How AI Affects Human Labor

AI is fundamentally reshaping our workforce, but the impacts are nuanced. The latest report, “Potential Labor Market Impacts of Artificial Intelligence: An Empirical Analysis,” by The White House Council of Economic Advisers, provides critical insights for leaders that will impact everyone's future.. 📊 Key Findings: ✅ 𝐆𝐫𝐨𝐰𝐭𝐡 𝐢𝐧 𝐇𝐢𝐠𝐡-𝐂𝐨𝐦𝐩𝐥𝐞𝐱𝐢𝐭𝐲, 𝐀𝐈-𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐝 𝐑𝐨𝐥𝐞𝐬 Roles requiring advanced AI skills have increased by 30% over the last five years. Positions such as AI ethics officers and data scientists are on the rise, indicating a shift toward more complex, creative work. Occupations that integrate AI effectively are growing twice as fast as average, suggesting AI's role in complementing human skills rather than replacing them. ❌ 𝐇𝐢𝐠𝐡 𝐑𝐢𝐬𝐤 𝐨𝐟 𝐉𝐨𝐛 𝐃𝐢𝐬𝐩𝐥𝐚𝐜𝐞𝐦𝐞𝐧𝐭 𝐢𝐧 𝐋𝐨𝐰-𝐒𝐤𝐢𝐥𝐥 𝐑𝐨𝐥𝐞𝐬 40% of current jobs are at risk due to high AI exposure but low skill requirements, particularly in administrative and routine manual tasks. These jobs are declining at a rate of 2% annually. Sectors like customer service and data entry are vulnerable, raising concerns about job security and economic stability in these fields. 📍 Regional Disparities: ✅ 𝐎𝐩𝐩𝐨𝐫𝐭𝐮𝐧𝐢𝐭𝐢𝐞𝐬 𝐢𝐧 𝐓𝐞𝐜𝐡 𝐇𝐮𝐛𝐬 Tech-centric regions like Silicon Valley show a high concentration of new, AI-driven job creation, reflecting significant economic opportunities for those regions. Urban centers with strong tech clusters are emerging as key players in AI employment, driving innovation and growth. ❌ 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 𝐟𝐨𝐫 𝐑𝐮𝐫𝐚𝐥 𝐚𝐧𝐝 𝐒𝐦𝐚𝐥𝐥𝐞𝐫 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐢𝐞𝐬 Rural areas and smaller towns are facing increased risks of job losses due to AI, without comparable opportunities for new AI-driven roles. This geographic imbalance could exacerbate regional economic disparities. 👉 Here are my questions for Leaders: 1️⃣ Are we ready to leverage AI’s potential while minimizing risks? How are we preparing our teams for a future where AI enhances human capability? 2️⃣ What is our reskilling strategy? With 40% of jobs potentially vulnerable, how are we investing in upskilling our workforce to transition into growth-oriented roles? 3️⃣ How can we balance geographic and economic disparities? Are we focusing enough on regional strategies to ensure inclusive growth? As leaders, our role is to harness AI's potential to foster a resilient, inclusive, and dynamic workforce. Are we ready to lead this change and shape the future of work?

New! We analyzed a billion job postings globally, and the results may surprise you: job numbers and wages are rising. Let’s dive in. For the second year running, the 2025 Global AI Jobs Barometer from PwC shows that productivity and wages are not just rising, they’re accelerating, even in roles that are most amenable to automation. Our research spans six continents and includes data from 24 countries and territories. 💭 100% of industries are expanding their usage of AI (even industries less obviously exposed to AI such as mining and construction) 📊 Since 2022 when awareness of AI's power surged, productivity growth in industries best positioned to adopt AI has nearly quadrupled (while falling slightly in industries least exposed to AI) 3️⃣ Industries most able to use AI have 3x higher growth in revenue generated by each employee  🪙 Workers with AI skills command a 56% wage premium (up from 25% last year) ⚒️ Skills sought by employers are changing 66% faster in occupations most exposed to AI (like financial analyst) versus least exposed (like physical therapist) – up from 25% last year . AI continues to act as an amplifier of human expertise — not a replacement for it, despite what the headlines might suggest. The prime example being that job growth is occurring even in roles where "automation" is playing the biggest role (like customer service and software engineering). Job cuts and doomerism make headlines, but job creation takes longer to materialize and to be recognized. It’s the difference between weather and climate, and why we call this report a "barometer". As the shifting sands of the past two years begin to settle into clearer patterns, there’s never been a better time to dive in, get hands-on, and lead your teams through this transformation. Link to the full report below.

📌 “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

The biggest AI impacts won’t be borne out in a calculus of jobs but rather in seismic shifts in the level of expertise required to do them. In our article in Harvard Business Review, Joseph Fuller, Michael Fenlon, and I explore how AI will bend learning curves and change job requirements as a result. It’s a simple concept with profound implications. In some jobs, it doesn’t take long to get up to speed. But in a wide array of jobs, from sales to software engineering, significant gaps exist between what a newbie and an experienced incumbent know. In many jobs with steep learning curves, our analysis indicates that entry-level skills are more exposed to GenAI automation than those of higher-level roles. In these roles, representing 1 in 8 jobs, entry-level opportunity could evaporate. Conversely, about 19% of workers are in fields where GenAI is likely to take on tasks that demand technical knowledge today, thereby opening up more opportunities to those without hard skills.   Our analysis suggests that, in the next few years, the better part of 50 million jobs will be affected one way or the other. The extent of those changes will compel companies to reshape their organizational structures and rethink their talent-management strategies in profound ways. The implications will be far reaching, not only for industries but also for individuals and society. Firms that respond adroitly will be best positioned to harness GenAI’s productivity-boosting potential while mitigating the risk posed by talent shortages.   I hope you will take the time to explore this latest collaboration between the The Burning Glass Institute and the Harvard Business School Project on Managing the Future of Work. I am grateful to BGI colleagues Benjamin Francis, Erik Leiden, Nik Dawson, Harin Contractor, Gad Levanon, and Gwynn Guilford for their work on this project. https://lnkd.in/ekattaQA #ai #artificialintelligence #humanresources #careers #management #futureofwork

Lots to unpack in this article (It’s a long one) 1. AI Automates Tasks, Not Jobs: - AI and machine learning automate specific tasks rather than entire jobs. - The impact on jobs is not a direct one-to-one replacement but a transformation of job roles. 2. Productivity Gains: - AI tools can significantly increase worker productivity. For instance, automated coding tools can make software developers 30-40% more productive. - These tools shift the emphasis to higher-level awareness and management of the work, requiring human oversight. 3. Economic Impact and Job Security: - The fear of AI taking jobs is rooted in economic concerns. - While AI may reduce the need for certain tasks, it will also create new demands for tasks that cannot be automated, balancing job availability. 4. High-Level Tasks Remain Human: - Creative, strategic, and problem-solving tasks are less likely to be automated. - Human roles will evolve to focus more on these high-level tasks, which require human intuition and judgment. 5. Economic Feasibility of Automation: - The cost of automating tasks with AI is a significant factor. High implementation and maintenance costs may slow down AI adoption. - Only tasks that are both technically feasible and economically viable are likely to be automated. 6. Long-Term Job Creation: - Historical trends show that technological advancements create new industries and job roles. - AI will likely follow this pattern, disrupting some jobs while creating new opportunities. 7. Adapting to AI: - Workers are encouraged to upskill and reskill to remain relevant in the evolving job market. - Businesses need to strategically integrate AI into their operations to maximize benefits and minimize disruptions. 8. Industry-Specific Impacts: - The impact of AI varies by industry. For example, interior design might automate technical tasks but retain human-driven creative work. - Different industries will experience varying degrees of job transformation based on the nature of their tasks.

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.

Will you be able to find a job in your field at the same rate of pay or better in 3 to 5 years? AI’s impact on jobs isn’t measured by the unemployment rate. It’s showing up in the underemployment and participation rates. Underemployment, being unable to find work in your field, is rising across domains, and over 700,000 people left the workforce in May alone (Bloomberg). This chart shows a leading indicator: impact on recent graduates. Entry-level roles have been hit the hardest. However, most who have looked for a job in the last year will tell you that it’s harder to find a job in their field, with their current skills, and at the same compensation level, even with experience. Fields with the lowest underemployment rates have a shortage, indicated by a low unemployment rate. Two fields stand out with above-average unemployment and below-average underemployment: Computer Science and Computer Engineering Demand in both domains is high for people with data and AI skills, but falling for people without them. Technical talent must continuously reskill to remain relevant in the job market, but that’s not new. We’re used to reskilling every 5 years with new programming languages, tech stacks, and areas of focus. Technical ICs are eventually forced into entirely new tracks: leadership, product, founder, or strategy roles. However, technical capabilities and continuous reskilling are part of a growing number of fields that used to be nontechnical. The abilities to use AI tools, understand technical artifacts, and communicate with technical teams are emerging requirements across domains. We need to do a better job of preparing workers for the real-world impacts of AI instead of sharing the hype. Every role is adding technical capabilities. The future of work is here, and continuous reskilling is a massive shift most workers aren’t ready for.

Anthropic analyzed 4 million Claude conversations to reveal how AI is actually being used across the economy, and the results shatter common predictions. Here's what they found: (1) Software and writing dominate - these two fields account for nearly half of all AI usage, with software development alone representing 37.2% of queries (2) Depth of integration varies significantly - while 36% of occupations use AI for at least 25% of their tasks, only 4% show deep integration (using AI for 75%+ of tasks) (3) Automation vs augmentation - contrary to popular belief, most AI interactions (57%) show augmentative patterns where humans and AI collaborate, rather than pure automation (43%) (4) Wage correlation surprises - AI usage peaks in mid-to-high wage occupations but drops significantly at both extremes, challenging previous predictions of the highest impact on top-wage and low-wage jobs The study provides the first large-scale empirical evidence of how AI is transforming work, confirming that AI is transforming work task by task, not replacing entire jobs overnight. Post + paper https://lnkd.in/gYJnWknN — Join thousands of world-class researchers and engineers from Google, Stanford, OpenAI, and Meta staying ahead on AI http://aitidbits.ai

Pretty much every day, I’m asked: 'Should we be worried about AI taking over jobs?' To be honest, I’m not losing any sleep over it—and here’s why. Generative AI is making waves, but here’s a surprising twist: it’s not replacing workers as much as it’s helping them. At this year’s American Economic Association (AEA) conference, a central theme emerged: AI is complementing human workers. Economists are finding that AI enables workers to do their jobs better—serving more customers, working more efficiently, and increasing demand for their skills. Take radiologists, for example. While AI can analyze medical images, it can’t replace all the other 26 tasks that they do, many of which are essential human tasks like consulting with doctors and patients. That’s true for most jobs—AI might automate certain tasks, but it doesn’t eliminate the need for human expertise and empathy. The result? Radiologist jobs are growing. Similarly, language translator jobs are growing. But here’s the flip side. Just because AI doesn’t take over entire jobs doesn’t mean it’s all good news. Partial automation could still make jobs less satisfying, more stressful, or lower wages. That’s why we have choices. As Erik Brynjolfsson pointed out at the conference, the way we design our AI systems—and the policies that support them—will determine whether we use AI to augment workers or concentrate its benefits in the hands of a few. ➡️ I couldn’t agree more. The future isn’t written in stone. The path to better is there for us humans to take—if we choose to redesign jobs and rethink our labor market systems—making them more dynamic, more accessible, and more human-centric. What do you think? How can we balance AI and human ingenuity to create a future that works for everyone? #AI #futureofwork #labormakets #aiandhumans #jobredesign