Future Ready Leadership With Jacob Morgan

November 06, 2026: I unpack Wall Street's worst day since 2025 with the S&P down 4.4%, the NASDAQ crashing 5.5%, and NVIDIA falling 9% as Democratic leaders push for national data center moratoriums, why tech companies are losing the PR battle despite data centers supporting 5.5 million American jobs, and how banning this infrastructure could crater one third of US GDP growth while pushing innovation to Saudi Arabia and the UAE. Then I get into new Economist Enterprise research showing only 4% of midsize companies say AI and workforce transformation are moving forward as integrated efforts while 59% say AI is racing ahead of people and processes, why I think the ROI conversation around AI is flawed because we don't measure ROI on driver's licenses or high speed internet, and how AI is less like a factory machine and more like a capability that makes your world bigger. Finally, I look at Apple cutting employee AI budgets from $300 a day down to $200 and possibly $100 for engineers while some teams may drop to $25 daily caps, why organizations are realizing they don't need frontier models for most work when free or cheap tools deliver great results, and how my video editor who I stopped working with came back and created his job again by showing me what he could do with AI to make my content more dynamic and engaging.
Chapters

00:00:00 Wall Street's Worst Day of 2025: The $1 Trillion Tech Wipeout
00:05:46 The Data Center Ban Debate: 5.5 Million Jobs on the Line
00:09:28 The Chain Reaction: What Happens If We Ban Data Centers
00:13:47 Your Retirement Account Is an AI Investment: The 45% Reality
00:17:24 AI Moving Faster Than Organizations Can Adapt: The Economist Survey
00:19:00 The Driver's License Analogy: Rethinking AI ROI Measurement
00:21:45 Building a Website in 24 Hours with Muse: The Real AI Capability Test
00:30:01 The Shadow AI Risk: When Enterprise Limits Drive Personal Tool Adoption

November 04, 2026: I unpack the 6.3 billion dollar crypto heist at Binance that started with a fake job offer, why the engineer who downloaded malware disguised as an interview assignment thought he was taking a legitimate career step, and how attackers used social engineering to turn hope into the most effective hacking tool in history. Then I get into a hidden wave of graduates who are skipping years of career progression by managing AI agents instead of learning the trade, why PwC found that entry level roles shaped by AI are seven times more likely to require senior skills like leadership and strategic decision making, and how these roles have grown 35% since 2019 while other entry level jobs shrink by 10%.
Chapters

00:00:00 The Dream Job Trap: How a $6.3 Billion Heist Started with a Fake Recruiter
00:03:14 Social Engineering at Scale: When Breaking In Means Getting Invited In
00:10:07 The Grunt Work Paradox: Graduates Managing AI Without Learning the Trade
00:13:22 The $6 Billion Spreadsheet Error: Why Judgment Matters More Than Tools
00:15:47 See One, Do One, Teach One: The Apprenticeship Model AI Can't Replace
00:27:12 Let Your Accomplishments Speak: The Cowbell Test for Leaders and Teams

I sit down with Khadija Benhamada, member of the executive board and chief people officer at Merck Group, a 358 year old life science, healthcare, and electronics company with more than 62,000 employees across 66 countries. We unpack why leadership is a daily choice not a title, why Khadija believes you're not born a ready leader but become one through aspiration and practice, and how Merck balances two critical energies that every leader must master: performing today while transforming for tomorrow. I explore why performing means understanding customer expectations, delivering with clarity, and using AI to scale productivity faster and cheaper, while transforming is about asking more questions than having answers, building agility at scale, and creating an organization ready for whatever might come next without trying to predict the future. Khadija breaks down why great leaders eat last and put their teams first, why she doesn't count her work hours because impact matters more than time, and why micromanaging kills both energy and results. We get into the four pillars of transformation including being two steps ahead, visionary thinking, risk taking, and scenario planning, why Khadija tells her teams to hope for the best and prep for the worst, and how working for a company that impacts patients with multiple sclerosis and helps people have children creates a noble pressure to always have a plan B.
Chapters

00:00:00 Leadership as a Daily Choice: Walking Before You Run at a 358-Year-Old Company
00:07:41 Clarity Versus Transparency: Managing Noise Without Creating Panic
00:09:59 Leaders Eat Last: Why Caring for Your Team Comes Before Everything Else
00:19:08 The Chess Player Mindset: Scenario Planning and Connecting the Dots
00:33:45 AI Productivity Versus AI Transformation: The Two-Speed Strategy
00:38:11 The Agent Manager Dilemma: When Employees Manage Bots Instead of People
00:50:16 Hope for the Best, Prep for the Worst: Building Possibility Over Risk

October 31, 2026: I get into why tech stocks are getting absolutely massacred with the NASDAQ down more than 3.5%, Intel losing 30% of its market cap, Alphabet down 12.6% in its worst day since going public in 2004, and the NASDAQ 100 on pace to lose more than $1 trillion in market value. I look at Gallup's report showing employee engagement hit a 15 year low at 29%, why I think this headline is more dramatic than the reality since engagement started at 26% in 2000 and is now 29% after a dot com crash, financial crisis, pandemic, remote work, and AI, and why a metric that barely moves through all of that isn't a very sensitive alarm. Finally, I unpack the case of David Derman, a research administrator at the University of Kentucky who became the first known humanist to receive a religious exemption from using AI, why the 2023 Supreme Court case Groff versus DeJoy raised the bar for employers to deny religious accommodations, and why religious discrimination charges jumped from 2,400 in 2021 to nearly 14,000 in 2022 during COVID vaccine mandates.
Chapters

00:00:00 Bartleby's Rebellion: When Employees Prefer Not To
00:04:09 Tech Stocks Massacred: The $1 Trillion NASDAQ Wipeout
00:15:42 Inside the CHRO Tech Stack: Why Nobody Loves Their Software
00:25:42 The AI Opt-Out: First Religious Exemption Approved at University of Kentucky
00:33:40 The Organic Fruit Niche: When Human-Made Work Becomes a Selling Point
00:34:04 Leader Action Items: Write the Standards Before Someone Says I Prefer Not To

October 28,2026: I unpack Marissa Mayer's viral moment when she asked her AI assistant Dazzle to tell her what made her 10-year-old daughter special, why the internet erupted over whether parents should outsource that kind of thinking, and the three questions you need to ask before handing anything off to AI. Then I head to Nevada where AI is building jobs in the north and replacing them in the south, why more than 100,000 acres of desert east of Reno are becoming one of the world's largest concentrations of data centers providing work for thousands of electricians and pipe fitters, and why 400 miles away on the Las Vegas Strip companies like Zoox and Waymo are replacing human-driven taxis while MGM's call center cuts hundreds of jobs using AI. Finally, I look at SAP replacing expensive AI models inside its software with cheaper alternatives, why their CFO says the move could save more than 2 billion euros in efficiency gains over the next two years even as overall AI spending rises, and how this works like a flat rate plumber who charges $300 to fix a leak no matter which parts go in.
Chapters

00:00:00 The Cake Mix Paradox: Why Effort Matters in the AI Age
00:11:03 The Three Questions: Deciding Which Eggs to Keep Cracking Yourself
00:16:42 The Myth of Permanent Jobs: What Construction Workers Already Know
00:21:42 SAP's $2 Billion AI Efficiency Play: Swapping Models Without Cutting Spending
00:24:15 The AI Model Commodity Shift: What It Means for Workers, Vendors, and Customers
00:26:42 Jevons Paradox Returns: Why Cheaper AI Means More AI, Not Less