HBR IdeaCast

Disagreement is essential to better decisions—but most of us either avoid it or handle it poorly. Julia Minson is a professor of public policy at the Harvard Kennedy School of Government, and she's spent years studying disagreement and what we get wrong. She explains why intent matters less than behavior, how leaders can model “receptiveness,” and why the goal of a good disagreement isn’t to win—but to keep the conversation going. Minson is the coauthor of the HBR article "A Smarter Way to Disagree" and author of the book How to Disagree Better.

What changes need to be made for an organization to truly succeed with their AI strategy? In this four-part special series, we'll share conversations from the recent HBR Strategy Summit to help you get ahead. In this episode, Harvard Business School professor Tsedal Neeley shares what she's learned about successful AI implementation and organizational transformation, from the minimum technological capabilities needed to what it takes to overcome silos to how to transform workflows and processes to add real value. HBR editor in chief Amy Bernstein facilitates, bringing in audience questions.

As the Trump administration continues to reshape the U.S. and global business landscape, many have been left wondering why CEOs and other business leaders aren't vocalizing their views. Jeffrey Sonnenfeld is a professor at the Yale School of Management and has conversations every day with leaders of some of the country's biggest companies. He explains how many leaders are navigating the current state of affairs in the U.S., explains examples of collective action that have gotten the Trump administration to change course, and whether he thinks organizations are adjusting to this "new normal."

AI needs to be central to any organization's strategy today, but many are still not implementing the technology in the most effective ways. In this four-part special series, we'll share conversations from the recent HBR Strategy Summit to help you get ahead. In this episode, HBR editor in chief Amy Bernstein speaks with Nigel Vaz, CEO of Publicis Sapient, a digital transformation company. Vaz explains that many enterprise-wide AI initiatives fail because incentives, talent strategies and a sense of trust aren't considered thoroughly enough. He shares lessons from his front row seat to AI transformations in the last few years, and how he thinks you can create real operational value at scale.

As organizations and their employees ramp up their generative AI experimentation, leaders are facing a new problem: the rise of AI-generated "workslop," which seems okay on the surface but doesn't actually pass muster and, when passed on to colleagues, ultimately hurts team efficiency, performance, trust and morale. Kate Niederhoffer, chief scientist at BetterUp, and Jeff Hancock, professor of communication at Stanford, say that while it's tempting to blame individuals for this kind of misuse of ChatGPT and other tools, management is more often that not contributing to the workslop epidemic by putting pressure on employees to produce more and to use AI when possible without offering clear training or guidelines. Niederhoffer and Hancock offer advice on how to stem the tide of workslop. They are coauthors of the HBR articles "AI-Generated “Workslop” Is Destroying Productivity" and "Why People Create AI “Workslop”—and How to Stop It."