The Future Of Work Podcast With Jacob Morgan | Futurist | Workplace | Careers | Employee Experience & Engagement |

The first quarter of 2026 was not just a collection of headlines. It was a definitive "hard reset" for the global workforce, marking the moment where the gap between legacy systems and the new AI-driven reality finally collapsed. In this episode of Future Ready Leadership, we're revisiting the top stories that made it to our Best of the First Quarter edition. We start with the trillion-dollar software sell-off, where the market's reaction to AI-driven workflows signaled a massive shift from humans performing manual tasks to supervising automated systems. This move toward radical accountability is further exemplified by Citigroup's declaration of the end of the "effort era," as CEO Jane Fraser mandated that employees be judged solely on measurable results rather than visible busy work. We then examine Amazon's internal talent mobility strategy, which reframes automation-related job changes as an opportunity for redeployment by giving staff 90 days to find new internal roles. This leads into a discussion on the

March 27, 2026: Anthropic accidentally leaked Claude Mythos — its most powerful model ever — and the implications for cybersecurity and enterprise AI go far beyond a product announcement. America's top HR leaders gathered at the WSJ CPO Summit and delivered a blunt message: most companies are building AI agents completely wrong, and IBM learned that the hard way. JPMorgan has made AI adoption a formal, trackable performance requirement for 65,000 engineers — and it's a preview of what's coming to every large organization. And a new KPMG survey finds Gen Z wants the C-suite and a 5 o'clock logout — so we have an honest conversation about whether that's actually possible.

March 26, 2026: A California jury found Meta and YouTube liable for deliberately addictive platform design — and the legal framework they used is headed straight for enterprise AI. Salesforce freezes base salary raises for directors and above, shifting to equity as Big Tech quietly rewrites its compensation playbook. Indeed's Hiring Lab data shows 95% of job postings still don't mention AI — and why that number is a warning, not a comfort. And Meta's president drops a number that reframes the entire AI workforce conversation: half a million electricians needed, and we're nowhere close.

March 25, 2026: Fortune reports that the job market has gotten so broken that people are paying $1,500 a month just to have someone apply to jobs on their behalf — and on average it takes 863 applications to land a single offer. We break down the AI doom loop that created this dysfunction, what it means for how companies hire, and what job seekers need to hear that nobody is telling them. Then ADP Research drops one of the largest workforce surveys ever conducted — 39,000 workers across 36 countries — and finds that only 22% of people feel their jobs are safe despite historically low unemployment. We push back on the doom framing, make the case that some anxiety is actually healthy and necessary, and surface the single most powerful lever any leader can pull right now: the data point that makes workers 5.3 times more likely to feel secure. And we close with Business Insider's exclusive look inside a Microsoft internal memo revealing a sweeping overhaul of the company's HR organization — including specific st

March 24, 2026: Three major research reports dropped today with a combined picture of where AI and work actually stand right now. A landmark NBER working paper of nearly 750 CFOs finds AI had zero measurable employment effect in 2025 — but projects roughly 500,000 job losses this year, concentrated in clerical and administrative roles. The same paper finds a productivity paradox: executives believe AI is working before the revenue proves it, echoing a pattern economists last saw with the personal computer. Anthropic's new Economic Index reveals something most organizations are completely missing: experienced AI users have a 10% higher success rate than newcomers — not because of what they're doing, but because of how long they've been doing it. AI fluency compounds like a skill, not a software license. And a major Gallup survey finds college graduates are more pessimistic about finding a job than at any time since 2013, with software developer postings down 29% and marketing down 27% — but the real explanatio

The real bottleneck to AI isn't the code; it's our own ego. We're so hooked on being the "expert" that we've forgotten how to be beginners again, and in a world changing this fast, that's a dangerous place to be. If we want to move forward, we must trade the safety of our legacy habits for the "productive discomfort" of constant unlearning. In this episode, Microsoft's Executive Vice President and Chief People Officer, Amy Coleman, joins us to talk about managing 220,000 employees through a growth mindset and explore the deep link between AI, culture, and leadership. Amy shares how to embrace adaptive leadership, which basically means leading even when you don't have all the answers. She explains why decreasing proximity is the secret to keeping trust alive during massive change by bringing employees closer to the "why" behind every decision. We get tactical as we uncover strategies for large-scale re-skilling, shifting from just tracking activity to rewarding real impact, and using talent redeployment to mak

March 20, 2026:  The White House dropped its national AI legislative framework today — I go through the whole thing, because there's a provision about preempting state AI laws that is one of the most consequential things to happen in AI policy in years. A columnist at The Sunday Times made an argument that stopped me: the real AI risk isn't losing your job — it's what happens to your retirement if AI disrupts your career at 50 instead of 30. Most people aren't thinking about it this way. They should be. Jensen Huang proposed paying engineers in AI tokens worth half their salary, on top of cash. I explain what tokens are, why elite engineers are leaving high-paying jobs over GPU access, and what it means that the unit of value in the AI economy is shifting from time to compute. The New York Times is calling it tokenmaxxing. And JPMorgan deployed AI to monitor junior bankers' hours — not because they're over-reporting, but because they're deliberately hiding how much they're actually working. Watch the ful

March 19, 2026: Jensen Huang had one of the biggest weeks in tech at Nvidia's GTC — but his sharpest line wasn't about chips. When asked why companies are laying off workers, he said simply: because they're out of imagination. We unpack what that means, plus his surprise take on compensation from the All-In podcast. Then Cognizant drops a bombshell update to its 2023 workforce study: 93% of jobs impacted by AI, $4.5 trillion in labor shifting to machines, six years ahead of schedule. Their own words: "We underestimated the technology." But two CEOs are pushing back on the doom narrative — Uber co-founder Travis Kalanick says humans will be "super fine" until AGI arrives, and Tech Mahindra CEO Mohit Joshi argues the demand for human labor isn't going anywhere, and has the data to back it up. We close with JPMorgan Chase's 2026 tech trends report and the concept quietly reshaping what leaders actually do: context engineering. Watch the full episode on YouTube ---------- Start your day with the world's top

March 18, 2026: Two-thirds of CEOs are freezing hiring while betting billions on AI — and a gender economist argues they're cutting the very people needed to make those bets pay off. A 7,000-word Substack essay imagined a "Ghost GDP" collapse by 2028, moved the Dow 800 points, and sparked a Wall Street war between Citrini Research and Citadel Securities over whether AI job fears are real or overblown. Management consulting was supposed to be dead by now — Capgemini's strategy chief explains why it's not, and why the shift to outcome-based billing may be the more disruptive story. And Microsoft's chief scientist says the degree with the worst starting salaries may be the most future-ready credential in the age of AI. Sources: Fortune, Bloomberg, Fortune Eye on AI. Watch full video on YouTube ---------- Looking for what actually moves the needle on performance and retention? It's in The 8 Laws of Employee Experience. Order here: 8EXlaws.com

March 17, 2026: Five major AI models shipped in a single week in February. Your company's training budget grew 5%. Cathie Wood told Bloomberg this morning that AI is already pushing productivity above trend and projects it hits 6% annually — Goldman Sachs says there's no macro evidence of it yet. Both can be right, and today we explain why. Plus: FedEx's blueprint for an AI agent workforce across 50% of its operations, the real argument against traditional corporate training programs, and the full financial math on Meta's reported 15,000-person layoff — including whether the company leaked it on purpose to let Wall Street price in $160 billion in market cap before a single cut is confirmed.

Many managers today spend more time on paperwork and individual tasks than actually coaching their teams. This lack of true leadership hurts the employee experience and stops a business strategy from succeeding. In this episode, Emily Field and I talk about her strategic transition from a McKinsey partner to becoming a first-time Chief People Officer at LPL Financial. She shares her initial 30-day "learning tour" where she focused on listening to employees to understand the company's unique culture before building her people strategy. We also unpacked her "People Leader Operating System" and a "talent flywheel" designed to improve the talent lifecycle from hire to retire. We explore the 50/50 performance management split to measure both business outcomes and human values, as well as using AI as a "superpower" to assist work while keeping human judgment as the main partner. Emily also explains the "people P&L" dashboard to track leadership data, the "align-empower-reinforce" model for training 1,300 leader

March 13, 2026: Most companies are cutting headcount to fund AI — but do they actually know what AI costs? When agentic AI runs autonomously overnight, the compute bill can hit $120,000 to $270,000 a year. Add hidden infrastructure costs running 200 to 400 percent above vendor quotes, plus the human oversight that never goes away, and the "AI is cheaper than people" math falls apart fast. Meanwhile Elon Musk is going the other direction — Tesla is increasing headcount while Atlassian and Block are cutting thousands, betting that output per human will get "nutty high." And an AI agent autonomously applied for 278 jobs this week, nearly got hired, and is still running. HR has no governance framework for any of this. Today's episode is about the gap between what organizations think AI costs, what it actually costs, and who's responsible for closing that gap.

March 12, 2026: Companies are failing to communicate the real promise and potential of AI to their people. Sam Altman stood in front of BlackRock and admitted nobody knows what to do about the labor-capital shift AI is creating. At Morgan Stanley's TMT Conference, the dominant investor question was what AI means for the next generation of workers — and the anxiety in that room is trickling down into every organization. Axios published data showing white-collar job cuts have been compounding for three years, giving employees every reason to be pessimistic. Gen Z is bringing parents to job interviews and planning early retirement in their 40s — two symptoms of a generation that has stopped believing the employment system will work for them. And Fast Company makes the case that women over 50 are the most undervalued workforce asset in the AI age — a missed opportunity hiding in plain sight. 

March 11, 2026: Amazon corporate workers say the company's AI push is creating more work, not less — with surveillance dashboards tracking every click and promotion criteria now tied to AI adoption. Oracle's Larry Ellison became one of the first Fortune 500 CEOs to explicitly confirm on an earnings call that AI tools are reducing his headcount — while the company carries $100 billion in debt and negative free cash flow. A new UBS report finds 63% of U.S. entrepreneurs are planning to exit their businesses in the next five years, an exit wave nobody is connecting to AI-driven workforce disruption. And as layoffs accelerate, the unemployment insurance system — unchanged since FDR built it in 1935 — is failing to reach 75% of the workers it was designed to protect.

March 10, 2026: AI is generating real, measurable productivity gains at major companies. Workers aren't seeing any of it. A new survey of 100 major CEOs finds only 9% plan to cut jobs because of AI this year — but buried inside that optimistic headline is an admission about ROI that changes the entire picture. China just launched the most ambitious society-wide AI employment push in history, betting that the technology creates more jobs than it destroys with 300 million retirements on the horizon. Fortune has the one metric CEOs are now using to quietly recalculate how many humans they actually need — and most employees have never heard of it. And Mercor, a $10 billion startup, is paying doctors, lawyers, and investment bankers hundreds of dollars an hour to train the AI that may eventually replace them.

While many companies focus only on buying new AI tools, the real secret to success often lies in changing how leaders think and act to drive a massive business turnaround. In this episode, Anna White, EVP and Chief People Officer at Lumen, joins the show to discuss how a major networking company is transforming its business through a deep focus on leadership and AI. We explore how leaders must shift from being "knowers" to "learners" by embracing curiosity and a growth mindset. The discussion covers practical steps like launching an AI literacy academy for all employees, using "Dare to Lead" training to build courage, and managing the risks of "work slop" by ensuring human judgment always checks AI work. We also dive into real examples of AI pilots, such as the GoalPro tool for aligning targets, and examine how to prepare for a future hybrid workforce where humans manage AI agents. This conversation offers a clear roadmap for HR leaders handling the complex mix of culture change and digital transformation. --

March 6, 2026: The U.S. economy lost 92,000 jobs in February — and the headline number is almost the least interesting part of the story. When you break down where the losses actually came from, you get a picture far more complicated than the AI-took-our-jobs narrative dominating social media right now. Healthcare, tech, federal government, manufacturing, transportation — each sector tells a different story, and together they reveal a labor market being squeezed from multiple directions at once: AI, tariffs, Baby Boomer retirements, post-pandemic correction, and a geopolitical shock that just sent oil past $87 a barrel. Meanwhile, the Fed is openly questioning whether it even has the tools to respond — because cutting rates doesn't create jobs for people whose skills have structurally shifted out of demand. Also this week: Uber's CEO says don't come here if you want to coast — and why that lands so differently in this economic moment. A new survey reveals that 90% of companies have AI chatbots but almost none

March 5, 2026: The company making AI (Anthropic) just published real data on what AI is actually doing to jobs — and the finding that should concern everyone isn't layoffs. It's that the hiring door for workers aged 22 to 25 has quietly dropped 14% in AI-exposed fields since ChatGPT launched. Today we cover four stories: Stanford's Erik Brynjolfsson on why minimum wage increases are accelerating robot adoption. Anthropic's brand new labor market study — and why you should read it with a critical eye. The February job cut numbers, which look better than January but hide a more troubling signal. And Vinod Khosla predicting today's five-year-olds will never need jobs — a claim we push back on hard. The data is in. It's more complicated than either side wants to admit.   Watch the full episode on YouTube   ----- Start your day with the world's top leaders by joining thousands of others at Great Leadership on Substack. Just enter your email: ⁠⁠https://greatleadership.substack.com/ Stop patching problems and s

March 4, 2026: The ECB just released new data showing companies that use AI are hiring, not firing — but the full story of what happened to bank tellers reveals why that optimism has a shelf life. USAA CEO Juan Andrade says Gen Z won't be as well off as Boomers and Gen X, and the numbers are stark: entry-level job postings down 29% globally, Gen Z financial insecurity up 18 points in a single year, and an average net worth of negative $22,000. Slack cofounder Stewart Butterfield says most of what passes for work in large organizations isn't actually work — he calls it hyper-realistic worklike activities, and the data shows it's costing U.S. companies $37 billion a year in ineffective meetings alone. And a neuroscientist who testified before the U.S. Senate says Silicon Valley convinced schools they were broken when they weren't, spent $30 billion putting screens in classrooms, and produced the first generation in modern history to score lower on cognitive tests than their parents — and now AI in classrooms is

March 3, 2026: The hype around AI and jobs is loud. The actual data tells a more nuanced story. This week, Stanford economist Nick Bloom released the most rigorous study yet on AI's impact on employment and productivity — surveying nearly 6,000 executives across four countries with the Federal Reserve and Bank of England. The findings are striking: 90% of firms report zero employment impact from AI so far, yet US executives are planning to cut over two million jobs in the next three years based on gains that haven't materialized yet. We break down what that gap means for workers, leaders, and organizations. Plus: CNN pushes back on the viral AI doom-loop narrative — and why "don't freak out yet" isn't the same as "you're fine." Why 43% of workers want to change careers but almost none will — and the psychological trap behind what researchers are calling "job hugging." And the central irony of the AI economy: the companies spending trillions to automate knowledge work can't build the infrastructure to run it b