Vinita Alexander

Vinita Alexander studies how artificial intelligence is reshaping communication inside organizations, focusing on the gap between what organizations say about AI and what employees understand and feel. Drawing on more than 15 years in corporate communications across pharmaceutical, biotechnology, medical device, and industrial gas sectors, Alexander asks how employees make sense of AI-driven decisions and automated workflows and how communication can be designed to sustain trust and shared meaning during disruption.

Her qualitative work is grounded in interview analysis and thematic coding and situated in research on communication as design and organizational resilience. Alexander is a research assistant to Professor of Communication Marya Doerfel, building a coded review of the interorganizational networks and collaboration literature. She collaborates with Associate Professor of Communication DaJung (DJ) Woo on a study of how early-career professionals anticipate AI’s role in their future work, coding and analyzing interview data.

Alexander has held roles at Novartis, Becton Dickinson, Sun Pharmaceuticals, and Linde. She has led global internal and executive communications through major organizational change, including merger integration, enterprise restructuring, and the launch of an internal artificial intelligence platform. She has built communications functions from the ground up in organizations that had none.

Alexander’s work is developing toward a dissertation on how employees make sense of AI-driven organizational change and how communication can be designed to sustain trust through those transitions. Her longer-term goal is a career in academic research and teaching, particularly teaching that connects communication theory to the realities students will meet in organizational practice.

M.C.I.S., Communication and Information Studies, Rutgers University
M.A., English Literature, University of Kerala
B.A., English Language and Literature, Mahatma Gandhi University

Rutgers Artificial Intelligence and Data Science (RAD) Collaboratory 
Digital Ethnography Working Group