M. Dalbert Ma

I am a doctoral candidate in Strategy & Entrepreneurship at London Business School. My research examines how AI relates to canonical questions in strategy: how firms organize work, how knowledge and decision rights are allocated - now between humans and AI - and how competitive advantage is created and sustained. I study these questions in frontier AI deployments, from autonomous logistics to knowledge work, combining proprietary operational data with formal modeling.

My job market paper examines what happens when AI consolidates coordination within firms, revealing a structural tradeoff between productivity and resilience. At the 2026 AOM Annual Meeting, it received the Robert J. Litschert Best Doctoral Student Paper Award and the STR Division Best Paper Award, and was named a top-three Finalist for the William H. Newman Award. It has also been nominated for the 2026 SMS Annual Conference PhD Paper Prize. I have presented my work at Wharton, MIT, Harvard, Columbia, and Duke.

My work on generative AI and the architecture of knowledge work is under revision (R&R) at the Strategic Entrepreneurship Journal. I have published in California Management Review and Forbes, my research has been featured in Fortune, and my work on the competitive implications of generative AI has informed UK policy. My research has been supported by the Institute of Entrepreneurship and Private Capital and the Noorjehan Pirani PhD Fellowship Award.

My dissertation committee is Michael G. Jacobides (chair), Keyvan Vakili, and Francisco Brahm.

I am on the 2026/2027 academic job market.

Feel free to connect with me over email: dma@london.edu