AI In Human Resource Management

Everyone keeps telling HR professionals they need to start leveraging AI more. More AI! More automations! More efficiency! But no one ever seems to offer specific examples of how exactly People leaders are supposed to start incorporating AI into their everyday workflow. So here are a few examples — both free and paid — on how to incorporate #AI into your everyday #HR work streams: 🙌🏼 Free: - Need to write a company policy and FAQ? Just draft your messy thoughts (exclude your company’s name) into ChatGPT and have it draft the entire thing for you. - CEO asking for the financial ROI on a particular initiative? Have ChatGPT recommend a formula to calculate this -Have ChatGPT draft all job descriptions (it’s scarily good at these), take home assessments, and interview Qs. - Have CharGPT calculate your average number of hours spent per open req so you can more effectively calculate recruitment needs - Tell ChatGPT about a complex spreadsheet you need to create and ask for formulas and tricks to automate and otherwise improve the process so you’re not losing time manually copy and pasting - Ask ChatGPT for a list of stats on anything from the business case for DEI to the top reasons employees quit — these will come in handy when presenting proposals to your leadership team - Have it recommend an offsite agenda based on goals you’re trying to achieve + recommended location and hotels based on your offsite budget 💰Paid (ie internal AI license to protect your data): - Throw in all free form responses from your engagement survey or exit interviews and have it analyze the data for trends - Anything to do with numbers crunching: have it calculate your turnover rates, retention stats, ELTV (employee lifetime value), average cost per hire - Have it review your internal company policies for gaps in compliance with state and federal law - Share existing processes (ie recruitment, onboarding, etc), and ask it how to cut the required time by 25% via automations Obviously, you should always apply your own sound logic to AI data and lean on trusted experts to verify any info. It’s definitely not a good idea to replace your employment lawyer with AI. But AI is a great starting point to get your ideas churning, crunch numbers, and quickly analyze large volumes of data. Want more tips for how to use AI, including specific prompts to help you get started? 👉 Check out my recommended list here: https://lnkd.in/edQZfspg 👉 Free AI usage policy for your employees here: https://lnkd.in/e-F_A9hW What cool tips did I miss?

If you’re in leadership, you need to understand *how* genAI will transform your organization, and what that means for restructuring teams. Here's what we're learning: BREAKTHROUGH IN AI IDEATION OpenAI is getting ready to launch new AI models (o3 and o4-mini) that can connect concepts across different disciplines ranging from nuclear fusion to pathogen detection. (Reporting from The Information's Stephanie Palazzolo and Amir Efrati). Molecular biologist Sarah Owens used the system to design a study applying ecological techniques to pathogen detection and said doing this without AI "would have taken days." THE NEW TEAMMATE EMERGES Remember the HBS study with 776 Procter & Gamble professionals? It showed that genAI functioned as an actual teammate. Individuals using AI performed at levels comparable to traditional human teams, achieving a 37% performance improvement over solo workers without AI. Teams using AI were three times more likely to produce top-quality solutions while completing tasks 12.7% faster and producing more detailed outputs. BREAKING DOWN SILOS That study showed that AI also dissolves professional boundaries. Without AI, R&D specialists created technical solutions while Commercial specialists developed market-focused ideas. With AI, both types of specialists produced balanced solutions integrating technical and commercial perspectives. A NEW KIND OF TEAM AI users reported higher levels of excitement and enthusiasm while experiencing less anxiety and frustration. Individuals working alone with AI reported emotional experiences comparable to those in human teams. That's wild. RESTRUCTURING FOR ADVANTAGE The HBS study showed that AI reduces dominance effects in team collaboration. When genAI translates between roles, it accelerates iteration at a pace that there’s no way traditional teams could match. ++++++++++++++++++++ THREE THINGS YOU SHOULD BE DOING NOW: 1. Upskill your entire workforce: Develop a fundamental behavioral shift in how teams interact with AI across every task. This only works if everyone is doing it. (We work with enterprise to upskill at scale - more below.) 2. Experiment with new team structures: Test different AI-team combinations. Try individuals with AI for routine tasks and small teams with AI for complex challenges. Find what works best for your specific needs. 3. Redefine success metrics: Set new standards for what good work looks like with AI. Track not just productivity but also idea quality, knowledge sharing across departments, and team satisfaction—all areas where AI shows major benefits. ++++++++++++++++++++ UPSKILL YOUR ORGANIZATION: When your company is ready, we are ready to upskill your workforce at scale. Our Generative AI for Professionals course is tailored to enterprise and highly effective in driving AI adoption through a unique, proven behavioral transformation. It's pretty awesome. Check out our website or shoot me a DM.

"AI is going to take your job anyway." - a friendly and supportive commenter on one of my posts last week. Well, if I'm being honest, I'd be happy for AI to take parts of my job - I have to do some boring things. Why wouldn't I want AI to take some of that on? HR and People work is one of the most natural places for companies to incorporate automation and AI given how much of our work involves repetitive processes. If you’ve ever found yourself: - scrambling to pull together hiring docs - chasing down offboarding tasks - rewriting the same onboarding emails - or wondering why someone suddenly quit... Zapier’s People team just shared a set of templates we actually use to automate all of that. And we’ve made them available for everyone: https://lnkd.in/g-a5mtyh These aren’t generic. They were built by HR folks for HR folks: 🧠 Hiring doc automation (saves 3–5 hours per role) 👋 Offboarding workflows (saves 3–5 hours per exit) 📝 AI-generated 1:1 briefs (15–30 mins saved per meeting) 👀 Attrition risk alerts (helps avoid costly surprises) Shout out to Emily Mabie, Cecilia Garza, Danielle Meinert, and Savannah Kusmik for contributing these use cases and templates! And the best part? You don’t need to implement a new system or abandon your current ones. These plug right into tools you’re probably already using like Slack, BambooHR, and ChatGPT. These workflows could easily save an employee 10-20+ hours a month. But does that mean AI will simply replace those employees? No - it means those we can now reallocate that time towards more important work that helps us and the business do better. Things like collaborating with partners, improving processes, coaching team members, and interviewing more candidates. I view all the "AI will take your job" comments as fear mongering - I'm not worried about it. But I am excited to offload more of my work to AI so I can spend more time doing the stuff I like that actually helps me grow at work! P.S. If you want to learn more about how Zapier is using AI within our HR function, our CPO, Brandon Sammut, is leading an AMA on July 9th - I'll drop his post below so you can check it out!

AI isn't just a tool; it's becoming a teammate. A major field experiment with 776 professionals at Procter & Gamble, led by researchers from Harvard, Wharton, and Warwick, revealed something remarkable: Generative AI can replicate and even outperform human teamwork. Read the recently published paper here: In a real-world new product development challenge, professionals were assigned to one of four conditions: 1. Control Individuals without AI 2. Human Team R&D + Commercial without AI (+0.24 SD) 3. Individual + AI Working alone with GPT-4 (+0.37 SD) 4. AI-Augmented Team Human team + GPT-4 (+0.39 SD) Key findings: ⭐ Individuals with AI matched the output quality of traditional teams, with 16% less time spent. ⭐ AI helped non-experts perform like seasoned product developers. ⭐ It flattened functional silos: R&D and Commercial employees produced more balanced, cross-functional solutions. ⭐ It made work feel better: AI users reported higher excitement and energy and lower anxiety, even more so than many working in human-only teams. What does this mean for organizations? 💡 Rethink team structures. One AI-empowered individual can do the work of two and do it faster. 💡 Democratize expertise. AI is a boundary-spanning engine that reduces reliance on deep specialization. 💡 Invest in AI fluency. Prompting and AI collaboration skills are the new competitive edge. 💡 Double down on innovation. AI + team = highest chance of top-tier breakthrough ideas. This is not just productivity software. This is a redefinition of how work happens. AI is no longer the intern or the assistant. It’s showing up as a cybernetic teammate, enhancing performance, dissolving silos, and lifting morale. The future of work isn’t human vs. AI. The next step is human + AI + new ways of collaborating. Are you ready?

When a company deploys an AI transformation, everyone fixates on the technology but here’s what is even more important. It's about the people. Over the years, I've developed a simple but powerful tool to evaluate teams for AI readiness. I call it my Will-Skill Matrix for AI! It’s taking a pre-existing model and customizing it for AI deployments based on 13 years of deployment experience. This framework is copyrighted: © 2025 Sol Rashidi. All rights reserved. 𝗛𝗶𝗴𝗵 𝗦𝗸𝗶𝗹𝗹, 𝗛𝗶𝗴𝗵 𝗪𝗶𝗹𝗹: These are your champions - they have the technical capabilities and the hunger to drive AI adoption forward. 𝗛𝗶𝗴𝗵 𝗦𝗸𝗶𝗹𝗹, 𝗟𝗼𝘄 𝗪𝗶𝗹𝗹: Often your most technically brilliant people who resist change. They've mastered existing systems and see AI as either a threat or unnecessary complexity. 𝗟𝗼𝘄 𝗦𝗸𝗶𝗹𝗹, 𝗛𝗶𝗴𝗵 𝗪𝗶𝗹𝗹: Your enthusiastic learners. They may not understand neural networks, but they're eager to embrace AI-driven solutions. 𝗟𝗼𝘄 𝗦𝗸𝗶𝗹𝗹, 𝗟𝗼𝘄 𝗪𝗶𝗹𝗹: These team members neither understand AI nor want to adapt to it. They're comfortable in their current roles and see no reason to change. Here's the counterintuitive insight most leaders miss: The "Low Skill, High Will" group is your hidden treasure in AI transformation. I discovered this at one of my employers during a massive data overhaul. My most valuable contributors weren't always the data scientists with impressive credentials. Often, they were business analysts who couldn't code complex algorithms but brought boundless curiosity and deep business knowledge and a will to figure it out. Why does this matter? Because AI implementation isn't just a technical challenge - it's fundamentally a human change management project. In one particularly tough transformation, I spent months trying to convince resistant technical experts to embrace new methods. Meanwhile, I overlooked enthusiastic business teams eager to learn and adapt. The breakthrough came when I finally shifted focus. By empowering the "High Will" groups and pairing them with technical mentors, our implementation timeline was shortened by nearly 40%. This completely changed my approach to building AI teams. The most successful AI implementations don't just depend on having the best algorithms or the most data engineers. They depend on having people throughout your organization who are willing to reimagine what's possible - and who bring others along with them.

HR teams aren't slow on AI. They're rational. They're watching Workday get sued for age discrimination because their AI screening tool allegedly filtered out older workers. This isn't theoretical anymore. A year ago everyone was pushing AI-first messaging to win HR tech deals. But I kept seeing deals stall for the same reason: Many HR leaders run the same nightmare scenario in their head. Regulatory heat, potential lawsuits and headlines. They see the risk. Vendors pretend it doesn't exist. If your strategy is leading with AI features, you've got an uphill battle. We're seeing a shift in what actually closes. HR tech companies need to lead with risk mitigation. Three principles: 1. Lead with audit trails, not slogans. Workday's lawsuit made bias a material risk. Buyers now ask about NYC's law requiring bias audits before using AI in hiring. They want proof that you can track whether your tool discriminates against protected groups. If you can't produce impact-ratio reports, model cards and subpoena-ready logs, you won't clear legal or procurement. 2. No autonomous rejections. Shadow mode first. Run in parallel before go-live. Show selection rates by protected class and impact ratios before any automated decision touches candidates. Keep human-in-the-loop at the rejection line, with kill-switches and drift/impact alarms that force manual review. 3. Contractual risk transfer. If you want HR teams to trust your AI, carry part of the tail: algorithmic indemnity (within guardrails), bias-budget SLAs, third-party audits aligned to any legal requirements and explicit audit rights. When Legal asks vendor-risk questions, let the contract do the talking. TAKEAWAY: HR leaders aren't anti-AI. They're anti-risk. Winners don't sell "AI." Winners solve problems and sell evidence that survives discovery. If you're AI-first approach in sales in stalling, study NYC's law requiring bias audits for AI hiring tools. Track Colorado's AI Act slated for June 30, 2026. Seek to understand why HR leaders are hesitating when it comes to AI tools. Your pipeline depends on it.

Think AI will steal your HR Job? Ignore AI and its capabilities and you'll create a self-fulfilling prophecy. Don't fear it, learn it. Here’s how AI is changing HR and what you need to do to stay relevant. 1. AI Is Revolutionizing Recruiting 📌 What’s changing: AI-powered tools are screening resumes, scheduling interviews, and assessing candidates faster than ever. ⚠️ What it means for HR: Recruiters who rely on outdated manual processes will struggle to keep up. ✅ How to stay relevant: Learn how to use AI-driven ATS (e.g., HireVue, Paradox, Eightfold AI). Use AI to reduce bias in hiring (but don’t trust it blindly—always audit AI decisions). Focus on candidate experience—AI can automate tasks, but humans build relationships. 2. AI Is Reshaping Employee Engagement & Retention 📌 What’s changing: AI can analyze employee sentiment, predict turnover risks, and personalize engagement strategies. ⚠️ What it means for HR: If you’re still guessing why employees leave, you’re behind. ✅ How to stay relevant: Use AI-powered surveys (e.g., Peakon, Culture Amp) to track engagement in real-time. Leverage AI to identify burnout risks before they become resignations. Balance AI insights with human connection—people don’t want to be managed by algorithms. 3. AI Is Streamlining HR Operations 📌 What’s changing: AI is automating HR paperwork, compliance tracking, and benefits administration. ⚠️ What it means for HR: If you’re spending hours on admin work, AI can do it faster. ✅ How to stay relevant: Learn AI-powered HRIS tools (e.g., Workday AI, BambooHR, UKG). Automate onboarding workflows to free up time for strategic HR. Shift from HR admin to HR strategy—let AI handle the paperwork. 4. AI Is Changing Learning & Development 📌 What’s changing: AI is personalizing training, recommending career paths, and predicting skill gaps. ⚠️ What it means for HR: Generic, one-size-fits-all training is dead. ✅ How to stay relevant: Explore AI-driven LMS platforms (e.g., Coursera for Business, LinkedIn Learning). Use AI to create tailored career development plans for employees. Focus on coaching and leadership development—AI can teach skills, but humans mentor. 5. AI Is Transforming HR Analytics 📌 What’s changing: AI can predict workforce trends, analyze DEI progress, and optimize workforce planning. ⚠️ What it means for HR: If you’re only looking at past HR data, you’re missing out on AI’s ability to forecast trends. ✅ How to stay relevant: Learn AI-powered HR analytics tools (e.g., Visier, ChartHop). Use predictive analytics to forecast turnover, pay gaps, and hiring needs. Partner with finance and operations—data-driven HR pros will lead the future. The best HR pros won’t fear AI, they’ll learn how to use it. Agree or disagree? ⬇️ ♻️ Repost to inspire change in your network. ➕ Follow Ricardo Cuellar for more content like this.

75% faster recruitment and 70,000 annual hours saved at Unilever—this isn't just efficiency, it's reinventing what HR teams can accomplish with AI. At AI ALPI, we've analyzed how leading enterprises are using generative AI in HR, and the results are transformative. Beyond the 40% reduction in time-to-hire, we're seeing something deeper: the evolution of HR from cost center to strategic powerhouse. → Talent acquisition is being revolutionized by tools like Findem and hireEZ that look beyond resumes, analyzing 50+ data dimensions to find perfect-fit candidates before they even start looking. → Employee retention is becoming predictive, not reactive. Visier Inc. and PeakOn are detecting flight risks 6-9 months in advance by spotting subtle patterns in everything from meeting attendance to communication styles. ↳ SAP's implementation reduced voluntary turnover in critical engineering roles by 19% through targeted interventions. → Onboarding is finally becoming personalized with platforms like Talentech Benelux and BambooHR creating role-specific journeys that adapt to individual backgrounds. Did you know? Enterprise AI assistants like IBM's AskHR now handle 1.5 million employee conversations annually, resolving 68% of inquiries without human escalation. The most fascinating shift? HR tools are moving from general platforms to vertical specialists. Our analysis shows 78% of new HR tech solutions offer modular integrations rather than trying to be all-in-one solutions. This 2-flip PDF guide breaks down clear use cases for each HR function with 2 specialized companies marked for each area—from ServiceNow and Zendesk for employee support to PayAnalytics by beqom and Syndio for compensation equity analysis. 🔥 Want more breakdowns like this? Follow along for insights on: → Getting started with AI in HR teams → Scaling AI adoption across HR functions → Building AI competency in HR departments → Taking HR AI platforms to enterprise market → Developing HR AI products that solve real problems #AIHR #AI #HRtech #GenAI #FutureofWork #HR

I’m so curious about how people are using AI tools in their day-to-day work within the People/HR space. Selfishly, I’d love to see more LinkedIn posts in my feed with practical tips -- the small ways people use tools like ChatGPT, NotebookLM or Perplexity (or others). The little hacks or useful prompts can be just as valuable as the new products that seem to be launching every day. There’s so much to learn! I find myself asking almost everyone that I run into to share a recent prompt they used that surprised them with what came back. One tip I’d like to share comes from Jessie Lloyd Roberts, PHR, my teammate on the People Team here at Nextdoor. Like many teams, we use personality assessments to help with team development (we use SDI from Core Strengths), and Jessie took it a step further by feeding our team’s profiles into a Google NotebookLM. This turned the AI into an informed partner that offers insights on how we can collaborate better. After a recent offsite where we reviewed our profiles, we uploaded those notes to the AI as well. Now, we have an AI partner—our own AI HRBP—ready to offer tips on working together. For example, I can prompt it with, “I need to have a direct conversation about a challenging issue that's come up. What are 2-3 things I should consider with my approach to the discussion?” or "I really want to celebrate this person, what are some ideas that takes their profile into account in how they like to be recognized?" As a people manager, it's been a really useful tool for me to quickly remember the different styles on the team and what to look out for....

A lot of companies think they’re “safe” from AI compliance risks simply because they haven’t formally adopted AI. But that’s a dangerous assumption—and it’s already backfiring for some organizations. Here’s what’s really happening— Employees are quietly using ChatGPT, Claude, Gemini, and other tools to summarize customer data, rewrite client emails, or draft policy documents. In some cases, they’re even uploading sensitive files or legal content to get a “better” response. The organization may not have visibility into any of it. This is what’s called Shadow AI—unauthorized or unsanctioned use of AI tools by employees. Now, here’s what a #GRC professional needs to do about it: 1. Start with Discovery: Use internal surveys, browser activity logs (if available), or device-level monitoring to identify which teams are already using AI tools and for what purposes. No blame—just visibility. 2. Risk Categorization: Document the type of data being processed and match it to its sensitivity. Are they uploading PII? Legal content? Proprietary product info? If so, flag it. 3. Policy Design or Update: Draft an internal AI Use Policy. It doesn’t need to ban tools outright—but it should define: • What tools are approved • What types of data are prohibited • What employees need to do to request new tools 4. Communicate and Train: Employees need to understand not just what they can’t do, but why. Use plain examples to show how uploading files to a public AI model could violate privacy law, leak IP, or introduce bias into decisions. 5. Monitor and Adjust: Once you’ve rolled out your first version of the policy, revisit it every 60–90 days. This field is moving fast—and so should your governance. This can happen anywhere: in education, real estate, logistics, fintech, or nonprofits. You don’t need a team of AI engineers to start building good governance. You just need visibility, structure, and accountability. Let’s stop thinking of AI risk as something “only tech companies” deal with. Shadow AI is already in your workplace—you just haven’t looked yet.