Tenure, Trust, and Technology: Emory Faculty on AI in Teaching and Research

• Type of Material: Report
• Authors: Michelle Kalbeitzer, Emory University; Anoushka Mukhopadhyay, Emory University
• Language: English
• Date: 2026-05-05
• Publisher: Emory University Libraries
• Publication Version: Final Published Version
• Copyright Statement: © 2026 Michelle Kalbeitzer and Anoushka Mukhopadhyay. All rights reserved.
• License: Creative Commons Attribution 4.0 International
• Keywords: artificial intelligence, generative AI, faculty perceptions, higher education, AI in teaching, AI in research, academic integrity, AI policy, AI literacy, algorithmic bias, faculty survey, educational technology, Emory University, AI adoption, research integrity, institutional policy, ChatGPT, large language models
• Subject - Topics: Artificial intelligence -- Study and teaching (Higher); Generative artificial intelligence in higher education
• Research Categories: Education policy; Higher education; Education; Educational technology

Abstract

This white paper presents findings from a 2025 survey of 399 Emory University faculty examining perceptions and use of artificial intelligence (AI) in teaching and research contexts. Drawing on a mixed-methods design that included Likert-scale, multiple-choice, and open-ended questions, the study identifies five key findings: (1) faculty familiarity with AI is a strong predictor of willingness to adopt AI tools; (2) classroom integrity and the student-faculty relationship are primary concerns in teaching contexts; (3) algorithm bias, accuracy, and research integrity are the dominant concerns in research contexts; (4) professional experience shapes AI adoption patterns in counterintuitive ways, with senior faculty exhibiting more values-based resistance than early-career colleagues; and (5) approximately 80% of respondents support institutional AI policy, with a clear preference for guidance and training over mandates. Findings suggest that AI literacy programming, discipline-specific policy guidance, and ongoing dialogue are essential to supporting responsible AI integration across the institution. This report is intended to serve as a baseline for tracking faculty perspectives as the AI landscape continues to evolve.