Why this term matters in the material In this channel's material, multidisciplinary expertise shows up as a lens for exploring AI's impact on work: as AI is positioned as a substitute for expensive labor — Mike Maples Jr.'s counter-positioning argument — value shifts away from narrow, single-domain skill and toward people who can connect several domains at once. The related coverage on AI, Jobs, and the Future of Work frames the practical payoff: identifying which of your tasks are exposed, understanding why demand for some expertise is rising rather than falling, and repositioning around the skills these sources agree are durable. How to use it When you see the term here, read it as a call to explore breadth, not just depth: combine understanding from more than one field so your work is harder to automate and easier to reposition as the economics of AI change. - Definition in context: expertise that spans more than one discipline and is applied together, not in isolation. - Why it's emphasized: AI is framed as a substitute for expensive labor, which pressures narrow, single-domain skills. - Practical use: use it to spot exposed tasks and reposition around durable, rising-demand skills.