What Will It Mean to Be An Expert in 2030? | Chris Myers of Johns Hopkins University

In this episode of the Smarter by Design podcast, I’m joined by Christopher Myers, Peetz Family Professor of Leadership and Faculty Director of the Center for Innovative Leadership at Johns Hopkins University, for a wide-ranging conversation about expertise, learning, and how AI is reshaping knowledge-intensive organizations like healthcare providers and AEC firms.Christopher studies how professionals learn from experience and from one another. Together, we explore what happens when AI becomes extraordinarily good at synthesizing information but still struggles with judgment, context, and tacit nuance. In fields like healthcare, architecture, and engineering—where decisions carry real liability and long feedback loops—the distinction between synthesis and judgment matters deeply.We examine a growing paradox: In the near future AI may be able to perform much of the “junior work” that once served as the apprenticeship path to becoming an expert. If AI creates the slide decks, drafts the notes, checks the drawings, and summarizes the literature, how do emerging professionals gain the reps, exposure, and judgment that traditionally came from doing those tasks? And if organizations eliminate junior roles in pursuit of efficiency, what happens to the future pipeline of senior expertise?The conversation also explores how expertise actually forms. Christopher shares his research on vicarious learning—how professionals learn from stories, informal conversations, and communities of practice—and why hybrid work may be compressing or eroding some of those learning opportunities. We discuss why informal knowledge sharing sometimes outperforms formal systems, and how simulation and AI-powered scenarios may offer new ways to scale apprenticeship in the future.At the center of the episode is a deeper question: What will it mean to be an expert in 2030? As AI raises the “standard of care” across industries, leaders must rethink not only how work gets done, but how judgment, responsibility, and organizational intelligence are developed over time.If you’re leading an AEC firm and wondering how AI will affect your talent pipeline, apprenticeship model, or long-term expertise, this conversation offers a thoughtful and research-backed perspective on what may lie ahead.GuestChristopher Myers, Peetz Family Professor of Leadership and Faculty Director of the Center for Innovative Leadership at Johns Hopkins UniversityChristopher G. Myers, PhD is the inaugural Peetz Family Professor of Leadership, Professor of Management and (jointly) of Medicine and Public Health, and the founding Faculty Director of the Center for Innovative Leadership at the Johns Hopkins University Carey Business School. His research and teaching focus on individual learning, leadership development, and innovation, with particular attention to how people learn vicariously and share knowledge in health care organizations and other knowledge-intensive work environments. Chris’s research has been published in premier academic journals in the fields of management and medicine and he has received a variety of awards and honors for his work, including being named by Poets &amp; Quants as one of the top 40 business school professors under 40 world-wide. Prior to joining Johns Hopkins University, Chris was on the faculty of the Harvard Business School and received his PhD from the University of Michigan Ross School of Business.CreditsHost: Christopher ParsonsExecutive Producers: Denise Parsons, Christopher ParsonsEditor: Coe HoeksemaTheme Song: “We Took the BART” — Written and Performed by The ParentsEpisode ResourcesResearch and Publications by Christopher MyersInformal Peer Interaction and Practice Type as Predictors of Physician Performance on Maintenance of Certification Examinations, Valentine et al. (JAMA Surgery, 2014)Chapters(00:00) Introduction(02:42) Predictions for Knowledge &amp; Learning Organizations in 2030(05:45) AI’s Strength in Synthesis and Limits in Creativity(10:11) Human Judgement, Context, and the Missing AI Feedback Loop(14:23) Beyond Synthesis: When You Still Need Dialogue and Pushback(17:12) How AI Changes Standard of Care Expectations in Healthcare(22:33) Why Medical Education Still Tests “Old” Expertise(26:03) How Clinicians Actually Learn: ChatGPT, Google, and YouTube(28:07) Why “Regular YouTube” Sometimes Beats Internal KM Systems</p