New research proposes a framework to give workers a stake in the AI systems built on their labor.
Data portability has often been presented as a way to reduce the control digital platforms exert through exclusive access to user data. In principle: if Meta, Alphabet, Spotify, or another platform holds your data, you should be able to take it with you. The idea has mostly been discussed as a consumer protection and competition policy tool. As Brookings explains, data portability can reduce switching costs and make it easier for rival firms to compete. But generative AI raises a potentially harder, worker-centric version of the portability problem. What if instead of a collection of images, videos, playlists, and posts, your data is the accumulated record of how you do your job? This question is at the heart of “Knowledge Guilds: Sharing the Productivity Gains of AI,” co-written by HBS AI Institute associate Zoë Cullen. The authors argue that workplace AI is not simply external automation adopted by firms. Rather, it is a tool that can capture workers’ expertise and convert it into firm-owned “knowledge capital”. This creates the potential for an adoption crisis, but Cullen and her authors propose knowledge guilds as a mechanism to ensure that the people who make AI effective share meaningfully in what it produces.
Why This Matters
For business leaders and executives, this research is a call to move beyond a “harvesting” mindset toward a strategy of sustainable intelligence. Successful execution in the AI era requires a unified conversation between leadership, HR, legal, and IT departments. By exploring the idea of knowledge guilds, organizations can begin to design a social contract that recognizes workers as stakeholders in AI-enabled productivity advances, ensuring that the gains of AI are not just concentrated, but shared and incorporated into further organizational wins.
Link to the HBS AI Institute Insight Article
Link to the Research Paper
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