The Digital Data Design Institute at Harvard invites individuals to embark on a journey into the future of business across industries and sectors. This collaborative effort bridges the intellectual chasm between academic research and industry practitioners to scrutinize innovative operating models and business models that are redefining traditional business paradigms that succeed in the age of AI and beyond. We delve into the intricate dynamics of digitalization, ecosystem-driven strategies, and platform-centric approaches that are shaping the contemporary business landscape. Together, we explore strategies and insights poised to empower organizations to excel in the ever-evolving world of commerce.
If AI can accept light supervision and then be off and running, what does it mean for how leaders and organizations design work, govern risk, and account for value? Drawing on perspectives from Jen Stave Jen Stave , Executive Director of the Digital Data Design (D^3) Institute at Harvard, Columbia Business School’s Stephan Meier, and […]
The disconnect between AI’s transformative potential and the actual scale of implementation represents one of today’s most significant organizational challenges. In their new article for the Harvard Business Review, “A Guide to Building Change Resilience in the Age of AI,” Karim Lakhani, Dorothy and Michael Hintze Professor of Business Administration at Harvard Business School and […]
As Gen AI technology continues to rapidly evolve and LLMs are integrated into more and more applications, questions of trustworthiness and ethical alignment become increasingly crucial. In the recent study “Generalizing Trust: Weak-to-Strong Trustworthiness in Language Models,” authors Martin Pawelczyk, postdoctoral researcher at Harvard working on trustworthy AI; Lillian Sun, undergraduate student at Harvard studying […]
As generative AI transforms the business landscape, a concerning trend demands immediate attention from executives and policymakers alike. In the recent Harvard Business School (HBS) working paper, “Global Evidence on Gender Gaps and Generative AI,” authors Nicholas G. Otis, PhD candidate at the Berkeley Haas School of Business; Solène Delecourt, Assistant Professor at the Berkeley […]
