How AI is Transforming Workforce Development

The gap I am focused on most these days when it comes to AI at work, is the gap between employees and employers. We know that 75% of knowledge workers are using GAI on the job, saying it’s not just helping them save time to focus on more important work but also to bring more human skills to their work, like creativity. But we also know that only 39% of those workers have been trained on AI at work, as companies struggle still to come up with a point of view on AI as well as a strategy for workforce development in the age of AI. If your company is struggling on that part, one thing you can do is look to those who are leading the way. IBM and Siemens are great examples of companies who are two steps ahead of most, moving beyond the incremental early days of AI towards the real, transformative benefits. I was inspired by my conversation a few weeks ago with Nickle LaMoreaux and Brenda Discher who are not only innovating with AI at scale, but keeping people at the center of it all. Across those conversations and many others I’m having, a few key foundational steps are emerging: 1️⃣ Have a pro-human AI point of view and strategy in place. AI has the potential to build a world of work where people can bring their full skills and abilities to bear — but we need to believe in the power of our people more than the power of our tech to realize it. 2️⃣ See jobs as tasks, not titles. Once you boil down a job down into a set of tasks, it’s much easier to see where AI is coming in to change or disrupt some of those tasks and where there are uniquely human skills people will spend much more time on then before. In a world where 68% of skills are set to change by 2030, understanding where this change will hit is crucial to helping your teams stay resilient. 3️⃣ Build learning into the day to day of your company’s culture. As skills for jobs change rapidly – learning is no longer a one-off moment at the start of a career. The ability to learn, unlearn, and relearn is what sets teams apart to stay agile and resilient. 

There’s no question that AI is transforming the training landscape. From AI’s ability to tailor an employee’s learning journey based on their existing or required skills, learning preferences, and previous courses to virtual training that uses AI chatbots to answer employee questions and provide on-demand microlearning support, AI has opened up lots of developmental possibilities. While some speakers and trainers, understandably, are worried about being rendered irrelevant, here’s some context (and potentially good news) about what I’m seeing when it comes to skills-based communication and leadership training. Organizations are not seeking external training for purely knowledge-based issues, since AI can put together training on just about anything. Good information is not a differentiator. But with more technology comes more miscommunication. Employees may have instant access to information, but retention of that information and the emotional intelligence and ability to navigate high-stakes conversations—these are still deeply human skills and require real-time coaching and training to build. Skills-based trainers and coaches can make the most impact by using role play to help people practice the communication and aligned leadership skills for learning transfer to happen. The L&D initiatives that drive real change aren’t about knowledge acquisition—they’re about skill embodiment. And the best way to ensure that learning sticks? Live, immersive role-play training. A lot of trainers say they use role-play for skill development, but in reality, it’s often a surface-level exercise—scripted, predictable, and failing to replicate the real-world pressures of high-stakes communication. What True Role-Play Training Looks Like -Learners experience the tension and unpredictability of real conversations. -Scenarios are customized to specific challenges. -Participants get live coaching and feedback to adjust in the moment and get to retry critical communication. -There's psychological safety and trust for high-stakes practice—before it counts in real life. Role-play training isn’t just a nice-to-have; it’s becoming a business imperative! As AI reshapes the learning landscape, the ability to embody skills—especially in high-stakes communication—is what sets impactful training, like what we do at Step into Your Moxie, apart. The most effective L&D initiatives aren’t just about acquiring knowledge; they’re about building the confidence and competence to use it when it matters most. How are you seeing AI impact leadership and communication training in your organization or consulting practice?

𝗠𝘆 𝗔𝗜+𝗛𝗜 𝗥𝗮𝗱𝗮𝗿: 𝗧𝗵𝗶𝘀 𝗪𝗲𝗲𝗸'𝘀 𝗠𝘂𝘀𝘁-𝗥𝗲𝗮𝗱𝘀 Four key developments in AI integration and human factors this week. Links in comments. 𝗧𝗵𝗲𝗺𝗲: 𝗢𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀 𝗺𝗼𝘃𝗲 𝗳𝗿𝗼𝗺 𝗔𝗜 𝗲𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝘁𝗼 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗶𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝗽𝗿𝗼𝗴𝗿𝗮𝗺𝘀 𝗔𝗜 𝗪𝗼𝗿𝗸𝗳𝗼𝗿𝗰𝗲 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 (NVIDIA) What to Know: California launches $500M initiative to train 100,000 AI-ready workers by 2025. Gwinnett County implements the first K-16 AI curriculum in Georgia, focusing on practical development skills. Why it Matters: States compete for AI talent as tech companies expand operations. Early education programs aim to close the 60% skills gap identified in NVIDIA's workforce assessment. 𝗔𝗜 𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗶𝘁𝘆 𝗥𝗲𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 (Stanford University/Google DeepMind) What to Know: Study of 1,000 participants shows AI can replicate individual decision-making patterns with 85% accuracy using two-hour structured interviews and behavioral analysis. Why it Matters: This technique reduces AI personality modeling from months to hours, enabling practical applications in personalized AI assistants and decision support systems. JPMorganChase's 𝗔𝗜 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 What to Know: JPMorgan deployed its "LLM Suite" to 200,000 employees in Q4 2023. The bank identified the top 20% of early adopters to serve as AI implementation leaders. Why it Matters: Initial data shows a 40% reduction in routine tasks among early adopters, with the wealth management division reporting 70% faster client documentation processing. 𝗔𝗜 𝗘𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 (Salesforce) What to Know: Benioff challenges current chatbot limitations, presenting Salesforce's shift toward autonomous agents that can execute multi-step business processes without constant human prompting. Why it Matters: Early adopters report autonomous agents completing sales qualification processes in minutes versus hours while maintaining human oversight for final decisions. Bottom Line: Organizations succeeding with AI focus on measured implementation, clear metrics, and structured human oversight rather than rushing to adopt every new capability. #AIImplementation #WorkforceTransformation #BusinessAI

𝐀𝐦𝐞𝐫𝐢𝐜𝐚'𝐬 𝐀𝐈 𝐀𝐜𝐭𝐢𝐨𝐧 𝐏𝐥𝐚𝐧 released today, outlines this Administration's bold strategy for America to secure global dominance in #AI and unleash a new era of economic opportunity for American Workers. I applaud President Trump’s leadership in delivering a worker-centered AI strategy and emphasizing the instrumental role that the U.S. Department of Labor will play in advancing it. The U.S. Department of Labor believes AI represents a new frontier of opportunity for workers, but to realize its full promise, we must equip Americans with AI skills, build talent pipelines for AI infrastructure, and develop the agility in our workforce system to evolve alongside advances in AI. The “𝐄𝐦𝐩𝐨𝐰𝐞𝐫 𝐀𝐦𝐞𝐫𝐢𝐜𝐚𝐧 𝐖𝐨𝐫𝐤𝐞𝐫𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐀𝐠𝐞 𝐨𝐟 𝐀𝐈” section of the AI Action Plan includes actions for #DOL to work with relevant federal agencies to: 🟢 Prioritize AI skills development as a core objective of education and workforce funding streams, including career and technical education, apprenticeships, and other federally supported skills initiatives. 🟢 Establish the AI Workforce Research Hub to lead a sustained federal effort to evaluate AI’s impact on the labor market and the American worker, including recurring analysis, scenario planning, and actionable insights for workforce and education policy. 🟢 Study AI’s impact on the labor market through BLS data collection efforts and provide the AI Workforce Research Hub with analysis to support tracking of AI adoption, job creation, displacement, and wage effects. 🟢 Fund rapid retraining for individuals impacted by AI-related job displacement, as well as issue guidance clarifying how funds can be used to proactively upskill workers at risk of future displacement. 🟢 Pilot new approaches to meet workforce challenges created by AI, which may include areas such as rapid retraining models to respond to labor market shifts and new models to support pathways into entry level roles.   The "𝐓𝐫𝐚𝐢𝐧 𝐚 𝐒𝐤𝐢𝐥𝐥𝐞𝐝 𝐖𝐨𝐫𝐤𝐟𝐨𝐫𝐜𝐞 𝐟𝐨𝐫 𝐀𝐈 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞" section of the AI Action Plan includes actions for #DOL to work with relevant federal agencies to: 🟢 Create a national initiative identifying high-priority occupations critical to AI infrastructure. 🟢 Partner with state and local governments and workforce system stakeholders to support the creation of industry-driven training programs for priority AI infrastructure occupations. 🟢 Partner with education and workforce system stakeholders to expand early career exposure programs and pre-apprenticeship opportunities for middle and high school students in AI infrastructure occupations. 🟢 Expand Registered Apprenticeships for occupations critical to AI infrastructure.   I look forward to leading DOL's efforts, ushering in a new wave of opportunity for American Workers. Congratulations Michael Kratsios David O. Sacks Lynne Parker White House Office of Science and Technology Policy

📌 “𝗙𝗼𝗿 𝗖𝗹𝘂𝗲𝘀 𝗢𝗻 𝗔𝗜’𝘀 𝗜𝗺𝗽𝗮𝗰𝘁 𝗢𝗻 𝗝𝗼𝗯𝘀, 𝗪𝗮𝘁𝗰𝗵 𝗧𝗼𝗱𝗮𝘆’𝘀 𝗧𝗲𝗰𝗵 𝗝𝗼𝗯𝘀”   I recently connected with Joe McKendrick to share my perspective on how AI is reshaping the tech workforce. Grateful to see our conversation featured in Forbes.   Joe underscores a point we’ve been emphasizing for months: 𝗔𝗜 𝗶𝘀 𝗻𝗼𝘁 𝗮 𝗵𝗲𝗮𝗱𝗰𝗼𝘂𝗻𝘁 𝗿𝗲𝗱𝘂𝗰𝗲𝗿—𝗶𝘁’𝘀 𝗮 𝗰𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗶𝗲𝗿.   It moves the constraint from compute cycles to the Human Intent Layer, where talent, judgement, and abstraction become the new premium.   Fresh labor signals back this up: 🔹450,000+ US tech openings (CompTIA) 🔹AI-related job postings nearly doubled YoY 🔹50%+ wage premium for AI-fluency (PwC) 🔹Revenue per employee rising 3x faster in AI-driven sectors 🔹12%+ of tech job ads now reference AI—and climbing (Federal Reserve Bank of Atlanta)   As I note in the article, we’re not witnessing the end of software engineering—we’re seeing its evolution. Developers are becoming AI trainers, strategic integrators, and adaptive problem-solvers.   𝗖𝗼𝗱𝗲 𝗶𝘀 𝗮 𝗰𝗼𝗺𝗺𝗼𝗱𝗶𝘁𝘆. What matters is how well we frame problems, guide systems, and turn intelligence into outcomes.   Thank you, Joe, for the thoughtful conversation. To other leaders: where do you see this shift heading?   📖 Read the full article linked below.   #AI #FutureOfWork #TechJobs #Leadership

I've been diving into the latest AI Jobs Barometer from PwC, along with several recent articles. One thing is clear: AI is no longer just automating low-value tasks. 👉 𝐈𝐭'𝐬 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐢𝐧𝐠 𝐭𝐡𝐞 𝐯𝐚𝐥𝐮𝐞 𝐞𝐦𝐩𝐥𝐨𝐲𝐞𝐞𝐬 𝐛𝐫𝐢𝐧𝐠 𝐚𝐧𝐝 𝐫𝐞𝐬𝐡𝐚𝐩𝐢𝐧𝐠 𝐣𝐨𝐛 𝐝𝐞𝐬𝐜𝐫𝐢𝐩𝐭𝐢𝐨𝐧𝐬 𝐚𝐜𝐫𝐨𝐬𝐬 𝐢𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐞𝐬. Some numbers that really stand out: • 3x faster revenue growth per employee in industries adopting AI. • +56% salary premium for workers with AI-related skills. • Required skills are evolving 66% faster than just a year ago. • All industries, even mining and agriculture, are now adopting AI. • "Automatable" jobs are not disappearing. They are evolving into higher-value roles. • Demand for degrees is falling, while demand for fundamental, current skills continues to rise. As Ilya Sutskever said, "AI will keep getting better, and the day will come when AI will do all the things that we can do." 👉 𝐖𝐞 𝐦𝐚𝐲 𝐧𝐨𝐭 𝐤𝐧𝐨𝐰 𝐞𝐱𝐚𝐜𝐭𝐥𝐲 𝐰𝐡𝐞𝐧 𝐭𝐡𝐚𝐭 𝐝𝐚𝐲 𝐰𝐢𝐥𝐥 𝐚𝐫𝐫𝐢𝐯𝐞. 𝐁𝐮𝐭 𝐭𝐡𝐞 𝐝𝐢𝐫𝐞𝐜𝐭𝐢𝐨𝐧 𝐢𝐬 𝐚𝐥𝐫𝐞𝐚𝐝𝐲 𝐜𝐥𝐞𝐚𝐫. Here are some key reflections for business and talent leaders: • The priority is no longer automating the past. It is rethinking how value is created in the age of AI. • Organizations that build trust in AI and take a strategic approach will lead. • AI is a powerful driver of productivity. But without strong investment in skills and role redesign, it risks increasing inequality and internal tensions. • Continuous learning is now a must to stay competitive. • Core skills need to be refreshed every 12 to 18 months to remain relevant. The future of work will not be managed. It will be fought for. Professionals and companies waiting for someone to hand them a playbook will miss the moment. 👉 𝐓𝐡𝐢𝐬 𝐢𝐬 𝐧𝐨 𝐥𝐨𝐧𝐠𝐞𝐫 𝐣𝐮𝐬𝐭 𝐚𝐛𝐨𝐮𝐭 𝐬𝐭𝐫𝐚𝐭𝐞𝐠𝐲. 𝐈𝐭 𝐢𝐬 𝐚𝐛𝐨𝐮𝐭 𝐬𝐮𝐫𝐯𝐢𝐯𝐚𝐥. And AI is not going to wait. P.S. If you're interested, here’s the link to the full PwC report: 🔗 https://lnkd.in/emeTQPVA #FutureOfWork #AI #TechTrends

94% of routine HR tasks can now be automated by AI tools, yet 0% of human empathy can be replicated by algorithms. The future of HR isn't about replacement—it's about powerful augmentation. Today at People Atom , we analyzed how AI is transforming the HR landscape while highlighting why human expertise remains irreplaceable. What we discovered challenges conventional wisdom about the future of work. The AI-Human Partnership Reshaping HR → AI excels at data-heavy tasks, reducing time-to-hire by 75% for companies like Unilever while simultaneously increasing candidate diversity—proving efficiency and equity can coexist ↳ Meanwhile, culture building, conflict resolution, and ethical oversight remain firmly in human territory, with organizations that balance AI efficiency and human judgment seeing 3x better employee engagement → IBM initially reduced HR headcount through automation but ultimately increased hiring in roles requiring creativity, critical thinking and human interaction—revealing how AI creates entirely new categories of HR roles ↳ The highest-performing HR departments now spend 60% less time on administrative tasks and 40% more on strategic initiatives that drive business outcomes ⚡️ Navigating the New HR Frontier → Build AI literacy across your HR team while preserving empathy as your core competitive advantage → Create human-AI collaboration frameworks where technology handles pattern recognition while humans interpret context and nuance → Redesign HR career paths to emphasize uniquely human skills: emotional intelligence ethics, and strategic leadership → Implement AI governance structures to ensure technology amplifies rather than undermines your company values The workplace revolution is accelerating, and the organizations that thrive will be those that leverage AI not as a replacement for human intelligence, but as a catalyst for deeper human connection. At People Atom, we're building the infrastructure to power this new world of work—where technology enhances humanity rather than diminishes it. Are you ready to shape the future of HR rather than be shaped by it? Join other forward-thinking leaders on our waitlist to transform how your organization nurtures its most valuable asset: people. Love the future (but love humans more), Joe

The Future of Work: When AI Actually Knows Your People The most successful organizations will have one thing in common: Their AI systems will know their people better than their managers do. Not in a creepy way. In a powerful way. Imagine AI that knows John's presentation style improves when he gets feedback 24 hours before, not 24 minutes. AI that recognizes when teams are about to hit creative blocks and suggests interventions. AI that can predict which employees are ready for stretch assignments based on demonstrated skills, not self-reported capabilities. This isn't science fiction. It's the inevitable result of treating work and development as a single, integrated experience. The latest technical breakthroughs in AI inference are making this possible. Advanced systems can now analyze behavioral patterns, communication styles, and work interactions in real-time to build comprehensive skills profiles—not from what people say they can do, but from what they actually demonstrate while working. While most organizations separate "doing" from "learning," we at Infopro Learning, Inc are working with learning and talent development leaders to build systems where every work interaction becomes development data, and every development moment enhances work performance. The breakthrough isn't better AI tools. It's creating the integrated context that lets AI understand how your people actually work, learn, and grow. Organizations that figure this out first will have AI systems that don't just assist—they anticipate, adapt, and amplify human potential in ways that seem almost magical. The question isn't whether AI will transform your workforce. The question is: Will you give AI the context it needs to transform it intelligently? How are you preparing your organization for truly context-aware AI? #AIEvolution #WorkforceTransformation #TalentStrategy #LearningandDevelopment #FutureReady #PerformanceReadyWorkforce

The Microsoft and LinkedIn 2024 Work Trend Index Annual Report is out, and unsurprisingly, AI is rapidly transforming the global workforce. Based on a survey of 31,000 people across 31 countries, here are the highlights, and what it means for education. Key Highlights: - AI usage has more than doubled in the last 6 months, with 75% of global knowledge workers reporting using GenAI tools. - 79% of leaders agree their company needs to adopt AI to stay competitive, but 60% worry their organization lacks a plan and vision to implement it. - 78% of AI users are bringing their own AI tools to work (BYOAI), cutting across all generations. - Leaders say they would not hire someone without AI skills (66%) and would prefer a less experienced candidate with AI skills over a more experienced one without them (71%). - AI power users are experimenting frequently with AI, getting support and encouragement from leadership, and receiving tailored AI training. They are seeing significant benefits in productivity, creativity, and job satisfaction. What does it mean for education? - Experience with AI is becoming a key hiring criteria, in part due to research that shows that GenAI use can significantly decrease skill gaps. - 77% of leaders say early-in-career talent will be given greater responsibilities due to AI. This has major implications for how schools and universities prepare students for the job market. - Only 39% of people who use AI at work have received AI training from their company, and only 25% of companies plan to offer training on generative AI this year. This gap between need for training and availability is similarly playing out in schools and systems right now. - As AI reshapes work, the skills required for jobs are projected to change significantly. Educational institutions will need to adapt curricula to focus on the uniquely human skills that will be most valuable in an AI-enabled work world, such as creativity, critical thinking, and relationship building. The rapid rise of AI is transforming the workplace and the job market and the entire education ecosystem has an essential role to play in equipping students and workers with the AI skills and aptitudes that are and will be most in-demand. For the full report, visit: https://lnkd.in/eyfSRzNj AI for Education #aiforeducation #aieducation #durableskills #GenAI #AIliteracy

I recently wrote that AI is not just a technology shift – it's a work shift. So, how does that play out? First, AI changes how we do tasks. Next, it changes how we do our jobs. Then, it changes entire functions. The result? A brand new way of getting work done and thinking about growth. Step 1: AI transforms tasks: AI works with you. It helps you do what you’ve always done — just faster. A marketer drafts blog posts in minutes. A rep writes emails with higher personalization, less effort. A support leader summarizes tickets in seconds. This is where most teams are today: AI as a productivity booster. Step 2: AI transforms jobs. AI works for you. It starts delivering outcomes. A content agent spins one blog into a full campaign. A prospecting agent books qualified meetings without human touch. A customer agent handles most Tier 1 support tickets. The job itself starts to evolve. You spend less time doing — and more time creating, optimizing, and scaling. Step 3: AI transforms functions. As agents take on entire workflows, the structure of departments begins to shift: Support shifts from to proactive experience design. Marketing shifts to creative strategy. Sales shifts to high-impact closing. Role ratios change. Skillsets shift. We are not quite here but we can see the path. The result for scaling businesses? A whole new way of approaching work, structuring teams, and thinking about growth.