Digital Transformation in Workplaces

Imagine you're the CFO of a global company and someone pitches you a recruitment automation solution that will do the work of 400 recruiters and save you $30M per year. What would you do? When I was at LinkedIn's Talent Connect in October, I attended a workshop with John Vlastelica in which he shared that a global company had decided to implement a recruiting automation solution that would allow them to save $30M in costs by eliminating 400 recruiter positions. They also reduced the time to hire from 11 days down to 3. He shared that another company had used recruitment automation software to hire 300,000 workers with minimal human involvement - people only came into the process after background checks had been performed. They also maintained candidate quality and candidate experience while increasing the speed of hire. These kinds of case studies should not surprise anyone, although it is sobering to anyone in talent acquisition - the rapid advancement of AI and automation in recruiting is both exciting and concerning. On the one hand, the potential for efficiency gains, cost savings, and improved candidate experience is huge and undeniable, as these examples demonstrate. On the other hand, we must also be mindful of the human impact - thousands of recruiters are seeing their roles transformed or eliminated. As talent acquisition professionals, it's important to be thinking about how to adapt and provide value in this changing landscape. Some key questions to consider: -How can we upskill and position ourselves to work alongside AI rather than be replaced by it? -What are the uniquely human elements of recruiting that AI can't replicate, and how do we double down on those? -How might our roles evolve to focus more on passive talent sourcing, talent intelligence/advisory, strategic workforce planning, employer branding, candidate engagement, and employee experience? For companies considering or implementing recruitment automation, I believe it should be a thoughtful, strategic decision - not just a blind cost-cutting measure. Here are some key considerations: -What is the optimal mix of human and automated touchpoints to balance efficiency and candidate experience? -How will the balance of AI and human involvement vary based on the labor market dynamics for each role? Roles with talent scarcity may require more human touch to attract and engage candidates, while high-volume roles with ample supply lend themselves to greater automation. -How will we redeploy or reskill displaced recruiters? -How do we maintain our employer brand and human touch with increased automation? The future of recruiting is undoubtedly both human and machine - but the mix is up to each company and may vary by role/department. I'm curious to hear your thoughts - have you been impacted by AI/automation? How are you and/or your company preparing for the intersection of AI/automation and recruiting? #AI #Recruiting #FutureOfWork

In the early days of Gem, our mighty recruiting team of 1 was drowning—30+ open reqs, hundreds of candidates lost in spreadsheets, three hiring managers pitching the same person. Until our Head of People said, "What if we treated talent like customers?" Here's exactly how we rebuilt our talent strategy: BACKGROUND: We were scaling fast. Talent data lived everywhere: personal inboxes, random spreadsheets, forgotten Slack threads. The breaking point: we lost a staff engineer to our competitor. - Candidate had expressed interest 8 months earlier - Their info was buried in an ex contract recruiter's inbox - By the time we found it, they'd already signed elsewhere Then came the embarrassment: Three different people reached out to the same eng leader candidate. Different messages. Two different comp ranges. The candidate forwarded all three emails back: "You might want to get aligned internally first." That's when we realized: most talent pools aren't pools—they're graveyards where good candidates go to be forgotten. THE SHIFT: Initially, I thought better spreadsheets would fix it. Classic founder mistake :) Our Head of People pushed back: "We spend millions on CRM for sales. Why are we tracking our second-most-important pipeline in Google Sheets?" If candidates are future employees, why weren't we treating them like future customers? We had just launched shared projects in Gem, so here’s the system we built: —— 1. Individual Pools (specific roles): One pool per req. A/B test outreach. Track "silver medalists." Share with hiring managers. 2. Team-Wide Pools (evergreen roles): Frontend. Backend. Data Science. ML. One curator per pool. Clear naming: "TP_Frontend_Senior" 3. Engagement Cadence: Monthly: Blog posts, company wins 1-2x Quarterly: In-person happy hours & meetups Annual: "Where are you now?" check-ins 4. CRM Layer: Filter by location, experience, diversity metrics Search all pools simultaneously Track every interaction —— ↳ Now, what did this actually accomplish? - Time-to-fill dropped significantly. - Response rates improved dramatically. - Duplicate outreach vanished. And here’s how you REALLY knew we were on to something: Candidates we engaged with started reaching out to us first. Not for jobs. Just to stay connected. To refer friends. We'd built a community, not a database. Key lessons: Talent pools without engagement are expensive graveyards. Build relationships before you need them. Treat candidates like customers, not inventory. P.S. This system became what Gem is today. If your team's still losing candidates in spreadsheets, let's talk.

The talk about AI replacing recruiters is everywhere. But what if we're asking the wrong question? The real opportunity isn't about replacement, it's about empowerment. For a recent client, we automated a large part of the recruitment process: sourcing, screening, and interview scheduling. This freed up a third of our recruiters' time each week. So, what did we do with that time? We reinvested it by upskilling our recruiters to handle not one, but two rounds of interviews that used to be a hiring manager's responsibility. One of those interviews is a technical assessment, where our recruiter is still augmented by AI to guide the process. The results speak for themselves: → Hiring managers are now hands-off until the final interview. They can focus on what truly matters: a candidate’s culture, long-term career fit, and company context. This gives them back an estimated 20–80 hours a year to focus on their actual job. → Our recruiters are more in control and closing candidates faster. They don't have to navigate a hiring manager’s calendar to keep the process moving. → The early data shows a better experience for everyone, from recruiters to hiring managers to candidates. The above didn’t happen overnight. It required a thoughtful and intentional approach to training, hiring manager shadowing, and change management. This is just one example, but it’s a powerful one.

🌍 UNESCO’s Pillars Framework for Digital Transformation in Education offers a roadmap for leaders, educators, and tech partners to work together and bridge the digital divide. This framework is about more than just tech—it’s about supporting communities and keeping education a public good. 💡 When implementing EdTech, policymakers should pay special attention to these critical aspects to ensure that technology meaningfully enhances education without introducing unintended issues:  🚸1. Equity and Access Policymakers need to prioritize closing the digital divide by providing affordable internet, reliable devices, and offline options where connectivity is limited. Without equitable access, EdTech can worsen existing educational inequalities.  💻2. Data Privacy and Security Implementing strong data privacy laws and secure platforms is essential to build trust. Policymakers must ensure compliance with data protection standards and implement safeguards against data breaches, especially in systems that involve sensitive information.  🚌3. Pedagogical Alignment and Quality of Content Digital tools and content should be high-quality, curriculum-aligned, and support real learning needs. Policymakers should involve educators in selecting and shaping EdTech tools that align with proven pedagogical practices.  🌍4. Sustainable Funding and Cost Management To avoid financial strain, policymakers should develop sustainable, long-term funding models and evaluate the total cost of ownership, including infrastructure, updates, and training. Balancing costs with impact is key to sustaining EdTech programs.  🦺5. Capacity Building and Professional Development Training is essential for teachers to integrate EdTech into their teaching practices confidently. Policymakers need to provide robust, ongoing professional development and peer-support systems, so educators feel empowered rather than overwhelmed by new tools. 👓 6. Monitoring, Evaluation, and Continuous Improvement Policymakers should establish monitoring and evaluation processes to track progress and understand what works. This includes using data to refine strategies, ensure goals are met, and avoid wasted resources on ineffective solutions. 🧑🚒 7. Cultural and Social Adaptation Cultural sensitivity is crucial, especially in communities less familiar with digital learning. Policymakers should promote a growth mindset and address resistance through community engagement and awareness campaigns that highlight the educational value of EdTech. 🥸 8. Environmental Sustainability Policymakers should integrate green practices, like using energy-efficient devices and recycling programs, to reduce EdTech’s carbon footprint. Sustainable practices can also help keep costs manageable over time. 🔥Download: UNESCO. (2024). Six pillars for the digital transformation of education. UNESCO. https://lnkd.in/eYgr922n  #DigitalTransformation #EducationInnovation #GlobalEducation

Legacy systems are holding HR leaders back. 61% of HR leaders cite outdated tech as a barrier to business goals (McKinsey). And tools like Workday and SAP SuccessFactors, that were once revolutionary, now face challenges like inefficiency, poor integration, and outdated user experiences. The time for transformation is now. 2025 offers HR Directors the chance to reimagine their tech strategies: > AI & Automation: Automate tasks like payroll and onboarding, allowing HR teams to focus on strategic initiatives. > Integrated Platforms: Cloud-based systems streamline operations, improving efficiency by 20% and cutting costs by 15% (Forbes). > Enhanced Employee Experience: Personalised tools and feedback systems boost engagement and retention. > Data-Driven Insights: Advanced analytics provide actionable insights into workforce trends and decision-making. 4 key considerations to make when evaluating HR Tech: 1) Focus on Scalability: Choose solutions that integrate well and grow with your organisation. 2) Embrace Automation: Free up time for strategic HR work. 3) Prioritise Employee Experience: Invest in tools that enhance learning, wellbeing, and communication. 4) Leverage Analytics: Use data to drive smarter talent and business decisions. 2025 is the time for HR leaders to modernise their tech infrastructure. Outdated systems no longer meet the demands of a dynamic, data-driven workforce. By embracing advancements in technology, HR departments can deliver greater efficiency, employee satisfaction, and business outcomes. What HR tech changes are you looking to make in 2025? #FutureOfHR #HRTech #HRInnovation #FutureOfWork P.S. This is 1 of 9 trends featured in our new report, Shaping the Future of HR. Find all 9 on the TalentMapper website 🔍 (1/9)

𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝗥𝗲𝗰𝗿𝘂𝗶𝘁𝗺𝗲𝗻𝘁: 𝗧𝗵𝗲 𝗢𝗧𝗚 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 In our continuous exploration of how AI is revolutionising HR practices, today we spotlight a pioneering initiative by OTG, an airport hospitality leader. Their recent shift towards automating recruitment processes showcases a significant leap in HR innovation. 𝗖𝗮𝘀𝗲 𝗦𝘁𝘂𝗱𝘆: OTG's Automation Drive OTG has embarked on an ambitious journey to enhance their recruitment by integrating advanced AI tools. This strategic move is designed to streamline hiring, improve candidate fit, and significantly reduce the time spent on administrative recruitment tasks. 𝗞𝗲𝘆 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗕𝗼𝗼𝘀𝘁: By automating initial screening and administrative duties, OTG has cut down the hiring cycle, allowing HR professionals to focus on strategic decision-making and personal interactions. 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗼𝗳 𝗛𝗶𝗿𝗲: AI-powered tools have enabled better matching of candidates to job requirements, improving the overall quality of hires and reducing turnover. 𝗦𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆: As OTG expands its operations across various airports, AI recruitment tools scale accordingly, providing consistent and reliable support in handling large volumes of applications. 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 𝗮𝗻𝗱 𝗔𝗱𝗮𝗽𝘁𝗮𝘁𝗶𝗼𝗻𝘀: While the transition has propelled significant gains, it also posed challenges. Adapting to new technologies required shifts in workflow and a keen focus on maintaining the human touch in HR practices—critical in the hospitality industry. 𝗪𝗵𝘆 𝗜𝘁 𝗠𝗮𝘁𝘁𝗲𝗿𝘀 OTG's case provides valuable insights for HR professionals considering similar technological enhancements. It highlights the importance of choosing the right tools, customising them to fit organisational needs, and balancing tech-driven efficiency with essential human elements of recruitment. https://lnkd.in/gRTk_yxu #DrJaclynLee #HRInnovation #AIRecruitment #CaseStudy #HospitalityIndustry #HRTech

🤖 𝗔𝗜 𝗶𝗻 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: 𝗵𝘆𝗽𝗲, 𝗵𝗲𝗹𝗽 — 𝗼𝗿 𝗯𝗼𝘁𝗵? AI training tool ads pop up in my LinkedIn feed daily. eLearnings done in minutes! Content created with a finger tip! Super fast, super creative… Our Infineon Technologies internal Digital Learning Solutions team in Porto (30 ‘human’ experts!) ran a pilot using current AI tools to create training videos. Here’s what we found: ✅ AI speeds up repetitive tasks such as audio synchronization, implementation of adjustments, creation of captions and helps generate quick, standardized content. ❌ When it comes to customization, creativity, and complex topics, including compliance and data sensitive contents, the results fall short. For training videos longer than three minutes, we found that the visuals and language become repetitive and generic. 🔑 The real value? Using AI selectively. For short, “commodity” trainings: yes. It’s a true game changer! For anything with broader interactivity, depth, need for internal context and culture ‘fit’: human expertise remains key. But it’s not either or – we consult our customers on both: pros and cons of using AI and discuss suitable use cases, when designing content. 📢 I’m curious: Have you tested AI in training development? What worked for you — and what didn’t? Julia Tronsberg António Sarmento Dias Liliana Pereira Jorge Botelho #digitallearning #learningsolutions #training #elearning #ai

This post is only for HR Tech founders. If you are not a HR Tech CEO or founder, please keep scrolling... Now that it is just us. Psst... HR teams aren't adopting your tech and I can tell you why. (Hint: It's Not the Features) If your "game-changing" platform isn't getting love from HR teams, the problem probably isn't missing features. It is sooooooo much deeper. Here's what's really going on: 1. You're Adding Problems, Not Solutions HR leaders don't need another tool that makes their day harder. As Luke Eaton put it, "Tools don't solve problems… If you don’t have a solution first, tech is just another cost." Your technology should simplify workflows, not complicate them. If it doesn’t directly remove pain points, HR won't adopt. 2. You Don't Get HR’s Scorecard HR teams are evaluated on clear KPIs and OKRs—time-to-fill, retention, engagement, DEI outcomes—not how fancy your AI sounds. Gartner's Mark Whittle nails it: "The goal isn’t to maximize tech value to HR, but to maximize business value." Deloitte found that "42% of organizations said tech initiatives failed due to unrealistic business cases or lack of measurable success." If you can’t clearly tie your tech to real business outcomes, you're speaking the wrong language. 3. Your Solution is Searching for a Problem Too many products solve problems HR doesn't have. Employee Benefit News warns that often "the need simply isn’t there." If your customers are asking, "Why do I need this?"—you’ve missed the mark. Start with real, pressing HR pain points—not invented ones. 4. You’re Not Really Listening JESS VON BANK advises an "empty chair" strategy. Always keep your HR customer’s perspective central. She emphasizes, "Listening to the voice of the customer helps prioritize what problems to solve and when." You can have the best tech but if a tree falls in a forrest and no one is there to hear it... (you know how it goes) Bottom line: HR isn’t always change resistant. They’re resisting empty promises. Align your tech with actual HR realities, and you'll see adoption skyrocket. Let's talk about turning your innovative ideas into tech HR teams actually want to use. #amiright

62% see AI as recruitment's future. But only *35%* dare experiment. This gap fascinates me. AI is reshaping recruitment. It’s not about replacing recruiters—it’s about freeing them. Think about this: Recruiters spend *30%* (yes, nearly *1.5 days* each week) on admin tasks. Updating ATS, scheduling interviews, writing reports... Who enjoys that? Now, imagine if that time went back where recruiters thrived: -> Building relationships -> Connecting people with opportunities -> Creating unforgettable candidate experiences AI makes this possible. ✅ Automate repetitive tasks ✅ Streamlines processes ✅ Enhances efficiency But here’s where most teams hesitate: *How do we start?* Here’s my approach: 1. Make your team AI-aware. AI isn’t magic—it’s an assistant. If you are in the EU, AI Literacy isn't a choice; it is mandatory. Experiment, discuss its strengths, and be mindful about ethical use. 2. Analyze your processes. Break down your recruitment workflow. Which steps are repetitive? Which tasks add little value? Use an action-priority matrix: High impact, low effort = Start here. 3. Engage your stakeholders. Work with ATS suppliers and legal and compliance teams early. AI works best as part *of* your system, not sitting on top. 4. Train and adopt. Identify AI champions within your team. They’ll guide others and share best practices. Invest time—adoption isn’t instant, but transformation is worth every step. Organizations embracing AI today will lead tomorrow. Why? Because they’re empowering recruiters, not replacing them. By automizing *30%* admin work, you give your team back what matters: time, energy, and focus. Ready for AI-driven recruitment? I’m here if you need help starting. Let’s make recruitment future-proof.

43% of talent leaders say legal concerns are slowing down AI adoption in recruitment A recent poll by Resourcing Leaders UK highlights the key blockers to AI adoption in Talent Acquisition: 43% cited legal concerns 20% mentioned budget limits 19% said skills gap 18% pointed to data quality This reflects what I see every day: organisations aren’t held back by technology… they’re held back by trust, governance, and compliance. That’s why an AI in HR Risk Assessment from Eunomia HR is so powerful. It helps HR leaders: ✅ Identify hidden risks (legal, bias, data quality, shadow AI) ✅ Classify systems under the EU AI Act, GDPR/UK GDPR, ISO 42001 & NIST AI RMF ✅ Build confidence with a clear roadmap for safe adoption My point of view here is that the biggest barrier to AI adoption in HR isn’t excitement or budget, it’s the absence of structured governance. If you’d like to understand how ready your HR AI is, I’ve built a free QuickScore self-assessment you can take in 5 minutes. Comment if you want the link, or reach out for details on my in-depth HR AI Risk Assessment programme.