The Future of Work With Jacob Morgan

September 2, 2026: I share key lessons from my CHRO session with iFood CEO Diego Barreto, including why he is investing in AI even with negative ROI, how he built a digital twin, and how iFood is rethinking reviews, meetings, and change management. Then I get into the Wall Street Journal's report on employers using new interview rituals to fight AI-enabled candidate fraud. Finally, I unpack Uber cutting 10% of its workforce and why the real story may be work redesign, bureaucracy, and coordination, not AI replacing jobs.

I talk with Ofir Bloch, SVP of Corporate Marketing at WalkMe, about why enterprise AI adoption is harder than buying tools and handing out licenses. We get into WalkMe's State of Digital Adoption research, the gap between executive confidence and employee trust, AI sprawl, shadow AI, Gen Z's overconfidence with AI, and why real ROI comes from changing workflows instead of just tracking usage.

August 28, 2026: I break down what redesigning work with AI actually means and share a practical framework for removing human glue, handoffs, waits, and routine work while creating new value. Then I get into Jensen Huang and Bill Gates disagreeing over whether robots and AI tokens should be taxed. Finally, I unpack the government's new 10-year jobs forecast and why the fastest-growing jobs in America still require something AI does not have: a human body in the room.

August 26, 2026: I look at Reuters' report on Meta's Project OT, the internal plan to turn Meta into an AI-native company with smaller, talent-dense teams overseeing software that does more of the daily work. Then I get into Anthropic reportedly telling investors its total addressable market could exceed $30 trillion and why that number may be more about payroll than software. Finally, I unpack Gallup's new Gen Z study and why the most important support for young people may not come from schools, but from weekly conversations at home.

August 24, 2026: I look at the rise of three-year bachelor's degrees and why the 120-credit college model was never really designed to measure learning. Then I get into new data showing softwAugust 24, 2026: I look at the rise of three-year bachelor's degrees and why the 120-credit college model was never really designed to measure learning. Then I get into new data showing software engineering jobs are rebounding, but junior engineers are being left behind as companies hire more senior talent. Finally, I unpack why annual performance reviews refuse to die, what they still do well, and why feedback, compensation, and documentation should not all be treated as the same thing.are engineering jobs are rebounding, but junior engineers are being left behind as companies hire more senior talent. Finally, I unpack why annual performance reviews refuse to die, what they still do well, and why feedback, compensation, and documentation should not all be treated as the same thing.

August 21, 2026: I look at why the bond market is sending CEOs a blunt message: the era of cheap money is over, and higher borrowing costs may push companies toward leaner headcount and more automation. Then I get into new CBRE data showing New York has passed San Francisco and the Bay Area as America's largest tech talent market for the first time in 13 years. Finally, I unpack the viral resume prompt-injection story, where job applicants are hiding invisible instructions in resumes to manipulate AI screening tools.

August 19, 2026: I look at new research showing that most workers would reject a promotion if it meant sacrificing their work-life boundaries, and why the traditional management promotion may no longer feel worth the cost. Then I break down reporting that Anthropic out-earned OpenAI in the second quarter. Finally, I get into the surge in boomerang employees, who now account for 35% of new hires, and why companies are increasingly bringing former workers back.

August 17, 2026: I look at Gallup's new research showing that AI adoption can improve or damage workplace culture depending heavily on one person: the direct manager. Then I get into Siemens CEO Roland Busch's approach to leadership, including short email replies, a sub-100-message inbox, and no recurring one-on-ones with direct reports. Finally, I unpack the public debate between Gavin Baker and Anthropic CEO Dario Amodei over AI fearmongering, trust, data centers, and whether AI leaders have helped create the backlash they are now trying to explain.

I talk with Lindsay Crawley-Herbert, Chief People and Transformation Officer at SCAN, about why AI transformation is really a people and workforce challenge. We get into why SCAN moved AI, data, and analytics under HR, how they built their internal GPT called SCAN X, how they manage AI costs and governance in a regulated healthcare environment, and why the goal is not replacing people but helping employees become "superhuman" with AI.

August 14, 2026: I look at OpenAI's own study on how companies use ChatGPT at work and why usage volume is not the same thing as ROI. Then I get into the Wall Street Journal's "jobless boom" argument and why companies may be growing without hiring for reasons beyond AI. Finally, I unpack Elon Musk telling SpaceX employees they will be Grok's "parents" because the AI will be trained on their work, knowledge, and contributions.

August 12, 2026: I look at Stanford's updated Canaries in the Coal Mine research, which finds young workers in highly AI-exposed jobs are falling behind while experienced workers are holding up. Then I get into Fortune's report on companies capping AI usage as token costs blow past budgets. Finally, I unpack Anthropic's plan to watermark Claude-generated output and why it raises a much bigger question about authorship: how much AI help can a document get before people stop seeing it as yours?

August 10, 2026: I look at Mark Zuckerberg's new Meta manifesto and why he's positioning open superintelligence as a direct challenge to OpenAI and Anthropic's more centralized approach. Then I get into Nissan using AI-powered cameras at its Canton, Mississippi factory to track how workers bend, twist, and move on the assembly line. Finally, I unpack WIRED's report on the rise of AI job interviews, where candidates record answers late at night and, in many cases, no human ever watches the interview.

August 6, 2026: I look at why more than a third of U.S. employers are handing out flat "peanut butter raises" even as top performers use AI to do more. Then I get into new data showing workers' share of U.S. economic output has fallen to the lowest level on record, raising a bigger question: if AI makes people more productive, who gets the gains? Finally, I unpack LinkedIn's move to reduce AI slop and why polished AI-generated work is becoming a real credibility problem inside companies.

August 5, 2026: I look at the Wall Street Journal story on parents getting involved in their adult children's careers, from job fairs to calls with hiring managers. Then I get into a new KPMG survey showing interns now rank career growth above salary and work-life balance, with 93% aspiring to reach senior leadership. Finally, I unpack LinkedIn's 2026 Top Colleges list and why families should think less about prestige and more about outcomes, cost, skills, and career ROI.

I talk with Naveen Jain, founder and CEO of Viome Life Sciences and author of Counterintuitive, about why entrepreneurs should focus on big problems instead of small ideas. We get into his framework of "why this, why now, why me," why non-experts often disrupt industries, how AI is changing work and healthcare, why personalized nutrition matters, and how parents can raise kids who are curious, resilient, and willing to build.

July 31, 2026: I look at Amazon's AI projects that ran massively over budget, including one Claude-powered project that came in 860% over plan. Then I get into Florida's proposed rule that would let parents opt their kids in or out of AI tools in the classroom. Finally, I unpack Anthropic's disclosure that its own Claude models breached live company systems during security testing, and why AI agents make the old idea of a "sandbox" much harder to trust.

July 30, 2026: I look at Mark Zuckerberg's argument that AI superintelligence should be for everybody, and why Meta's falling operating margin and massive AI spending tell a more complicated story. Then I get into Leopold Aschenbrenner's AI hedge fund selling its public portfolio to Citadel after a brutal reversal in AI infrastructure stocks. Finally, I unpack the Financial Times report on PwC publishing fake AI citations and why fabricated sources may become one of the biggest credibility risks in the AI era.

July 29, 2026: I look at how KPMG is rebuilding the entry-level audit role as AI takes over routine testing and forces companies to rethink how young employees learn judgment, critical thinking, and business skills. Then I get into Fortune's story on the CFO cost wall around AI and why proving ROI is getting harder. Finally, I look at where hiring is actually happening and why the real AI jobs story may be less about collapse and more about how work is being redesigned.

July 28, 2026: I explain the concept of human prompting, the leadership skill I believe every organization needs as AI becomes embedded in work. I get into why AI can make people look smarter while weakening judgment, how cognitive surrender shows up in schools, medicine, law, and the workplace, and why leaders need to ask better questions before accepting AI-generated work. I also break down the eight human capacities AI cannot replace, from disagreement and intuition to moral judgment, empathy, and slow thinking.

I talk with Ron Johnson, creator of the Apple Store and Genius Bar, former J.C. Penney CEO, and author of Shop Different, about what really made Apple's retail strategy work. We get into his early career at Target, how Steve Jobs recruited him, why the Apple Store was built for the 95% of customers who did not yet use Macs, how the Genius Bar came to life, what he learned from J.C. Penney, and why he remains optimistic about AI, work, and the future of retail.

July 24, 2026: I unpack the story of OpenAI's AI model escaping its sandbox and hacking into Hugging Face during a cyber stress test. Then I get into Anthropic's surprise launch of Claude Opus V, why the model's price and performance matter, and what it says about AI becoming cheaper and more commoditized. Finally, I break down Jensen Huang's first post on X, his open weights letter, and the growing fight between open and closed AI models.

July 23, 2026: I look at Google's Atlas study, which analyzed nearly 15 million Gemini interactions and found that AI use at work is broad but still shallow. Then I get into new research showing students who used AI for homework performed better at first, but saw major drops in exam scores later. Finally, I unpack Anthropic chief economist Peter McCrory's argument for why AI has not raised unemployment yet: it is still amplifying human expertise more than replacing it.  

I talk with Mark Paulek, Chief Human Resources Officer at Kyndryl, about how leaders should approach AI transformation without losing employee trust. We get into Kyndryl's People Readiness Report, the company's AIR framework for anticipating demand, inventorying skills, and redeploying talent, plus how they think about AI governance, human-in-the-loop decisions, ROI, reskilling, and why AI adoption is ultimately a people challenge before it is a technology challenge.

July 17, 2026: China's Moonshot AI released Kimi K3, their largest AI model yet, and it is already testing close to OpenAI and Anthropic on major benchmarks. Then I get into the AI guilt showing up among students and new workers who leaned heavily on AI and now question whether they can trust their own skills. Finally, I look at why leaders may struggle to keep their best people when AI makes it easier for top performers to leave and build on their own.

July 16, 2026: New JLL research shows most executives expect AI to grow their teams instead of shrink them, even as layoffs continue in AI-exposed industries. Then I get into New York becoming the first state to freeze new large AI data centers, why I think that is a mistake, and what it could mean for American AI infrastructure. Finally, I unpack Apple's lawsuit against OpenAI and make my prediction that Sam Altman will not be CEO of OpenAI within the next year unless the company makes major changes.  

July 15, 2026: Andreessen Horowitz's argues that AI is not simply replacing workers, it is turning every worker into a manager of agents. Then I get into Bank of America's claim that AI is already showing ROI in its earnings, and why I'm skeptical of how much of that efficiency gain can really be attributed to AI. Finally, I look at OpenAI's first physical device, a screen-free AI companion reportedly designed to feel alive, and why that matters for the future of work.

July 14, 2026: Goldman Sachs' warns that the real AI productivity payoff may not arrive until 2030 at the earliest, because companies are buying the technology faster than they are redesigning work. Then I get into the split among leading economists over whether AI needs new institutions and guardrails now, or whether early governance could slow progress. Finally, I look at IBM's major market shock and why it shows that even companies selling AI transformation can struggle when customer behavior changes faster than the organization can move.

I talk with Ron Friedman, award-winning social psychologist and bestselling author of The Best Place to Work and Super Teams, about what high-performing teams actually do differently. We get into why great teams avoid unnecessary meetings, how teammates make each other better, why feedback usually fails, and how AI is changing collaboration, curiosity, communication, and accountability at work.

July 10, 2026: Axios warns about AI's new class divide: the haves, the have-nots, and the "no-nots" who are already being shaped by AI without realizing it. Then I get into new Indeed and Business Insider data showing that AI is moving into job titles far beyond tech, from physical therapy to legal, finance, marketing, and management. The bigger issue is not just who has access to AI. It's who knows how to use it, who is being quietly managed by it, and whether leaders use AI to make people better or slowly de-skill them.

July 9, 2026: OpenAI released its new GPT 5.6 lineup, Elon Musk's xAI launched Grok 4.5, and GPT Live showed where voice-based AI may be heading next. Then I get into Uber's Agentic Pods, where the company is embedding AI-proficient engineers inside legal, finance, and HR even as leadership admits it still can't prove the ROI. Finally, I look at the Brown University AI cheating scandal, where students averaged 96 on a take-home midterm and then collapsed to 48 on an in-person final, and why this should worry every leader thinking about AI, skill, and judgment.

I talk with Yolanda Seals-Coffield, PwC US Chief People and Inclusion Officer, about how PwC is preparing 80,000 people for an AI-enabled future. We get into PwC's approach to democratizing AI access, building responsible AI habits, measuring adoption beyond token usage, and creating learning that happens directly in the flow of work. Yolanda also shares how PwC is rethinking entry-level talent, human skills, and career development as AI changes the work new graduates are expected to do.

July 3, 2026: Tesla is capping employee AI spending at $200 a week after some engineers reportedly burned through thousands of dollars in tokens, showing that "free" AI was never really free. Then I get into the rise of social offloading, where people use AI not just to think for them, but to handle difficult messages, feedback, and human interactions.

July 2, 2026: Microsoft is putting $2.5 billion and 6,000 employees behind a new group designed to help customers actually use AI inside their businesses, following a similar move from Amazon. Then I get into why former chief AI officer Sol Rashidi fired half of her AI agents after spending more time babysitting them than getting work done. I also look at why administrative assistants may become more valuable in the AI era when they know how to use the tools, manage context, and apply judgment.

July 1, 2026: Companies are discovering that AI agents can drive token usage far beyond what they budgeted for, forcing leaders to bring cloud-style cost controls into AI spending. Then I get into Ford bringing back 300 veteran quality inspectors and engineers after its AI-driven quality checks missed what experienced humans could catch. Finally, I look at Palantir CEO Alex Karp's CNBC warning about token pricing, customer data, model control, and why more companies may start rethinking how much of their AI strategy they want to outsource.

June 30, 2026: New research from Ramp Economics Lab and Revelio Labs shows that companies spending the most on AI are not shrinking the fastest. They are actually growing headcount faster, including in entry-level roles many assumed would disappear first. Then I get into Amazon Web Services' $1 billion push to build a new unit of embedded AI engineers, sending teams directly into customer organizations to help turn AI pilots into real work. The bigger story is that AI is not simply replacing jobs. It is changing which jobs grow, which skills matter, and where the real bottleneck is. 

I talk with Mike Thomson, President and CEO of Unisys, about the real state of AI inside companies. We get into why some organizations are using AI as cover for layoffs, why the backlash against data centers is often built on incomplete information, and why enterprise AI adoption will take years instead of weeks. Mike also explains why technical debt, messy data, governance, security, token costs, and workforce readiness are the real barriers leaders need to understand before they assume AI can simply replace people at scale.

June 26, 2026: OpenAI launched ChatGPT 5.6 with limited access to only 20 organizations, showing how frontier AI capability and government review are starting to split. Then I get into California's new AI job-loss tracker, which shows no broad AI layoff apocalypse yet, but does reveal pressure on college-educated workers in high-exposure roles. Finally, I look at why more executives are questioning whether they even want the CEO job anymore as leadership becomes more reactive, more political, and harder to sustain.

June 24, 2026: Meta's employee surveillance program, which tracked keystrokes, mouse activity, and screenshots before a data exposure forced the company to pause it. Then I get into Legion's lawsuit against the U.S. government after losing access to Anthropic's Fable 5 model, showing how frontier AI access is becoming a new business dependency and supply chain risk. I also look at software engineers facing workplace paralysis as AI models keep changing faster than people can master them, and why AI rollouts may be burning out the very high performers companies need most.

June 23, 2026: Companies are drowning in AI pilots, prototypes, and scattered use cases that make teams busier without necessarily making the business better. I talk about why the real advantage may come from finishing the few AI initiatives that matter instead of starting 300 that don't. Then I get into Adam Grant's new research linking return-to-office mandates with CEO narcissism, what the study actually found, where the methodology gets complicated, and why the better question for leaders is not "office or remote," but what arrangement produces the best outcomes for the team, the business, and the work being done

I talk with Greg Matson, Senior Vice President and Head of Marketing and Products at Solidigm, about the storage infrastructure powering the AI boom. We get into why AI training and inference require massive amounts of data, how GPUs, SSDs, and data centers work together, and why storage can't be an afterthought for companies building enterprise AI. We also discuss the scale of today's AI data center buildout, how Solidigm is using AI internally, and what this means for the future of work, education, and the skills people will need in an AI-first world.

June 19, 2026: Anthropic's Fable 5 shutdown appears to be tied to SK Telecom, Project Glasswing, Amazon researchers, the White House, David Sacks, and a dispute over whether Anthropic should fix or de-deploy the model. Fortune 500 companies just hit record revenue, profit, revenue per employee, and profit per employee while shrinking headcount for the second year in a row, raising a bigger question about productivity gains without job growth. New data from LV8 founder Griffin Hadrill shows AI-generated creative ads are underperforming human-made ads by 3 to 5 times, which is a reminder that originality, emotional connection, and human judgment still matter.

June 18, 2026: Companies are starting to count the real cost of AI after two years of broad experimentation, from rising token bills to the higher wage premiums commanded by AI-skilled workers. Then I look at Senator Ruben Gallego's push to investigate ghost jobs and whether AI-powered hiring platforms are distorting the labor data policymakers rely on. Finally, I break down Wall Street's hiring dilemma: AI can automate junior-level work, but it cannot replace the apprenticeship that develops future rainmakers, dealmakers, and senior leaders.

June 17, 2026: Anthropic's Claude Fable 5 and Mythos models were pulled after a government directive raised concerns about jailbreak risks, creating a wake-up call for companies building critical workflows on frontier AI models they don't actually control. Then I get into Meta's AI transformation struggles, including layoffs, employee reassignments, low morale, surveillance concerns, and what leaders can learn from one of the most visible AI change-management failures so far. Finally, I break down PwC's 2026 Global AI Jobs Barometer, which shows that AI isn't collapsing the labor market but splitting it into two tracks: roles where AI increases the value of human judgment, and roles where AI makes work easier for non-experts to perform.

Kelle Fontenot, Chief Digital Officer at KPMG, joins me to talk about how one of the world's largest professional services firms is embedding AI into the way work gets done. Kelle shares how KPMG is approaching enterprise AI adoption through its AIQ program, why AI requires close partnership between digital, HR, technology, and the business, and what it takes to drive change across 250,000 people globally. We also get into the realities of AI adoption inside a large, highly regulated organization: digital teammates, AI agents, tool overload, trust, security, and why traditional training alone doesn't change behavior. Kelle offers a practical look at how leaders can move beyond experimenting with AI and start making it part of the everyday flow of work without losing human judgment along the way.

June 12, 2026: SpaceX made history with the largest IPO ever recorded, raising $75 billion in its NASDAQ debut and instantly becoming one of the most valuable companies in the United States. But under the hood, this isn't just a rocket company anymore. It's a bet on Starlink, reusable rockets, and xAI's massive AI infrastructure. Then I get into the first-ever appearance of OpenAI, Anthropic, and Google DeepMind leaders at the G7 Summit, and what it means when the most powerful AI companies in the world are now part of global policy conversations. Finally, I break down Jeff Bezos' $12 billion raise for Prometheus, a new company building an "artificial general engineer" that could reshape manufacturing, aerospace, pharma, defense, and the future of high-skill knowledge work.

June 10, 2026: Palantir CEO Alex Karp is warning tech leaders that bragging about AI-driven layoffs is a major political mistake and could fuel backlash against the entire industry. Then I get into a new Reuters/Ipsos poll showing that 53% of Americans fear AI could put them or someone in their household out of work, which means AI job anxiety is no longer a fringe concern. Finally, I break down the "great flattening," with new data showing that 41% of employees say their companies trimmed management layers last year, and why eliminating too much middle management could create a serious leadership pipeline problem for the future.

June 9, 2026: Meta is investing $115 million into America's Workforce Academy to train electricians, welders, plumbers, fiber technicians, and other skilled tradespeople for the AI infrastructure boom. This isn't charity, it's a talent pipeline for the data centers, wiring, fiber, and physical systems AI depends on. Then I get into Anthropic's release of Claude Fable 5, its most powerful publicly available AI model yet, and what it means for trust, accuracy, pricing, and accountability as AI moves deeper into business operations.

We have all worked at a place where we felt like just another number in a spreadsheet. It is incredibly frustrating when you offer feedback that seems to vanish into a black hole of corporate bureaucracy. But what if your company actually treated your voice like a strategic roadmap for the future? In this episode, DJ Casto, the EVP and Chief Human Resources Officer at Synchrony, joins us to explore how his team transformed their culture to become the number one best place to work in 2026. DJ shares the secrets behind their decade-long journey of separation from GE Capital and how they climbed the rankings by anchoring their identity in the concept of trust. We dive deep into their philosophy of co-creation, where active listening through quarterly pulse surveys and roundtables allows employees to directly design the culture they want to inhabit. Discover how Synchrony applies agile software principles to HR by launching minimal viable products for benefits like personalized wellness coaches and on-site therapists to see what truly resonates with the workforce. We also tackle the modern challenge of AI, moving past the doom and gloom to discuss how technology can actually unlock human creativity and fulfill more enriched roles. You'll learn how to foster employee accountability through a focus on critical experiences rather than rigid job paths. This episode unpacks how you can build a high-trust organization where continuous improvement is a lifestyle rather than a one-time goal. Watch the full video 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/ Quick heads-up: my new book, The 8 Laws of Employee Experience, is a practical playbook for building an environment where people do their best work—order a copy here: https://bit.ly/8exlaws

June 5, 2026: Two stories today. First: hybrid work's approval ratings are climbing — but new research finds half of its believers quietly defected over three years. There's a name for what's breaking it, and most organizations haven't seen it yet. Second: Anthropic dropped internal data showing AI is writing 80 percent of its own code and outperforming human researchers on their own turf. The numbers are real — but so is the question of who's really behind the warning. One week after closing a $965 billion valuation and four days after filing for an IPO, Anthropic is calling for AI governance and oversight. That might be genuine concern. It might also be regulatory capture — the oldest playbook in business, where the most powerful incumbent shapes the rules in ways that lock out everyone coming up behind them.

June 4, 2026: Microsoft unveiled a wearable AI badge at Build 2026 that can see, hear, and act on your behalf. I break down the real productivity upside, and the chilling effect on human communication that the tech press isn't talking about. Then I take a critical look at Monterey Park's landmark vote to permanently ban data centers — 86% to 14%, the first in America. I understand why communities push back. I also think this particular decision is a mistake, and I'll tell you exactly why.Finally: Uber just cut 23% of its entire HR and recruiting function at record revenue, with 95% AI adoption across engineering — then said AI had nothing to do with it. 

June 3, 2026: Most people use a data center dozens of times a day and have no idea what it is. Today I'm changing that. I break down exactly what data centers are, what "compute" actually means, why every new AI model needs exponentially more of it, and how short we currently are as a country — using real numbers from Goldman Sachs, FERC, RAND, and others. Then I take on the five biggest myths driving the backlash: that new data centers waste water, that they're an energy disaster, that they kill jobs, that taxpayers are funding Big Tech, and that they destroy communities. I debunk every single one with sourced data — because the misinformation around data centers is doing real damage to America's AI future. These buildings currently account for 80% of US economic growth according to S&P Global, they're funding the nuclear renaissance, and they're the front line in a race with China that we cannot afford to lose. This is the episode I'd send to anyone who thinks data centers are the enemy.