As AI becomes more valuable, companies need an organizational model to navigate who owns, controls, and profits from data.
September 27, 2024
Don Smith/Getty Images
The AI boom — and the growth of gen AI in particular — has introduced new points of conflict between employees and companies. Some of these have already started to play out, such as in the Writers Guild of America strike over how AI can and can’t be used in the entertainment industry. But others are still on the horizon. As AI becomes more integrated into business, high quality data for training AI becomes more valuable and a more important part of employees’ contribution. Companies need to navigate if and how employees will be compensated for their data, as well as questions such as who owns and controls that data. One potential solution is data cooperatives, an organizational model that enable individuals to pool their data with the purpose of gaining bargaining power with the companies analyzing their data. These have the potential to mutually benefit companies and employees, and build a positive, collaborative relationship around a potential future flashpoint in labor relations.
The impact of AI, and generative AI in particular, is being felt across industries. But while executives are excited about this technology’s potential, white collar workers are often wary about what it may mean for them, their jobs, and their futures. These differing perceptions are creating new tensions and presenting new challenges for both groups.
-
JP
José Parra-Moyano is a professor of Digital Strategy at the International Institute for Management Development (IMD Business School) in Switzerland. His research focuses on the management and economics of data and privacy, with a special focus on how organizations can use data analysis techniques and AI to increase their competitiveness. He is an award-wining teacher, whose research has been published in top tier academic journals.
-
AJ
Amit Joshi is a professor of AI, Analytics and Marketing Strategy at IMD, and specializes in helping organizations use artificial intelligence and develop for their big data, analytics and AI capabilities. An award-winning professor and researcher, he has extensive experience of AI and analytics driven transformations in industries such as banking, fintech, retail, services, automotive, telecoms, and pharma.
