Ways? | L. ELISA CELIS, LINGXIAO HUANG, AND NISHEETH K. VISHNOI - A Mathematical Framework for AI-Human Integration in Work
AI Agents are good at tasks not jobs…
In his article, Cobus Greyling provides an insightful and accessible analysis of a new study by Elisa Celis, Lingxiao Huang, and Nisheeth Vishnoi, which presents a mathematical framework that models jobs, workers, and worker-job fit, and introduces a novel decomposition of skills into decision-level and action-level subskills to reflect the complementary strengths of humans and GenAI. Greyling’s incisive analysis offers a helpful perspective for HR leaders navigating the future of work. His core message is clear: AI agents are fantastic at tasks, not entire jobs. They're not just substitutes, but powerful amplifiers of human capability, especially for less experienced workers, effectively compressing productivity gaps and fostering extraordinary collaboration. Here are four key learnings for HR: (1) Agentic AI Augments Human Potential: AI agents boost efficiency and performance, particularly for junior talent, by handling structured tasks and freeing humans for higher-order work. (2) Redefine Skills & Development: While AI takes on the mundane, HR must strategically ensure continuous skill development, focusing on uniquely human capabilities like judgment, creativity, and complex problem-solving. (3) Design for Human-AI Synergy: Organisational design must pivot to foster premium collaborations between humans and AI. It's about combining complementary strengths to achieve outcomes greater than the sum of the parts. (4) HR Leads Strategic Integration: Our role in HR is pivotal. We must orchestrate the strategic integration of agentic AI, balancing its efficiency gains with the imperative to preserve and nurture human ingenuity, driving both innovation and connection.
FIG 5: Al for work: skill difficulty continuum (Source: Cobus Greyling)
PEOPLE ANALYTICS
KETAKI SODHI AND COLE NAPPER - Who Needs a “Human in the Loop” When AI Gives Itself Feedback
Ketaki Sodhi, PhD, Program Owner for Agentic Listening and Analytics at Microsoft, and Cole Napper provide a fascinating perspective on the "human in the loop" concept for Generative AI, provocatively asking: which human, and how? This isn't just a technical question; it's where I/O Psychology and People Analytics come into their own. The article frames AI "evals"— the systems for assessing whether AI outputs are useful, accurate or aligned —as essentially performance management for Large Language Models. Just as we've wrestled with defining "good" in complex human knowledge work for decades, we now face the same challenge in building AI systems. In a world of infinite " " answers, AI evals demand the same nuance we apply to human systems: competency models, multi-rater input, calibration, and context. One of the key takeaways from Ketaki and Cole is that true success lies not in chasing perfect answers from AI, but in designing smart, human-informed systems. These are the systems that can discern between good, better, and what genuinely drives impact for your organisation. For people analytics leaders and I/O psychologists, this is a clarion call to leverage their deep expertise in human performance to shape the very fabric of our AI-driven future.
FIG 6: Source – Ketaki Sodhi
BEN BERRY - The future is built by everyone: What is Vibe Coding and why should People Analytics teams adopt it | ROSARIO GERMINO - From People Analytics to People Economics and Impact | ADRIAN PEREZ – GitLab People Analytics Team Handbook | DOMINIK TOMICEVIC - Can NASA’s People Graph and LLMs Revolutionize Workforce Planning? | MORGAN DEPENBUSCH - How to let color do the storytelling
In each edition of the Data Driven HR Monthly, I feature a collection of articles by current and recent people analytics leaders. These are intended to act as a spur and inspiration to the field. Five are highlighted in this month’s edition: (1) In a particularly insightful piece, Ben Berry examines whether vibe coding, a product management practice of using AI tools to rapidly build functional prototypes to help turn rough ideas into working concepts, should be adopted in people analytics. (2) In her thoughtful article, Rosario Germino argues that to elevate people decisions to the same level of strategic investment as product or finance, we need a new way of thinking—and a new kind of function – People Economics and Impact, which she then breaks down into the why (see FIG 7 on the multi-dimensional aspect of informed decision making), what and how. (3) In a recent post, Adrian M. Pérez provides open source access to GitHub’s People Analytics Team Handbook, a rich resources covering areas such as (i) data governance framework, (ii) tools and methodologies, (iii) survey administration, and (iv) Tableau dashboard strategies. (4) Dominik Tomicevic provides a compelling account of how NASA’s People Graph is supporting a range of priorities from upskilling to workforce planning – with insights from the NASA team of David Meza, Madison Ostermann and Katharine Knott, MBA: “Knowledge graphs offer flexibility, since you don’t need a full schema upfront. We began with known relationships and expanded as we uncovered more insights in the data.” (5) In an edition of her excellent Trending Up newsletter, Morgan Depenbusch, PhD offers some compelling guidance on the use of colour in data visualisation and storytelling.
FIG 7: Informed decisions are multi-dimensional. Financial logic makes them investable (Source: Rosario Germino)
THE EVOLUTION OF HR, LEARNING, AND DATA DRIVEN CULTURE
MCKINSEY - HR Monitor 2025
The gap is widening between what is needed from an efficient, effective HR function and what most organizations currently offer
McKinsey's HR Monitor 2025 benchmark study of workforce and HR trends across Europe, delivers a sharp analysis of the critical shifts shaping the HR profession, emphasising that the next 12-24 months are decisive for the function. The report identifies five key trends: (1) Workforce planning is not approached strategically enough – see FIG 8 - (“…with rapid changes driven by gen AI and shifting skill needs, workforce planning must move beyond short-term staffing forecasts to include a longer-term view and future-scenario planning”). (2) Talent acquisition is becoming more complex: with only 56% offer acceptance rates, 18% of new hires leaving during their probationary period and the overall hiring success rate in Europe standing at a lowly 46%, a more strategic and coordinated approach to attracting and hiring talent is required. (3) Employee development continues to be highly fragmented (“To prepare the workforce for future challenges, organizations must connect performance management, learning and development, and talent development in one cohesive strategy”). (4) Employee experience is essential—and underdeveloped (“A more tailored, data-driven approach to the employee experience is needed to build motivation and long-term commitment to employers”). (5) Gen AI and shared-services centres could boost efficiency and effectiveness (“HR departments must modernize their operating models by expanding SSC adoption and using automation and gen AI to increase speed, scalability, and strategic impact”). For Chief People Officers, the message is clear: You must align HR strategy directly with business priorities, strengthen your HR operating model, and aggressively build digital and AI skills within HR. This is about laying the foundation for a modern, AI-enabled HR function that is both deeply people-centric and laser-focused on organizational performance. Kudos to the authors: Julian Kirchherr, Vincent Bérubé, Charlotte Seiler, Dr. Kira Alexandra Rupietta, Kristina Stoerk, Nina-Marlene Senst, and Simon Gallot Lavallée.
...with rapid changes driven by gen AI and shifting skill needs, workforce planning must move beyond short-term staffing forecasts to include a longer-term view and future-scenario planning
FIG 8: Engagement in workforce planning (Source: McKinsey)
FIG 9: Predicted impact of gen AI on HR department (Source: McKinsey)
ESER RIZAOGLU AND STEPHANIE CLEMENT - How CHROs Can Prepare Their Function and the Enterprise for AI Transformation
CHROs play a key role in safely using AI at scale to deliver business outcomes.
Recent research by Eser Rizaoglu and Stephanie Clement for Gartner provides a helpful roadmap for CHROs steering their organisations through AI transformation, by focusing on HR's pivotal role in shaping the future of work. The report highlights three key actions for CHROs to enable their organisation's AI approach: (1) Assist in delivering business outcomes using AI: Leverage GenAI for HR productivity first, then expand to drive enterprise-wide improvements with a broader AI portfolio. (2) Manage behavioural outcomes of AI: Cultivate a culture of innovation, build human-centred change management plans, and introduce new HR roles to foster human-machine partnerships. (3) Enable workforce readiness for AI: Implement AI literacy programs for all (see FIG 10), while targeting upskilling efforts on segments most impacted, building empathy, and tracking readiness indicators. For CHROs in Steady-AI-Pace organisations, the focus is on foundational AI literacy and policy. Those at an Accelerated-AI-Pace must deepen this by targeting high-impact workforce segments and deploying AI champions to drive effective, human-centric change.
FIG 10: AI Literacy Program Roadmap (Source: Gartner)
DAVE ULRICH - Navigating Eight Paradoxes of AI for HR
When algorithms combine with human empathy, judgement, and creativity, sustained progress occurs.
In his article, Dave Ulrich highlights eight paradoxes on the AI for HR agenda that he believes business and HR leaders need to navigate to move up the s-curve and waves of HR impact (see FIG 11) to deliver more value. As Dave explains: “Navigating (not just managing) paradox means highlighting and working through opposing ideas—each of which is valid—that combine to create more value.” The eight paradoxes identified in the article are: (1) AI and AI: Artificial Intelligence * Authentic Intimacy. (2) Remove jobs and redefine work. (3) Bottom line efficiency and top line growth. (4) Distribute and concentrate power. (5) Lower and increase risk. (6) Expand perspective and reduce cognition. (7) Provide answers and explore questions. (8) Isolate and connect.
FIG 11: Five stages of AI for HR evolution (Source: Dave Ulrich)
EMPLOYEE LISTENING, EMPLOYEE EXPERIENCE, AND EMPLOYEE WELLBEING
JARED WEINTRAUB - A day in the life of a GenAI-enabled workforce
Deloitte forecasts that 25 percent of companies currently using GenAI will launch agentic pilots this year, rising to 50 percent by 2027
Jared Weintraub, PhD, SPHR's article for Deloitte paints a tantalising picture of a 'Gen-AI enabled workforce,' showcasing how AI agents are already transforming our daily work. Through a fictional Fortune500 company, Jared brings to life three key personas: (1) New Hire (Riley): Experiences personalised onboarding, with AI agents helping her navigate culture and quickly excel in her role. (2) VP (Taylor): Sees optimised leadership workflows, receiving instant summaries, personalised action items, and even real-time feedback on calls. (3) CEO (Angelina): Gains powerful support for strategic decision-making, with AI agents providing real-time insights and even coaching for high-stakes events like public town halls. These examples demonstrate AI's profound potential not to replace workers, but to fundamentally enhance human potential, leading to a significantly improved employee experience where individuals, teams, and organisations can thrive and perform at their absolute best. Thanks to Brian Heger for highlighting in his excellent Talent Edge Weekly.
WORKFORCE PLANNING, ORG DESIGN, AND SKILLS-BASED ORGANISATIONS
SCOTT REIDA AND KRISTIN SABOE - Applying the Rule of 72 to Workforce Skill Obsolescence and Productivity Degradation
Amazon's Scott Reida and Google's Kristin Saboe, Ph.D. introduce a powerful financial concept to HR: the "Rule of 72." Traditionally, it's a shortcut to estimate how long an investment takes to double, by dividing 72 by its annual growth rate. They ingeniously flip this, applying it to skill evolution: by dividing 72 by a role's weighted average 3-year Compound Annual Growth Rate (CAGR) of its skills, one estimates the "years to obsolescence" if no upskilling occurs. This provides critical directional clarity on how fast job competencies are shifting. Their framework, illustrated in FIG 12, categorises skills into four key zones: (1) Emerging (low adoption, high growth, representing the cutting edge). (2) Table Stakes (widely adopted, foundational must-haves with steady growth). (3) On the Cusp (moderate adoption, sustained expansion, offering long-term value). (4) Sunset (declining demand, requiring intentional upskilling). This enables smarter workforce planning. HR can now target training budgets where skill erosion is rapid, shifting from reactive to proactive strategies. It transforms talent into a dynamic portfolio , informing sharper hiring and career development in our accelerating world.
FIG 12: Categorising skills into four key zones (Source – Scott Reida and Kristin Saboe)
McKINSEY - The new rules for getting your operating model redesign right
When people feel invested in and supported, they are more likely to embrace change, contribute meaningfully, and sustain the behaviors that drive long-term impact.
New research from McKinsey updating their nine golden rules for operating model redesign, which finds that five original (evergreen) rules have stood the test of time while four new (evolved) rules have emerged (see FIG 13). The study identifies a key finding: redesign success jumps from 59 percent when using all nine original rules to 97 percent when using all nine in the refreshed set. The article also presents four broad redesign themes for leaders to focus on: (1) Create alignment among leaders and decision-makers, grounded in strategy. (2) Invest deeply in rewiring workflows. (3) Make significant investments in people. (4) Create a performance-oriented culture for durable impact. For Chief People Officers, the key takeaway is that they need to become the architects of dynamic, human-centric operating models. Their focus shifts from traditional talent management to proactively designing how work gets done, emphasising skills and capabilities over static roles. CPOs should also lead on ethical AI integration, foster a culture of continuous learning, and empower leaders. This creates a workforce built for perpetual reinvention, driving sustained value in an increasingly uncertain world. Kudos to the authors: Brooke Weddle, J.R. Maxwell, Tristan Allen, Deepak Mahadevan, Elizabeth Mygatt, and Olli Salo.
FIG 13: The refreshed golden rules of organisational redesign (Source: McKinsey)
LEADERSHIP, CULTURE, AND LEARNING
JEFF WETZLER - The Right Way to Prepare for a High-Stakes Conversation
Curiosity increases your ability to process new information and respond creatively to complex problems. It activates the brain’s learning and reward centers, increasing your capacity for insight and creative problem-solving.
In his recent HBR article, Jeff Wetzler introduces a helpful concept for leaders: The Curiosity Check (see FIG 14). This diagnostic is designed to fundamentally shift your mindset from defensive certainty to productive curiosity, and so improve your effectiveness in high-stakes discussions and boost your influence. It’s all about unlocking crucial, often hidden, insights. Wetzler outlines three actionable steps: (1) Choose Curiosity Over Certainty: Actively ask yourself "What am I missing?" challenging your assumptions. (2) Make It Safe to Speak Up: Create an environment where people feel secure sharing their true thoughts, proving safety through action, not just words. (3) Pose Quality Questions: Shift from shallow or leading questions to open-ended, neutral, and deeper inquiries that encourage genuine reflection. Wetzler brings this to life with examples, highlighting how leaders often miss critical information when they assume team alignment, never probing for the "unspoken thoughts" that hold the real insights. This approach empowers you to tap into wisdom you might otherwise completely overlook. Thanks to Amy Edmondson for highlighting.
FIG 14: The Curiosity Curve (Source: Jeff Wetzler)
MCKINSEY RESEARCH AND INNOVATION LEARNING LAB – Reimagined: Development for the Future of Work – Evolving Trends in L&D Article | Full report
Leaders must prepare for a future defined by radical candor regarding the impacts of AI on work and the workforce.
The 2025 McKinsey Learning Perspective spotlights three interconnected themes crucial for people development in a rapidly changing world: (1) Fluid Development Ecosystems: Organisations must design work to be inherently developmental, shifting from rigid structures to dynamic, data-driven ecosystems. This means de-siloing HR functions and embedding learning into daily work, making growth continuous and seamless. The goal is to make daily challenges catalysts for growth, supported by real-time data and foresight. (2) Responsible AI Adoption: This defining moment demands leaders preserve employee trust by showing AI will help them thrive, not just automate work. It's about fostering powerful human-AI collaboration, offloading repetitive tasks to AI to unlock human creativity and higher-order skills. Responsible adoption hinges on equipping employees with uniquely human capabilities like critical thinking and judgment. (3) Resilient and Adaptable Individuals and Organisations: Thriving organisations anticipate challenges, adapt, and grow, building structural and cultural foundations for resilience. This involves unlocking the potential of diverse, multigenerational workforces, supporting recuperation to prevent burnout, and enabling organisational resilience through sustainable workflows. It means seeing resilience as a shared, cultivated capability, not just an individual trait. Read the article by Heather Stefanski, Benjamin Hall, Jake Gittleson, and Jessica Glazer, and then dive into the full report, which also includes contributions from the likes of Sandra Durth.
DIVERSITY, EQUITY, INCLUSION AND BELONGING
ROBERT D. AUSTIN, NEIL BARNETT, CHLOE R. CAMERON, HIREN SHUKLA, THORKIL SONNE, AND JOSE VELASCO - How Neuroinclusion Builds Organizational Capabilities
Leaders should consider neuro-inclusion as a strategic capability-building opportunity rather than a diversity initiative
In a rapidly evolving world, neuro-inclusion is emerging as a critical organisational capability, as highlighted by Robert Austin, Neil Barnett, Chloe Cameron, Hiren Shukla, Thorkil Sonne, and Jose Velasco in the MIT Sloan Management Review. This isn't merely a diversity initiative; it's a strategic imperative that unlocks competitive advantage by leveraging the rich, natural variation in human cognition. By intentionally designing processes for neurodistinct individuals, organisations can profoundly improve: (1) Hiring, by tapping into overlooked talent pools with unique skills (as seen with SAP attracting highly credentialed candidates often missed by traditional interviews); (2) Innovation, through diverse perspectives that spark novel solutions (Microsoft's Teams ‘Blur’ feature emerged from a neurodistinct engineer's insights); and ultimately, (3) Culture, by fostering a more adaptive and truly inclusive environment for everyone. As the article reveals, EY, Microsoft, and SAP are prime examples of organisations already reaping these benefits, demonstrating that embracing neurodiversity enhances collective intelligence and drives superior business outcomes.
FRANK DOBBIN AND ALEXANDRA KALEV - Achieve DEI Goals Without DEI Programs
Many management innovations designed to improve performance actually boost workforce diversity as well, without inviting the backlash of formal DEI programs.
Frank Dobbin and Alexandra Kalev, in their recent HBR article, challenge the traditional view of DEI. They argue that as formal DEI programs face headwinds, HR leaders can still drive significant diversity, equity, and inclusion by focusing on high-performance management techniques that naturally foster inclusion and improve business outcomes, all without the ‘DEI program’ label. They highlight five powerful techniques and provide examples of how these have been implemented by companies: (1) Referral programs: Companies like Oracle use these effectively, often boosting representation organically. (2) Skills upgrading: Walmart exemplifies this, investing in employee upskilling that broadens opportunities for diverse talent (see FIG 15). (3) Mentoring programs: IBM has long leveraged robust mentoring to support career progression across all groups. (4) Scheduling flexibility and stability: Gap demonstrates how providing predictable yet flexible schedules empowers diverse workforces. (5) Performance-based retention: Amazon uses data-driven approaches to identify and retain top performers, inherently benefiting those who excel regardless of background (also see FIG 15). This approach embeds DEI within the fabric of how we manage and develop our people, making it an undeniable component of business success. It’s about doing good by doing well.
FIG 15: Walmart and Amazon’s changing workforces (Source: Dobbin and Kalev)
HR TECH VOICES
Much of the innovation in the field continues to be driven by the vendor and analyst community, and I’ve picked out a few resources from July that I recommend readers delve into:
LISA K. SIMON - How Much Is a Skill Worth?
In her article, Lisa K. Simon, Chief Economist at Revelio Labs, presents the findings of a new paper, she co-authored with David Dorn, Ludger Woessmann, Moritz Seebacher and Florian Schoner, which finds that the number and type of skills workers report are strong predictors of how much they earn: “In fact, differences in skills predict earnings better than differences in education or past experience. Workers who list more skills tend to be in better-paid jobs. On average, each additional skill listed on a resume is associated with 0.67 percentage points higher earnings.” Another finding is that not all skills are valued equally, with occupation-specific and managerial skills providing the largest boost to income, while a higher prevalence of general skills is associated with lower earnings (see FIG 16). Thanks to Seth Hollander, MBA for highlighting the article and paper.
Workers who list more skills tend to be in better-paid jobs. On average, each additional skill listed on a resume is associated with 0.67 percentage points higher earnings.
FIG 16: Only having general skills on a resume is associated with lower earnings (Source: Revelio Labs)
WARDEN AI - State of AI Bias in Talent Acquisition
This is an excellent new report from Jeffrey Pole and the team at Warden AI, which provides a comprehensive and data-driven review of AI bias, compliance and responsible AI practices in talent acquisition – the area of HR, which perhaps has the most significant adoption of AI. With a foreword by Kyle Lagunas, and contributions from the likes of Hung Lee (see quote below) and Sarah Smart, Sultan Murad Saidov and Trent Cotton, key findings include: (1) 75% of HR leaders say bias is a top concern when adopting AI. (2) 15% of AI systems fail to meet fairness metrics for one or more demographic group. (3) AI scores 0.94 vs 0.67 for humans, outperforming on average across fairness metrics (see FIG 17). (4) AI is up to 45% more fair than humans for women and racial minority candidates. Congrats too to Jeff and the team for raising $1.6m in a recent funding round.
We are right to worry about AI bias, but we should not forget that the baseline, human only judgment, is far from bias-free - Hung Lee
FIG 17: AI outperforms humans across fairness metrics (Source - Warden AI, State of AI Bias in Talent Acquisition)
COLE NAPPER - From HR Skills…to HR Jobs
When new trends emerge at work, they are likely to first appear as skills. As skills evolve, they consolidate into job titles and full occupations.
The prolific Cole Napper highlights Lightcast data to paint a compelling analysis on the journey of people analytics, workforce planning and talent intelligence from trends to skills to jobs: “When new trends emerge at work, they are likely to first appear as skills. As skills evolve, they consolidate into job titles and full occupations.” In the article, Cole presents data visualisations and analysis on how job postings mentioning each of the three skills fluctuated over time, how this translated into job titles, and the wage premium (see FIG 18) that these three categories have on HR salaries in general (on the theme of people strategy and analytics salaries, read this post by Pallavi Narang) Look out for Cole’s book, People Analytics: Using data-driven HR and Gen AI as a business asset, which is available for pre-order now ahead of being published on August 26.
FIG 18: Median salaries in HR areas (Source: Lightcast)
PODCASTS OF THE MONTH
In another month of high-quality podcasts, I’ve selected four gems for your aural pleasure: (you can also check out the latest episodes of the Digital HR Leaders Podcast – see ‘From My Desk’ below):
PETER FASOLO - Leading with impact as a chief human resources officer – In this must-listen episode of Capital H, Peter Fasolo, Ph.D., former chief human resources officer at Johnson & Johnson, joins host Kyle Forrest to discuss the power of systems thinking, board collaboration, aligning your people agenda with enterprise strategy, and more.
ANGELA LE MATHON - AI-Native HR Operating Model & AI Agents for Skills/Tasks – The brilliant Angela LE MATHON joins Cole Napper to discuss how AI is transforming the work that people analytics does and how the function operates as well as envisioning a new AI-native operating model for HR.
SVENJA GUDELL, BROOKE WEDDLE, AND BRYAN HANCOCK - What the labor market isn’t telling you—yet – Svenja Gudell, chief economist at Indeed, joins Brooke Weddle, Bryan Hancock, and host Lucia Rahilly, on an episode of McKinsey Talks Talent to help leaders make sense of the current collision of labour market trends: generative AI, agentic AI, an aging workforce, shifting priorities, and more.
BEN WEIN – How Bristol-Myers Squibb used skills data to solve a life-or-death talent shortage – Ben Wein, Director of Workforce Skills Enablement at Bristol Myers Squibb, joins Julius Schelstraete ? on The TechWolf Podcast to share how BMS is becoming a skills-based organisation—starting with a business-critical talent shortage in cell therapy manufacturing. Ben explains how BMS uses skills data to drive faster hiring, smarter workforce planning, and ultimately, patient impact.
VIDEO OF THE MONTH
DJ PATIL - Data, Decisions, and the Future of Work: How AI and Curiosity Are Redefining Careers
Many of the videos of the talks at the recent Wharton People Analytics Conference are now available on the Wharton School YouTube channel, including my talk on How Top Companies Scale People Analytics Adoption. There are some wonderful talks from the likes of Amy Edmondson, Ravin Jesuthasan, CFA, FRSA, Ben Waber, Karalee Close, Guru Sethupathy and Michael Fraccaro, but perhaps my favourite session of the two days was former US Chief Data Scientist DJ Patil’s fireside chat with Eric Bradlow on how firms can harness data science to navigate the future of work. They explore the evolving relationship between AI and human collaboration, the promises and pitfalls of algorithmic management, and how leaders can build ethical, resilient, and high-performing organizations in an increasingly data-driven world.
BOOKS OF THE MONTH
Given it’s the summer in Europe and North America, here are two books to read while you are getting some well-earned relaxation time:
PETER HINSSEN – The Uncertainty Principle - Peter Hinssen's The Uncertainty Principle, his fifth book, is a vital read for HR leaders. It argues we're in a "Never Normal" world, where constant change is inevitable. Hinssen transforms uncertainty from a threat to an opportunity, urging us to move faster and think bigger. For HR, this means embracing ambiguity, leading cultural shifts, leveraging people data, and redefining talent and leadership for relentless evolution. It's about equipping our people to thrive and transform every challenge into a strategic advantage. For a preview of the book, I recommend Peter’s recent discussion with me on the Digital HR Leaders podcast: Uncertainty as an Opportunity: HR's role in Shaping the Future.
JENNY DEARBORN AND KELLY RIDER - The Insight-Driven Leader: How High-Performing Companies are Using Analytics to Unlock Business Value - Jenny Dearborn, MBA and Kelly Rider's The Insight-Driven Leader is an inspirational guide to unlocking serious business value through people analytics. This book shows how to transform raw data into powerful workforce insights, solving critical challenges and driving success. You'll learn: (1) How to move beyond traditional rear-view HR metrics to actionable insights. (2) Real-life case studies from leading organisations, as well as cautionary tales. (3) Recommendations for becoming an insights-driven organization using workforce analytics. The book is a must-read for leaders aiming to align data with strategy and build a truly insight-driven culture.
FROM MY DESK
July saw four new episodes of the Digital HR Leaders podcast – all sponsored by our friends at Mercer (thanks IŞIL ÇAYIRLI KETENCI):
ANSHUL SHEOPURI - How People Analytics is Powering Business Strategy - Anshul Sheopuri, Executive Vice President of People Operations & Insights at Mastercard, joins me for a conversation on how to embed analytics into enterprise-wide decision-making at scale. Thanks to Sasha Houlihan for organising.
PETER HINSSEN - Uncertainty as an Opportunity: HR's role in Shaping the Future – As highlighted in the Books of the Month above, Peter Hinssen joined me to discuss what it really takes for HR to embrace uncertainty and lead in this era of the ‘Never Normal.’
RAVIN JESUTHASAN AND BRIAN FISHER - The Skills Revolution: Your Playbook for Workforce Agility – Ravin Jesuthasan, CFA, FRSA and Brian Fisher join me to explore why skills-based workforce planning has surged to the top of the HR agenda - and what leading companies are doing to turn intent into action.
AMY BAXENDALE - How Arcadis Built a Skills-Powered Organisation – Amy Baxendale , Global Future of Workforce Director at Arcadis, provides a detailed guide on the journey the company has embarked to become a skills-powered organisation. The episode includes discussion on the business case, securing sponsorship, setting up governance, the partnership with Mercer and Eightfold, and the early benefits:
We are early in the journey, but we are seeing some promising signs of progress. Our time to hire is trending downwards - that has a direct commercial impact for the business. We've also actually been able to calculate the financial impact of work that's being completed through gigs and show the actual impact on EBITDA
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 525 roles with half of these being new.
THANK YOU
To HR magazine and Charissa King for including me again in their annual HR Most Influential list as one of the ten most influential practitioners
The Talent Games for including the Digital HR Leaders podcast at #6 in its 27 Best Leadership Podcasts for HR Leaders.
Steve Sands for including my work as part of his Human Resource Management Analytics night class at the National College of Ireland.
A huge thank you to the following people who either shared the June edition of Data Driven HR Monthly and/or posted about the Digital HR Leaders podcast, conferences or other content. It's much appreciated: Emmanuel Duncan, Rob Baker, FCIPD, MAPP, Richard Hall, Robert Rogowski, Catherine de la Poer, Caroline Lambe, Jeremy Sholl, Narelle Burke, Edan Halili, Francesca Caroleo (SHRM-SCP, ICF-ACC), Uwe Gohr, Joseph Frank, PhD CCP GWCCM, Randeep Kaur, Aaron Chasan, Danial Singh Kang, Jorge-Luis Gonzalez, Anisha Moosaأنيشا موسى?????, Carlos Lopes, Danielle Farrell, MA, CSM, Kris Saling, Hiroyuki MIYAI, Ph.D., Yukiko Hosomi, Dr. Christoph Spöck, Joachim Rotzinger, Kevin Le Vaillant, Seung Won Yoon, Alexis Fink, Timo Tischer, Dr. Tobias Bartholomé, Jose Luis Chavez Vasquez, Meg Bear, Abhinav Tiwari, Esther Abraas, Gareth Flynn, Elizabeth Musso, Jana Glogowski, Maarten van Beek, K Nair, Joonghak Lee, Sameer Tahir, Robert Allen, Volker Jacobs, Bilal Laouah, Florent Maire, Oliver Kasper, Jaap Veldkamp, Patrick Coolen, Jeff Wellstead, Jean-Francois (Jeff) BOUBANGA MIGOLET, Dan George, Shujaat Ahmad, Alexandra Nawrat, People Edge Consulting Ltd., Andrew Spence, Roshaunda Green, MBA, CDSP, Phenom Certified Recruiter ?, Austin Brockert, MBA, Dan Riley, Sanja Licina, Ph.D., Anna A. Tavis, PhD, Stela Lupushor, Jeremy Shapiro, David Simmonds FCIPD, Catriona Lindsay, Aravind Warrier, Michael Arena, Greg Pryor, Isabella Cheshire, Amardeep Singh, MBA, Aline Costa, Anis Alexandros El Namparaoui, Adam Treitler, Helder Figueiredo, Sebastian Knepper, Sebastian Kolberg, Lewis Garrad, Kerry Ghize, Preetha Ghatak Mukharjee, Jacob Nielsen, Pete Jaworski, Søren Kold, Prabhakar Pandey, Avani Solanki Prabhakar, Ian Grant FCIPD, Erik Samdahl, Max Blumberg, Sergey Puchka, Romy Hobson, Bettina Dietsche, Hernan Chiosso, CSPO, SPHR ?, Paola Alfaro Alpízar, Sergio Garcia Mora, Hanadi El Sayyed, David van Lochem, Maria Nolazco Masson, David McLean, Clara W Estanqueiro, Shonna Waters, PhD, Kevin Martin, Kathi Enderes, Serena H. Huang, Ph.D., Smadar Tadmor, Tobias W. Goers ツ, Dr. Denise Turley AI.Impact.Equity, Stella Ioannidou, Apeksha Awaji, Evan Franz, MBA, L N Divya Mudundi, Ross Sparkman, Salman Farooq, Megan Reitz, Todd Tauber, Heather Muir, AJ Herrmann, Priyanka Mehrotra, Oliver Auty, Priya Subrahmanyan, Naotake Momiyama, Bill Banham, Matthew Yerbury, Prachi Agasti, Robin Haag, Fabian Stokes, MBA, SWP, Monika Manova, Barry Swales, Dean Carter, Ian OKeefe, Ying Li, Alexandre Monin, Mike Zarrilli, Natasha Fearon, Pedro Pereira, David Balls (FCIPD), Naomi Verghese, Geetanjali Gamel, Frankie Close, Warren Howlett, Stephanie Murphy, Ph.D., John Gunawan, Jesse Clark, MBA, Caitie Jacobson Mikulis, Meghan M. Biro, Dan Trares, Kouros Behzad, Kathleen Kruse, Nick Lynn, Mariana Allain Carrasqueira, Marina Pearce, PhD, Dawn Klinghoffer, Raquel Mitie Harano, Delia Majarín, Deborah M. Weiss, Courtney McMahon, Nirit Peled-Muntz, Hanne Hoberg, Adam McKinnon, PhD., Don Dela Paz, Matt Elk, Sophia Houziaux, Danielle Bushen, Nabil Dewsi, Sai Bon Timmy Cheung 張世邦, Dolapo (Dolly) Oyenuga Agnes Garaba, Wouter Minten, Olly Britnell, Nick Hudgell, Roxanne Laczo, PhD, Claire Masson, Daisy Grewal, Ph.D., Laura Cole, Brian Elliott, Erin Eatough, PhD Henrik Håkansson Gabe Horwitz Russell Klosk (智能虎)
The final note this month is a sad one - rest in peace Diogo Jota and André Silva.
ABOUT THE AUTHOR
David Green ?? is a globally respected author, speaker, conference chair, and executive consultant on people analytics, data-driven HR and the future of work. As Managing Partner and Executive Director at Insight222, he has overall responsibility for the delivery of the Insight222 People Analytics Program, which supports the advancement of people analytics in over 100 global organisations. Prior to co-founding Insight222, David accumulated over 20 years experience in the human resources and people analytics fields, including as Global Director of People Analytics Solutions at IBM. As such, David has extensive experience in helping organisations increase value, impact and focus from the wise and ethical use of people analytics. David also hosts the Digital HR Leaders Podcast and is an instructor for Insight222's myHRfuture Academy. His book, co-authored with Jonathan Ferrar, Excellence in People Analytics: How to use Workforce Data to Create Business Value was published in the summer of 2021.
MEET ME AT THESE EVENTS
I'll be speaking about people analytics, the future of work, and data driven HR at a number of upcoming events in 2025:
July 31 - August 1 - People Matters TechHR India 2025, Delhi
August 13-16 - GCHRA Africa, Accra, Ghana (I will join virtually)
September 25 - Visier Outsmart Local London, London
October 7-9 - Insight222 Global Executive Retreat, Atlanta (exclusive to the people analytics leader in member companies of the Insight222 People Analytics Program®)
October 15-16 - People Analytics World, New York
October 21-22 - UNLEASH World, Paris
November 12-13 - HR Forum 2025, Oslo
More events will be added as they are confirmed.
AI Transformation
2025年07月27日
AI Transformation
员工体验平台的演进：推动 AI 转型的关键引擎Josh Bersin 公司发布新研究指出：员工体验平台（EXP）正在成为企业 AI 转型的关键基础设施。EXP 不再只是HR工具，而是推动组织学习、透明沟通和员工赋能的核心平台。研究提出五大战略：以人为本、自下而上、持续学习、透明沟通和实时优化。案例包括 Microsoft 的 HR AI 转型、ASOS 的 AI 自动化、Clifford Chance 的法律文书 AI 起草。EXP 赋能组织实现敏捷变革和AI落地。
AI 正在快速改变职场——不仅是技术，更是组织文化与工作方式的深刻变革。
人工智能（AI）的广泛应用为生产力、效率和业务增长带来了前所未有的机遇。然而，AI 转型并不仅仅意味着“部署新技术”，它实际上深刻地重塑了员工体验，影响着组织文化、团队协作方式与工作流程。
在这一转型过程中，员工体验平台（Employee Experience Platform，简称 EXP） 正逐渐从传统的 HR 工具，演进为推动企业成功实施 AI 的关键引擎。EXP 不再只是一个用于请假或查政策的门户，而是集成沟通、学习、协作、数据与自动化的智能化平台，帮助组织推动 AI 采纳、提升员工准备度，并确保 AI 真正带来业务价值。
员工体验平台的演进
EXP 的初始功能主要是处理事务性流程，如请假申请、薪资查询等。但如今，随着 AI 技术的发展，EXP 已演变为智能化的交互中心，集成以下核心功能：
跨系统的员工沟通与协作
提供关于 AI 使用和员工情绪的实时洞察
支持个性化的学习与技能建设
自动化重复任务，让员工专注于更有价值的工作
同时，得益于 AI Agent 的融入，如今的 EXP 变得更易使用，员工可通过自然语言与系统交互，实现跨系统流程操作，无需再进入多个事务性系统。
因此，EXP 不再是“可有可无”的系统，而是 企业 AI 成功转型的关键基础设施。
企业 AI 转型案例
我们调研了三家具有代表性的公司，探讨他们在 AI 转型中如何借助 EXP 实现落地与成效：
1. ASOS（线上时尚零售）
部署 Microsoft Copilot 与 Microsoft Viva 赋能多业务部门
用 AI 驱动 HR 案例处理工具，提升服务效率
通过自助服务门户精简事务流程
用自定义 AI bot 自动完成可持续认证流程
成果：员工生产力提升、参与度增强、AI 无缝落地
2. Microsoft（打造 AI 驱动的 HR 部门）
通过 Viva 学习模块开展 AI 培训
自助 HR 工具增强员工支持体验
实时分析 AI 使用情况，持续优化策略
成果：HR 效率显著提升，数千名 HR 领导参与 AI 社群
3. Clifford Chance（国际律所）
用 AI 起草法律文件，为律师提供初稿
借助 AI 语言工具跨越法律语境差异
利用 AI 管理法律知识，快速找出相关案例
成果：文书效率提升、知识共享加速、决策更精准
AI 转型的敏捷性要求
与传统变革不同，AI 推广不是一次性事件，而是一个 持续试验、迭代和适应的过程。因此，企业需具备“变革敏捷性”（Change Agility），用灵活的机制推动员工学习和组织协同。
借助 EXP 实现 AI 成功的五大战略
我们总结出五个成功企业在 AI 转型过程中普遍遵循的策略，而 EXP 是支撑这些策略实施的核心平台：
1. 以人为本与目标导向（Focus on People and Purpose）
AI 的导入需与组织使命、价值观和员工需求保持一致。EXP 可确保所有 AI 工具围绕员工体验设计，提升参与度、工作效率和福祉。
? 案例：Microsoft HR 借助 Viva Amplify 定制 AI 推广内容，让 HR 团队及时获取战略沟通信息，确保 AI 项目与业务目标保持一致。
2. 采用自下而上的迭代方法（Bottom-Up, Iterative Approach）
AI 转型不能靠高层指令推动，而应依赖一线员工的反馈与试验。EXP 通过实时反馈与学习机制，让员工在实际工作中试用、迭代与优化 AI 工具。
? 案例：ASOS 借助 Viva 社区功能发起“Work Smarter”活动，员工可在平台上公开交流 AI 使用案例，形成知识共享文化。
3. 鼓励透明沟通与试验精神（Transparent Communication and Experimentation）
员工需要明确知道 AI 工具的使用场景、目的与风险，才能建立信任并积极参与。EXP 提供结构化、公开的试验机制，确保过程透明。
? 案例：Clifford Chance 在 Microsoft Viva 中嵌入 AI 工作流程，员工可以实时测试 AI 辅助起草功能，同时了解其运行逻辑。
4. 推动持续学习与技能建设（Continuous Learning and Skill-Building）
员工必须掌握 AI 基本素养，才能有效融入 AI 工具。EXP 提供基于角色定制的学习路径，支持技能升级与长期成长。
? 案例：Clifford Chance 借助 Viva Learning 培训员工 prompt 工程、AI 素养与数据分析技能，为 AI 工具的使用打下基础。
5. 实现实时度量与持续优化（Real-Time Measurement and Improvement）
与传统 IT 项目不同，AI 推广必须持续监测并快速调整策略。EXP 提供实时分析能力，帮助企业追踪员工情绪、生产力与 AI 使用情况。
? 案例：Microsoft HR 借助 Viva Insights 实时追踪 AI 使用频率、员工负荷减轻情况与情绪变化，以便动态调整 AI 战略。
HR 在 AI 转型中的新角色
在 AI 重构工作的过程中，HR 部门不再只是支持者，而是：
主导员工技能升级与再培训
协助重塑岗位定义与工作流程
在 HR、IT 与业务之间架起 AI 战略桥梁
落实负责任 AI 政策，确保 AI 应用符合伦理与企业文化
HR 将在未来的 AI 时代中扮演 “战略引导者 + 管理变革催化者” 的核心角色。
行动建议与未来展望
企业若想在 AI 转型中取得成功，应当：
✅ 采用“变革敏捷”思维，持续学习、实时迭代
✅ 建立 AI 驱动的员工体验平台，支持流程与文化融合
✅ 打破 HR、IT、业务之间的壁垒，实现跨部门协同
✅ 实施实时度量机制，根据反馈不断优化 AI 战略
EXP 已成为企业迈入 AI 未来的基础设施。
AI 将持续重塑职场，但决定 AI 成败的关键并非技术本身，而是组织是否能让员工真正拥抱 AI、用好 AI。
EXP 不再只是一个 HR 工具，而是打造学习型组织、推动信任建设和灵活变革的“中枢神经系统”。企业若想在 AI 驱动的时代中保持竞争力，就必须把员工体验放在战略核心位置。
作者：Kathi Enderes | 全球研究与行业分析高级副总裁 | Josh Bersin Company
AI Transformation
2025年07月19日
AI Transformation
How To Make Productivity Soar: Four Stages of AI TransformationWe’ve been doing a lot of advisory work on skills and job design and now that AI tools have arrived, we’re reinventing work faster than ever. So let me give you some thoughts on this process, and you can also learn more from my recent podcast.
As you know, there are many types of AI business tools: Copilots, Assistants, Agents, Talent Intelligence Systems, and embedded applications. Each of these products are built on an AI-first foundation and they layer on domain expertise, use-case analysis, and iterative design to build smarter and smarter systems.
Self-driving cars started as voice assistants, automatic braking, and lane warnings. Now they keep you in the lane and slow your car when the speed limit changes. And soon enough they’ll be driving for us, so we can sit in the back seat and read a book.
Our HR Assistant Galileo started as a research and problem solving tool, and it’s rapidly becoming an AI coach, benchmarking tool, recruiting, and change management system. So all these tools go from simple use-cases to deeper applications and autonomy over time.
As the tools get smarter and more domain focused we are going to have to rethink our jobs and business processes. And unlike ERP, where we essentially trained people to “adopt” the system, now a lot of the groundbreaking applications come from the bottom up. Individuals will discover capabilities for AI and then apply them in increasingly innovative ways.
And over time, as they get smarter, our jobs move more to “supervisors” and “trainers” of AI, not just consumers. For example if our self-driving car took a bumpy route, we may “retrain it” to take a longer but smoother road.
As I discuss in the podcast, I believe there are four stages of adoption today. And we’re in the middle of doing all four at the same time.
Level 1: Make existing work easier. (Same job, better tools.)
This is where we click on the Microsoft Copilot or Zoom or Teams and the system analyzes a meeting, summarizes emails, or writes a document with our help. We do our jobs the same way we did before, but we now have a “super-productivity” tool to make it easier. These “add-on” use cases are emerging everywhere, and they already feel like a commodity.
In most cases employees see 10-15% or more improvements here, but life isn’t that much different. And sometimes the tool slows us down (Copilot doesn’t create slides well at all yet) and may actually get in the way. But we can expect this mode to continue and most of us figure this out on our own.
Level 2: Major steps eliminated, but the job is the same. (Same job, tools eliminate work.)
At level 2 we automated a lot. Software engineers now use copilots to develop 70% of their code, so they’re spending more time testing and prompting the AI. Their individual coding skills may atrophy, but they can now work on more architectural issues.
The “job” of software engineer may still be the same, but the output is far greater. So we’re making the same pay, doing the same work, but using highly automated tools.
This includes scenarios like chip designers, software engineers, supermarket checkout clerks, nurse scheduling jobs, and even recruiting assistants. Paradox customers, for example, virtually eliminate “scheduling assistants” for recruiting.
At this level companies can see 50-75% productivity improvement, and free time to focus on quality management, customer service, and ongoing improvements to the tools.
Level 3: Re-engineered work, partnered with agents. (New job, redesigned process, agents automate work.)
At level 3 we go further: we re-engineer the process and the work. Imagine how McDonald’s replaced its counter workers with a kiosk, eliminating the “may I take you order please?” role.
This took some major design effort but resulted in a whole new set of roles, workflow, and management structure in the restaurants. The “cost per burger” went down, and the customer experience is almost as good (not quite).
Here we need to be careful because sometimes the “self-service, AI-enabled” experience doesn’t work. A good example is the supermarket self-checkout. It rarely works well and usually takes longer than standing in line. But it will get better, and the resulting experience is faster throughput, more data (the self-service agent might offer you a discount since it knows your buying history), and far superior employee roles.
In level 3 the employees are still involved, and we are more or less “working with the machine,” aiding and supporting the process.
Level 4: Autonomous intelligent agents, people training and managing the AI. (New job, redesigned process, people “manage” the agents.)
At level 4 we go even further. Imagine an AI recruiter (Paradox does this) that could email a hiring manager and his team, gain feedback and requirements on a job and role, consolidate input, and create a total description. This Agent could then review this job against the company culture and pay policies, compare the job against similar jobs in the external market, and tweak the level, job title, and description to be competitive. And then it could start sourcing, and give the hiring manager and human recruiter a set of candidates ranked by various criteria.
That process, which takes dozens of steps for a recruiter, could be fully automated and vastly improved. The Agent could even look at prior hires and get even smarter about who to source based on the success of other candidates.
Now the human job is to “train” and “monitor” and “manage” this AI Agent, who has effectively become a digital employee. (Note: Salesforce is doing a terrific job of building this out for sales and service.)
The Rise of the SuperWorker
Our thesis is that AI is not a “job-replacement” technology, it’s a “SuperWorker empowerment” technology. In other words, most of these scenarios result in higher value jobs, higher pay, and value creation (not cost reduction) in the business.
This is happening fast.
We’re in the middle of a big study in this area and I’ll be explaining this more in our upcoming 2025 Predictions report. The upside of all this will be new and higher paying jobs, faster response to business change, but a lot of IT, design, and data management to do. But based on our research, this is coming soon.
AI Transformation
2024年12月01日
AI Transformation
2024年的HRTech：GenAI、分析和技能技术In 2024, the field of Human Resources is experiencing a transformative shift with the integration of cutting-edge technologies such as Generative AI (GenAI), advanced analytics, and skills technology. This article by Dave Zielinski, featured on SHRM Online, delves into the evolving landscape of HR, highlighting the significant impact of these technologies on enhancing the employee experience, improving regulatory compliance, and revolutionizing talent management. Industry analysts and thought leaders share insights on the growing importance of GenAI in HR processes, the challenges of maintaining employee experience in cost-cutting scenarios, and the potential of predictive analytics in optimizing workforce planning.
接受SHRM Online采访的人力资源行业分析师、从业者和思想领袖表示，今年，人力资源职能部门将采用生成式人工智能 (GenAI)，投资于提升员工体验的技术，并采用强大的预测分析和技能技术。
人力资源领导者将转向技术，这些技术不仅可以提高法规遵从性，还可以帮助其组织做出更好、更快的人才决策并重新定义工作方式。
有远见的公司将继续投资 EX
一些分析师预测，随着高管将注意力转向降低成本和提高效率，远离包容性、公平和多样性等问题，员工体验 (EX) 将在 2024 年出现“衰退”；灵活的工作安排；和员工心理健康。员工的工作选择将减少，雇主将收回一些影响力。
不过，尽管许多组织可能会在 2024 年减少或冻结 EX 支出，但专家对此类举措的后果提出警告。
JP Gownder 是 Forrester 的副总裁兼首席分析师。他在博文中写道，根据 Forrester 研究，66% 的技术决策者表示，他们将在 2024 年增加对 EX 或人力资源技术的投资，其中许多投资将旨在提高效率，而不是 EX 结果。
但逆流而上的领导者将在 2024 年获得实实在在的好处。
“通过开发成熟的 EX 计划，您的组织可以提高生产力、降低人员流失率并提高创造力，”Gownder 写道。
其他专家认为，足智多谋的人力资源领导者会在预算紧张的情况下找到投资 EX 的方法。
管理咨询公司光辉国际 (Korn Ferry) 首席人力资源官 (CHRO) 业务的高级客户合伙人丹·卡普兰 (Dan Kaplan) 表示：“人力资源部门将被迫在低迷的市场中保持参与度，甚至在成本削减和削减的整个过程中也不例外。” “这将是一场艰难的舞蹈，但最好的人力资源领导者会找到办法做到这一点。”
光辉国际 (Korn Ferry) 专门负责人力资源问题的高级客户合伙人胡安·巴勃罗·冈萨雷斯 (Juan Pablo Gonzalez) 表示，组织对 EX 的承诺在 2024 年不会减弱，但 EX 看起来会非常不同。
“EX 的本质可能会变得更加个性化，同时也会变得不那么个性化，”冈萨雷斯说。“例如，通过使用 Microsoft Office Copilot、Workday 和 Salesforce 等大型软件平台中已有的人工智能功能，雇主和员工已经改变了他们的 EX。正在发生的情况是，员工与技术的互动越来越多地取代了与人的互动，但与技术的互动已经变得更加适合员工的特定需求和情况。”
亚特兰大人力资源咨询公司 IA 的创始人兼管理负责人 Mark Stelzner 表示，虽然由于组织面临控制盈利的挑战，预算将在 2024 年重新分配，但良好的 EX 相关技术投资将继续为公司带来红利。
“我认为投资 EX 实际上会提高效率并降低成本，”Stelzner 说。“到 2024 年，我们可能会看到组织不断转向‘流程主导、技术支持’的理念。端到端流程的优化通常会导致诸如消除现有技术债务以及统一工具和技术等决策，以减少员工的困惑并优化个性化，从而减少集成良好的接触点。”
Gartner 专门研究人力资源技术的副总裁分析师 John Kostoulas 表示，做出更具战略性的采购决策和改善现有技术生态系统的治理是改善 EX 的两个关键。Gartner 最近的研究发现，60% 的人力资源领导者认为他们当前的技术阻碍而不是改善了员工体验。
Nucleus Research 专门负责员工体验的研究经理 Evelyn McMullen 表示，仅仅为了提高效率而不是 EX 结果而设计的技术投资可能被证明是短视的。她指出，改进的 EX 通常会带来更好的绩效并降低与营业额相关的成本。
麦克马伦说：“考虑到劳动力市场和求职者优势的不断波动，减少 EX 预算的风险尤其大。” “当控制权不可避免地回到求职者手中时，保留 EX 投资的组织将能够更好地捕获和留住最优秀的人才。”
GenAI 从实验转向加速采用
到 2024 年，通过更多地采用该技术，人力资源职能将从涉足 GenAI 转向更深的领域。
随着领导者制定更严格的 GenAI 治理计划以及使用该技术的风险开始降低，人力资源和招聘部门将越来越多地使用其 HRIS 平台中已有的 GenAI 工具来编写职位描述和面试指南、创建敬业度调查、开发培训课程、分析数据，并制定政策。
世界大型企业联合会 2023 年底对首席人力资源官的调查发现，61% 的首席人力资源官计划在 2024 年投资人工智能以简化人力资源流程。
分析师 Eser Rizaoglu 表示：“许多人力资源领导者的 GenAI 之旅仍处于起步阶段，但要么通过现有的人力资源技术提供商获得 GenAI 功能，要么到 2024 年中期购买新的 GenAI 工具。” Gartner 的人力资源研究和咨询实践。
Rizaoglu 表示，许多人力资源技术供应商仍在努力弄清楚如何充分利用 GenAI 的功能，同时平衡保护数据、确保有效治理和考虑道德因素的需求。他表示：“在实现这种精细的平衡之前，GenAI 能力在人力资源领域的大规模扩散将面临挑战。”
Stelzner 表示，虽然去年 GenAI 带来了兴奋并刺激了人力资源领域的实验，但“冷酷的现实”是许多组织仍然没有准备好全力投入。
“到 2024 年，GenAI 采用率的任何增长都可能是渐进式的，包括更好地利用聊天机器人、增强员工沟通的个性化、更加关注人才招聘领域的可能性以及系统升级和实施测试的自动化。”他说。
埃森哲进行的研究发现，GenAI 有潜力改变组织 40% 的工作时间。“这并不意味着 40% 的工作岗位将会消失，而是反映了工作方式的转变，”负责该公司人力资源转型和交付实践的埃森哲董事总经理迈克尔·本亚明 (Michael Benyamin) 表示。“技术将取代一些任务，让员工在工作中变得更有生产力、更具创造力和效率。人工智能是人类能力的倍增器。”
随着 GenAI 开始增强或转变更多的工作角色，人力资源和学习领导者将需要创建敏捷的学习计划，以重新培训员工使用快速发展的 GenAI 工具的技能。许多工人几乎没有接受过如何使用该技术的培训。
Salesforce 于 2023 年进行的一项调查发现，62% 的员工表示他们缺乏有效、安全使用 GenAI 的技能。波士顿咨询集团的另一项研究发现，尽管该技术有望从根本上重塑他们的工作方式，但只有 14% 的一线员工接受过与人工智能相关的技能提升。
Benyamin 表示，随着 GenAI 在工作场所变得越来越普遍，人力资源部门必须帮助制定负责任和道德的人工智能使用政策，并制定培训计划来解决偏见、歧视、数据保护和适当数据使用等问题。
更加关注变革管理，提高新人力资源软件的采用率
专家认为，许多人力资源领导者将寻求通过采用变革管理策略来提高 2024 年技术投资的回报，例如确保员工使用新采用的技术解决方案。
人力资源面临的一项持续挑战是管理云技术供应商源源不断的更新和新功能，导致许多人力资源软件即服务 (SaaS) 许可证闲置。位于加利福尼亚州帕洛阿尔托的 SaaS 智能平台 Productiv 于 2023 年进行的一项研究发现，组织中 53% 的 SaaS 许可证总体未使用。
位于阿拉巴马州亨茨维尔的人力资源咨询和研究公司 Lighthouse Research 的首席研究官本·尤班克斯 (Ben Eubanks) 表示，许多组织低估了如何确保员工在新的人力资源平台和应用程序推出后定期使用它们。
“人力资源和人才技术不是‘按下开关就可以开始’类型的解决方案，”尤班克斯说。“但许多雇主仍然这么认为，并低估了采用该技术所需的行为改变。”
重新思考员工敬业度调查
更多的人力资源和执行团队将重新考虑如何创建敬业度调查以及分发调查的频率，以减少“调查疲劳”。
ServiceNow 高级副总裁兼员工工作流程产品总经理 Gretchen Alarcon 表示，随着组织继续努力寻找“秘方”，让员工在 2024 年更频繁地重返办公室，人力资源领导者将需要使用更有意义的方法测量工具。
她说：“组织将利用员工的声音调查和反馈来分析在办公室花费的时间与员工情绪和生产力的关系。” “这将使领导者能够根据数据而不是假设做出决策，这样他们就可以根据员工的需求、行为和提高生产力的因素来调整重返办公室 [RTO] 策略。”
从改进的技能技术中获益
转向基于技能的招聘和晋升策略的人力资源和招聘领导者将受益于技术的发展，例如使用人工智能和机器学习自动创建、组织和更新员工技能数据库的技能本体，从而显着减少体力工作量人力资源部要求。
下一代本体论和其他新兴技能技术可以使人力资源领导者更轻松地识别组织中的技能差距，然后相应地调整招聘或学习和发展计划。虽然市场上没有真正的端到端技能技术解决方案，但许多人力资源领导者正在将人工智能驱动的点解决方案结合在一起，以创建有效的技能数据库和评估工具。
“到 2024 年，随着组织采用技能智能技术，他们将开始认识到，这不是拥有最大的技能数据库，而是一个不断更新的丰富且互联的技能数据库，”Alarcon 说。她补充说，此类数据库使公司能够了解人才缺口是否是由于缺乏合适的人才或缺乏技能造成的，以及他们是否需要为未来培养、购买或借用人才。
预测分析工具变得更加强大
人力资源从业者和分析师认为，人力资源部门将受益于日益强大的预测分析工具，这些工具将改善劳动力规划和数据驱动的决策。
光辉国际 (Korn Ferry) 的冈萨雷斯 (Gonzalez) 表示：“凭借更大的数据集和改进的算法，人力资源部门应该能够采取一些措施，例如缓和过去几年的招聘盛衰周期。” 例如，冈萨雷斯表示，雇主不会雇佣数千名员工，然后在六个月后解雇其中一半，而是能够更好地预测在合理的时间内他们需要的员工数量和类型。他说：“然后他们可以雇用和培养一支更稳定的员工队伍，以造福所有组织利益相关者。”
Stelzner 认为，许多人力资源部门由于没有充分发挥数据分析的潜力而错失了机会。他说，如果未能投资分析人力资源数据所需的工具和技能，可能会导致洞察力缺失，并阻碍人力资源战略与更广泛的业务目标保持一致的能力。
“从历史上看，人力资源部门也一直在努力解决数据的准确性问题，”斯特尔兹纳说。“这会影响该职能部门依靠报告和数据分析来通知和支持其决策的能力。更糟糕的是，企业的其他部门已经接受过培训，预计人力资源系统会提供有问题的数据，因此在数据清理、报告和分析方面还有很多工作要做，以重新获得整个企业的可信度。”
Dave Zielinski 是 Skiwood Communications 的负责人，这是一家位于明尼阿波利斯的商业写作和编辑公司。
作者：Dave Zielinski
AI Transformation
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