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Skills, tasks, jobs, activities. These terms get used interchangeably across HR and talent acquisition, but they mean fundamentally different things. Skills are attributes of people. Tasks are components of work. Jobs are bundles of activities.
Having clarity here matters more now than ever. As AI begins reshaping how work gets done, organisations need a precise understanding of their workforce at the task level. Without clear taxonomies, it becomes impossible to understand how to effectively implement AI for automation and augmentation. So how should companies be preparing to take the most advantage of the inevitable shifts AI will bring?
My guest this week is Ben Zweig, CEO of Revelio Labs and author of the new book Job Architecture. In our conversation, he explains how to build effective taxonomies cheaply and scalably with LLMs and why this foundation is critical for navigating change. Ben also teaches Data Science and The Future of Work at NYU Stern and talks through an invaluable framework for assessing the likelihood of AI-driven job displacement.
In the interview, we discuss:
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By Matt Alder4.7
7777 ratings
Skills, tasks, jobs, activities. These terms get used interchangeably across HR and talent acquisition, but they mean fundamentally different things. Skills are attributes of people. Tasks are components of work. Jobs are bundles of activities.
Having clarity here matters more now than ever. As AI begins reshaping how work gets done, organisations need a precise understanding of their workforce at the task level. Without clear taxonomies, it becomes impossible to understand how to effectively implement AI for automation and augmentation. So how should companies be preparing to take the most advantage of the inevitable shifts AI will bring?
My guest this week is Ben Zweig, CEO of Revelio Labs and author of the new book Job Architecture. In our conversation, he explains how to build effective taxonomies cheaply and scalably with LLMs and why this foundation is critical for navigating change. Ben also teaches Data Science and The Future of Work at NYU Stern and talks through an invaluable framework for assessing the likelihood of AI-driven job displacement.
In the interview, we discuss:
Follow this podcast on Apple Podcasts.
Follow this podcast on Spotify.

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