Future Ready Leadership With Jacob Morgan

April 14, 2026: The Stanford AI Index shows generative AI has hit 53% global adoption — faster than any technology in history — but also reveals a 50-point gap between expert optimism and public fear about jobs. An AI agent in San Francisco opened a store, hired staff, negotiated with vendors, and forgot to schedule anyone on opening day. Meta is building a photorealistic clone of Mark Zuckerberg to interact with employees — raising hard questions about leadership presence at scale. And a new Bloomberg Businessweek investigation finds college students are skipping the broken entry-level job market entirely and founding AI companies instead. Jacob unpacks what each story actually signals for leaders, organizations, and the future of work.

Companies today are rushing to build an AI strategy, but they often forget to create a human strategy to match it. As technology takes over daily tasks, keeping the human element alive at work is a huge challenge for business leaders.
In this episode, Kathie Patterson, Chief Human Resources Officer at Ally, joins us to explore how to balance new AI tools with human emotional intelligence. We uncover how to roll out AI to employees for better efficiency while making sure a human is always in the loop for the moments that truly matter.
Kathie explains why leaders need strong EQ and training in crucial conversations to handle conflicts, since frustrating moments like getting stuck in dead-end phone trees prove that people still crave real human connection during stressful times. We also explore balancing workplace empathy with business accountability, offering real support like mental health and fertility benefits without treating adult employees like children.
Finally, we look at how to adapt to generational shifts, like Gen Z entering the workplace, and the risks of using AI for HR tasks like hiring and promotions. CHROs will find this episode essential for building a future-ready culture that embraces both high-tech tools and deep human connection.
Watch the full video on YouTube
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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: 8EXlaws.com

April 10, 2026: Andreessen Horowitz just released hard data showing nearly a third of the Fortune 500 has live AI deployments — and the pattern underneath reveals exactly which jobs and functions are next in line. Then: Gallup says global employee engagement just hit a five-year low, and I'm going to argue that metric is fundamentally broken and why your board should stop asking for it. Plus, Microsoft Research coins a term you'll be using by tomorrow — "workslop" — and reveals the hidden social penalty employees face for using AI openly. McKinsey adds a critical wrinkle: your most AI-fluent employees are your biggest flight risk. And a new Wharton study finds that 80% of people follow wrong AI answers with complete confidence — and feel better about themselves while doing it.

April 9, 2026: Meta had a big week. The company launched Muse Spark, its first model from a completely rebuilt AI team, framing it as the opening move toward personal superintelligence. And internally, employees were competing on a secret leaderboard tracking exactly how many AI tokens each of the company's 85,000 workers consumed — with titles like "Token Legend" awarded to the top users. Their CEO didn't crack the top 250. We break down what both stories mean for the future of work, plus why Lowe's just committed $250 million to skilled trades training and why OpenAI and Anthropic are building AI models too dangerous to release to the public.

April 8, 2026: A major new survey finds that 44% of Gen Z workers admit to actively sabotaging their company's AI rollout — and the real story isn't what you think. Second, Anthropic just announced Project Glasswing, a landmark cybersecurity initiative built around an unreleased AI model that autonomously found vulnerabilities hiding in critical software for up to 27 years — flaws that thousands of expert researchers missed entirely. And third, a New York Times investigation reveals Google's AI Overviews are wrong one in ten times — which sounds small until you do the math at five trillion searches a year. Jacob breaks down what each of these stories really means for the future of work, and why the most important insights are the ones the headlines are missing.