Research
My research focuses on organizational behavior and higher education governance. Existing literature often models institutional adaptation as a rational exercise; however, I believe that financial retrenchment and artificial intelligence adoption restructure power asymmetries within the academic workforce. Consequently, I seek to identify the mechanisms by which administrative work is reorganized. By centering the academic labor market, I examine how these structural forces alter skill demand and compress professional discretion across universities.
Working Papers
Artificial Intelligence and Academic Work: Evidence from a National Survey of U.S. Faculty
Artificial intelligence (AI) has moved from a specialized research tool to a general-purpose technology that is reshaping the production, teaching, and evaluation of knowledge in higher education. Faculty now confront AI in core professional tasks such as literature reviews, data analysis, writing papers, grading, and peer review. However, there is little systematic evidence on how these tools are used or how practices vary across disciplines and career stages. A comprehensive national survey of U.S. faculty can provide the first empirical baseline on AI adoption in research, teaching, and service, thereby informing institutional policy, professional norms, and future scholarship on the transformation of academic work. We survey faculty members from 50 randomly selected R1 and R2 institutions. We study faculty usage patterns and look at emerging shared norms regarding the use of AI by faculty.
Organizational Transformations in Higher Education Through AI Adoption
Higher education administration is facing intense pressure to adapt AI into their work. However, much of the existing literature only studies AI’s impact on student learning outcomes and faculty perspectives. This study fills the gap in the organization management literature by studying AI adoption in higher education administration. It does so by integrating literature on task and skill based theories of technological change, resource dependence, and institutional isomorphism into a theoretical framework. It argues AI adoption will raise governance challenges regarding AI versus human tasks, increased vendor reliance resulting in bureaucratic, and managing legitimacy pressures to prevent symbolic AI adoption. By integrating these three theoretical lenses, it offers implications for higher education administrators on job restructuring, vendor management, and isomorphic mimicry across the sector. It also identifies areas for future research to better develop empirical frameworks to study AI adoption in higher education administration.
Power, Prestige, and Coalitions: How NC State Navigated the Politics of Budget Cuts during the Great Depression
Federal budget cuts and the approaching enrollment cliff have placed higher education institutions in a precarious position. The existing literature examines only the outcomes of budget cuts, treating them as rational and technical exercises and ignoring the political processes that shape these outcomes. This study uses NC State’s history of navigating budget cuts during the Great Depression as a case study to develop a theory on the budget-cutting process. Using archival documents, it develops a theoretical framework around three lenses: centralization of power, sub-unit prestige, and coalition building. The study found that leaders sought to centralize authority. NC State relied on the prestige arising from enrollment data and federal funding and redefined its vision and mission to safeguard key functions. The study also highlights alumni and industry mobilization as key to strengthening negotiating positions.