Artificial Intelligence (AI) Use in Academic Operations: Between Promise and Practice

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Artificial Intelligence (AI) Use in Academic Operations: Between Promise and Practice

Artificial Intelligence (AI) Use in Academic Operations: Between Promise and Practice

Artificial Intelligence (AI) Use in Academic Operations: Between Promise and Practice, the latest AACRAO report, made possible with the support of Coursedog, is based on data from a 60-second survey on AI use in higher education academic operations.

In September 2025, AACRAO, with the support of Coursedog, created and distributed a 60-second survey to AACRAO members regarding the use of AI in academic operations within higher education institutions. Artificial intelligence (AI) is being increasingly used for various tasks in higher education and is gaining wider acceptance. Findings from this survey aim to understand the four types of AI applications within academic operations. AACRAO asked its members to share their institutions’ approaches to AI implementation in support of academic operations, current usage patterns, and future plans. This report includes the results of the 167 responses received.

Key Data

  • 85% of respondents agree (either strongly or somewhat) that AI can help make academic operations more efficient and improve outcomes.
  • 36% of respondents indicated that the Provost or Chief Academic Officer, such as Provost or VP for Academic Affairs, holds the responsibility for decisions on AI use in academic operations.
  • 75% of survey respondents are not currently using AI in academic operations.


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Unless otherwise noted in a specific report, the AACRAO member institution size, type and control categories are based on the following definitions and sources: 
The enrollment value used to delineate the institution's size category is defined as full-time enrollment plus 1/3 of part-time enrollment and is based on the enrollment reported by the institution to the U.S. Department of Education's National Center for Education Statistics (NCES). 
Institution type and control values are also defined by and verified through NCES criteria.