Understanding Job Displacement Due To Automation

New research from MIT reveals an interesting automation paradox - AI/automation can simultaneously replace experts in one field while creating more expert jobs in another. Let's take a look at two examples from the research - bookkeepers vs. inventory clerks. Both got heavily automated between 1980-2018 but with different outcomes. Bookkeeper employment fell 33% while wages rose 40%. Employment doubled for Inventory clerks, but wages fell 13%. This happened because automation removed the routine parts of bookkeeping (data entry), leaving behind the expert work (analysis, problem-solving). However, for inventory clerks, automation removed the expert parts (price calculations), leaving mostly generic tasks anyone could do. The researchers call this "expertise bifurcation" and it explains why predictions about AI displacement can be so difficult to predict. When looking at the average expertise level of more than 300 occupations over nearly 40 years, they found that when simpler tasks disappeared, jobs became more specialized, and often better paid, even as employment declined. However, when automation removed the more expert tasks, wages tended to fall as more people moved into the role. “Taxi drivers, for example, once relied on deep knowledge of local streets, which was a real differentiator. But with the arrival of GPS, that expertise was automated. The result is a more commoditized taxi service: lower wages, but many more drivers.” The researchers point out that this shift can create opportunities for new professions to open up "because automation removes the hardest parts that used to be out of reach." One of the key takeaways from this research is that it's not about whether your job can be automated - it's about whether AI will eliminate your expert tasks or your supporting tasks. If AI handles your routine work while you focus on judgment, creativity, and complex problem-solving? Your value just went up. If AI can do what makes you uniquely valuable? Different story. The question isn't "Will AI replace me?," but "Will AI make my expertise more scarce, or more common?" So - what do you think this means for sourcers and recruiters? Check out the article and link to the full research here: https://lnkd.in/eHW7zfSp #AI #FutureOfWork #Automation

A new paper from Stanford University shows that early-career workers are currently the most exposed to AI. “Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence” evaluates changes in the labor market for occupations exposed to generative AI using high-frequency administrative data from ADP, the largest payroll software provider in the United States. The researchers studied a sample consisting of monthly, individual-level payroll records through July 2025, encompassing millions of workers across tens of thousands of firms. They linked the payroll data to “established measures of occupational AI exposure and other variables” to quantify the realized employment changes since the widespread adoption of generative AI. From the introduction: “We find that since the widespread adoption of generative AI, early-career workers (ages 22-25) in the most AI-exposed occupations have experienced a 13 percent relative decline in employment even after controlling for firm-level shocks. . .  These six facts provide early, large-scale evidence consistent with the hypothesis that the AI revolution is beginning to have a significant and disproportionate impact on entry-level workers in the American labor market.” Key Findings: 1) Substantial declines in employment for early-career workers (ages 22-25) in occupations most exposed to AI, such as software developers and customer service representatives. 2) Overall employment continues to grow robustly, but employment growth for young workers in particular has been stagnant since late 2022. 3) Not all uses of AI are associated with declines in employment. In particular, entry-level employment has declined in applications of AI that automate work, but not those that most augment it. My Thoughts: These findings make sense, but this is still just the leading edge of the impact on jobs. As the AI models get smarter, more generally capable, more reliable, and more agentic (able to perform tasks at or above levels of the average human worker) the impact will continue to move up the corporate ladder. I still believe middle management could be at high risk in the next 1-2 years across many industries. We explore this new report on ep 165 of The Artificial Intelligence Show (episode link in the comments). 00:00:00 — Intro 00:07:17 — AI Labor Market Signals 00:16:37 — AI Industry’s Increasing Political Influence 00:28:33 — Google’s Stunning “Nano Banana” Image Editor 00:34:26 — OpenAI Parental Controls and Support Features 00:38:23 — Anthropic Settles Authors’ Copyright Lawsuit 00:42:44 — Meta’s AI Strategy in Flux 00:46:06 — GenAI App Landscape Report 00:51:10 — OpenAI–Anthropic Joint Safety Evaluation 00:54:37 — Jensen Huang Suggests AI Will Create a Four-Day Workweek 01:00:11 — Microsoft’s AI Excel Warning 01:03:17 — Claude in Classrooms 01:07:07 — AI Product and Funding Updates

The AI job reckoning isn’t a hypothetical. It’s happening, and here's how to stay ahead: Dario Amodei, CEO of Anthropic and one of AI’s most influential voices, isn’t speculating about the future, he’s spelling it out: AI could eliminate half of all entry-level white-collar jobs in the next 1 to 5 years. This isn't fear-mongering. Amodei is building the systems reshaping the workforce. He says most people still don’t believe what’s coming. But disbelief won’t delay the impact. Here's the current state: → AI models today can code, draft legal contracts, review health records, write marketing copy, and conduct research. → Companies aren’t slowly testing, they’re implementing. → Layoffs are starting: ↳Microsoft cut 6,000 employees ↳Meta is reducing mid-level engineering roles ↳Walmart is trimming corporate jobs ↳CrowdStrike cited AI as the driver for cuts As I said on my podcast (Rush Hour Podcast): these companies are richer than ever. Yet they’re still cutting jobs, not because of losses, but to maintain margins as AI investments grow. One analyst projected Microsoft may need 10,000 annual job cuts just to offset AI-related capital costs. This is not a pause, it’s a restructure. Amodei puts it bluntly in a recent interview: “You can’t just step in front of the train and stop it. The only move that’s going to work is steering the train.” The speed and scope of AI’s impact are unlike past tech waves. This one targets: → Junior engineers → First-year law associates → Entry-level analysts → Customer service agents These stepping-stone jobs are vanishing quickly, and may not return. But this doesn’t have to be all doom and gloom. While jobs shift, tools for adaptation are more accessible than ever. Here are three moves you should be making now: 1. Stay Plugged In Track AI news like your job depends on it, because it might. Axios, The Information, TechCrunch and AI company blogs (like Anthropic’s Economic Index) offer real-time signals. 2. Upskill With AI You don’t need to code, but you do need to be AI-literate. Learn to use ChatGPT, Claude, and Midjourney in your current role. Either AI augments you, or replaces you. 3. Keep Your Career Fluid Assume more job shifts are coming. Keep your LinkedIn current. Practice interviewing. Nurture your network. In a shifting market, connections matter more than titles. Here's the bottom line: This isn’t speculation, it’s execution. AI is changing the labor market faster than most people realize. Amodei and other leaders are waving red flags, not to scare us, but to give us a head start. The winners of the AI era won’t be the ones with the safest job, but those who stay curious, flexible, and connected. How are you preparing for this new technology wave? Lmk below! 👇🏾 ---— 👋🏾 Want more startup advice and tech news? Follow me here: Justin Gerrard And check out my podcast: Rush Hour Podcast ♻️ Repost if you think someone in your network would benefit! #anthropic

50% of entry-level white collar jobs could be eliminated by AI within 5 years, driving up unemployment rates to 20% — but medicine is different. In an Axios interview last week: • Dario Amodei (CEO, Anthropic) warned AI could eliminate half of all entry-level white-collar jobs in the next 5 years • Governments and companies aren’t raising the alarm • Expect 10–20% unemployment • Industries at risk: tech, finance, law, consulting, admin — any task-based or knowledge work • Human workers are being replaced with AI agents. Entry-level roles most exposed Why? • AI is already good enough for "real" human work: eg. summarizing, brainstorming, reviewing contracts • Also good at “analyzing medical symptoms and health records” (quote from Axios article, but our research lab and others have seen strong signals where AI alone outperforms doctors in simulated patient care tasks) Anthropic clearly has a stake in this shift — but the underlying concerns are valid. Why bother training an intern when a chatbot gets it done faster, better, and cheaper? Trends: - Microsoft is laying off 6,000 employees, saying that the company is aligning for the AI era - Currently, 60% of people use AI for augmentation and 40% for automation, according to Amodei - A recent World Economic Forum survey found that 41% of employers plan to reduce their workforce because of AI automation by 2030 🩺 What about medicine? Have been asked by many residents and med students: - Should we be worried? - Which specialities should I avoid? My view: I don’t see any provider job loss in medicine. Healthcare is very insulated relative to other industries, because of: 1️⃣ Limitless and rising demand: aging populations, chronic disease management, primary and specialty care access 2️⃣ Structural barriers: reimbursement, regulation, malpractice risk Most importantly: Medicine isn't just knowledge work. We can — and should — use AI to expand reach, make care more preventive and accessible, and solve the parts of medicine that are still inefficient / eliminate busy work that no provider enjoys. But: Start now. Familiarity with these tools — even outside of clinical work — will matter. This week, Stanford’s Jonathan H. Chen, Reena Thomas and team are convening the first event dedicated to this topic: 📌 AI in Medical Education Symposium 🗓️ June 4, 2025 | 1:00–6:00 PM PT 📍 Stanford Hospital + Virtual 💻 Free to register — in person full, virtual seats still available. Agenda: • Framing AI’s impact on medicine — Jonathan H. Chen, MD, PhD • LLMs and prompt engineering — practical workshops Dong-han Yao, MD Shivam Vedak MD, MBA • Legal liability and regulation — Michelle Mello, JD, PhD • Real AI tools for medical education — live demos Andrew Berg, MD • Panel: What Makes a Doctor a Doctor? Free to attend for non Stanford clinicians, educators and trainees. Will be relevant for anyone thinking about how AI will reshape medical training and clinical practice.

Employment for 22–25-year-olds in AI-exposed roles has dropped up to 20% since late 2022... A new Stanford report released today reveals that AI is already reshaping entry-level employment, and the first signs are in the data. The report, "Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence," by Erik Brynjolfsson, Bharat Chandar, and Ruyu Chen, is the first large-scale empirical signal that AI is actively disrupting the labor market, and doing so unevenly. Analyzing ADP payroll data from 25 million+ U.S. workers, the report finds: ⭐ Employment for 22–25-year-olds in AI-exposed roles has dropped up to 20% since late 2022 ⭐ The shift isn’t limited to tech; trends are visible across industries and across data sets ⭐ Wages have remained stable, suggesting employers are cutting roles, not pay ⭐ The impact is concentrated in roles where AI automates, not where it augments That last point matters. Jobs that involve codified knowledge, like junior software development or customer service, are more vulnerable. Jobs that depend on tacit knowledge, collaboration, and judgment... less so. The researchers call young professionals in these roles the canaries in the coal mine. They’re not just early victims of automation, they’re early signals. So, if your organization is scaling AI, the strategic question isn’t just what we can automate. It’s whether we are building systems that replace talent or elevate it. The opportunity is still ours to shape. But only if we’re intentional. The report is robust, and I recommend downloading and reading it. It makes several additional important points. Download the report here: http://bit.ly/45Ttgzo

Lots of folks are talking about the new Stanford Digital Economy Lab study from Erik Brynjolfsson, Bharat Chandar, and Ruyu Chen that uses ADP payroll data to confirm something many of us already knew (or suspected): a 13% relative employment decline for 22–25-year-olds in the most AI-exposed jobs, with software engineering and customer service taking the biggest hit. One finding from the study that isn’t getting as much attention (but should): marketing and sales roles seem to be faring slightly better. Early-career headcount is still down, but by smaller amounts — with an upward trend over the past two years clawing back much of the post-ChatGPT dip. What’s going on? There are many factors, but it likely lines up with a principal finding of the study: entry-level employment declines when AI automates work, with muted effects when AI augments it. In GTM today, AI often augments. It spins one idea into dozens of testable variants, compiles account research into briefs, surfaces the right moment or quote from hundreds of call transcripts and pulls the right chart from an ocean of creative assets. AI speeds experimentation without deciding the message or the deal. Because feedback loops are immediate (CTR, replies, meetings booked) and the blast radius is small, humans stay pivotal. The pattern points to a future where the best roles go to the most leveraged — people who combine AI with domain expertise, customer understanding, and creative judgment. What these positions will be and how we handle structural changes impacting young workers, though, remain important open questions that demand serious study and attention (and more than just “universal basic income will fix it”). Expect more thoughtful takes from us as we mull on it and talk to entrepreneurs and folks in academia; would love to hear what you think!