Over 200 Research Teams Compete to Study How AI Will Reshape Workplace Collaboration
Stanford HAI and Google DeepMind launched the AI for Organizations Grand Challenge to fund research on how artificial intelligence will change the way teams work together. More than 200 academic teams from 156 universities submitted proposals exploring three areas: using AI to improve organizational alignment, measuring the human impact of AI deployment, and simulating team behavior with synthetic organizations.
A panel of judges from six universities and Google DeepMind evaluated proposals in a double-blind review process. Thirteen teams advanced to pitch their ideas before judges selected winners on May 12.
First Place: Building a "Large Coordination Model"
Yankai Wang, a PhD student at Stanford Graduate School of Business, and Amir Goldberg, a professor of organizational behavior there, won the $100,000 grand prize for their proposal to study what they call the "grammar" of coordination.
The researchers plan to analyze how successful teams coordinate work through emails, meetings, and document edits. They will use transformer machine learning architecture-the same technology behind large language models-to build a model that predicts which sequence of actions works best for a given situation.
"We want to develop a framework to help leaders understand the dynamics of coordination and make decisions grounded in organizational science instead of having to trust someone's instinct," Wang said.
Google DeepMind will implement the study in its own offices and provide computing resources, engineering support, and mentorship to the winning team.
Four Other Finalists Recognized
The challenge also recognized four finalist teams:
- Lean Curation: A team from Emory University, Cornell University, and Carnegie Mellon University proposed applying lean manufacturing principles to help organizations decide which AI-generated ideas deserve resources.
- Co-AI: Carnegie Mellon's Tepper School of Business team designed a method to measure collective intelligence in teams using AI.
- From Invisible to Accessible: Researchers from UC Berkeley's Haas School of Business and INSEAD proposed using AI recommendations to surface expertise trapped in organizational silos.
- TeamLens: Northwestern University researchers proposed linking team science theory with multimodal language models to analyze team behavior at scale and identify factors that determine success.
Broader Effort to Center Human Needs
The challenge is part of a larger initiative to ensure workplace AI adoption prioritizes human needs. Stanford HAI also announced a new AI and Organizations Lab led by Melissa Valentine, an associate professor in Stanford's management science department, with funding from Google DeepMind.
"The field of organizational science is moving faster than most people realize," said Simon Bouton, Chief Experience Officer at Google DeepMind.
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