Choose the human path for AI
To realize the greatest gains from artificial intelligence, we must make the future of work more human, not less.
Faculty
Kate Kellogg is the David J. McGrath jr Professor of Management and Innovation, a Professor of Business Administration at the MIT Sloan School of Management.
Kate's research focuses on helping knowledge workers and organizations develop and implement Predictive and Generative AI products, on-the-ground in everyday work, to improve decision making, collaboration, and learning. She shows how organizations can gain user acceptance and effective use of intelligent products and services by including users in the technology design process, providing training to give employees the skills they need to work with intelligent technologies, and designing the technologies with employees in mind.
She has authored dozens of articles that have appeared in top journals across the fields of management, organization studies, healthcare, sociology, work and employment, and information systems research. Her research has won awards from the Academy of Management, the American Sociological Association, the Alfred P. Sloan Foundation, the Institute for Operations Research and the Management Sciences, and the National Science Foundation.
Over the past decade, Kate has partnered with for-profit and not-for-profit organizations to help improve collaboration among diverse experts, use technologies to improve internal knowledge sharing, and manage the human aspects of new technology implementation in order to thrive in fast-paced and uncertain contexts.
Before coming to MIT Sloan, Kate worked as a management consultant for Bain & Company and for Health Advances. She received her PhD in organization studies from MIT, her MBA from Harvard, and her BA from Dartmouth in biology and psychology.
Featured Publication
"A Field Guide to Deploying AI Agents in Clinical Practice."Gallifant, Jack, Katherine C. Kellogg et al, Working Paper. 2025. SSRN.
Featured Publication
"Cyborgs, Centaurs and Self-Automators: The Three Modes of Human-GenAI Knowledge Work and Their Implications for Skilling and the Future of Expertise."Randazzo, Steven, Katherine C. Kellogg, Fabrizio Dell'Acqua, Ethan R. Mollick, François Candelon, Karim R. Lakhani, and Lila Lifshitz-Assaf, Working Paper. December 2025. Fortune Article. Video Summary.
Randazzo, Steven, Akshita Joshi, Katherine C. Kellogg, Hila Lifshitz, and Karim R. Lakhani. Sloan Management Review, February 3, 2026.
Kellogg, Katherine C., Danielle S. Bitterman et al, Working Paper. November 2025. SSRN.
Steven Randazzo, Akshita Joshi, Katherine C. Kellogg, Hila Lifshitz-Assaf, Fabrizio Dell'Acqua, and Karim R. Lakhani, Working Paper. October 2025.
Kellogg, Katherine C., Hila Lifshitz, Steven Randazzo, Ethan Mollick, Fabrizio Dell'Acqua, Edward McFowland III, François Candelon, and Karim R. Lakhani. Information and Organization Vol. 35, No. 1 (2025): 100559.
To realize the greatest gains from artificial intelligence, we must make the future of work more human, not less.
From MIT experts, strategies to transform skills, roles, and human potential across your organization.
Professor Kate Kellogg and co-authors wrote: "Given the need to moderate LLMs' inaccuracies, hallucinations, and other limitations, having a human in the loop is a common AI governance approach. Our finding regarding how GenAI tends to get activated into a 'power persuader' when users seek to validate output is critical, therefore, as it suggests that the loop itself has become contested ground."
Professor Kate Kellogg and co-authors wrote: "To understand how companies can truly extract value from human-AI collaboration, we conducted a field experiment with 244 consultants using GPT-4 for a complex business problem-solving task. The experiment analyzed nearly 5,000 human-AI interactions to answer a critical question: When humans collaborate with GenAI, what are they actually doing—and what should they be doing?"
Professor Kate Kellogg said: "The fascinating pattern we found in this paper is that when the consultants tried to push back, the AI didn't concede. Instead, it intensified its arguments and shifted its rhetorical strategy. It wasn't merely providing information. It was actively trying to persuade the consultants."
When it comes to emerging technologies, junior employees may not be the best teachers of their more senior colleagues.