Top 3 Faculty Uses of Gen AI

• By Rhea Kelly
• 08/26/25

A new report from Anthropic provides insights into how higher education faculty are using generative AI, both in and out of the classroom. The company analyzed 74,000 anonymized conversations from faculty around the world on its Claude.ai platform, as well as surveyed 22 faculty from Northeastern University, to provide an "empirical snapshot" of educator AI adoption in university settings, according to a news announcement.

Faculty uses of AI ranged from developing course materials and writing grant proposals to academic advising and managing administrative tasks, Anthropic said. Their top three uses were:

• Developing curricula (57%). Common requests included designing educational games, creating interactive tools, and creating multiple-choice assessment questions.
• Conducting academic research (13%). Common requests included supporting bibliometric analysis and academic database operations, implementing and interpreting statistical models, and revising academic papers based on reviewer feedback.
• Assessing student performance (7%). Common requests included providing detailed assessment feedback for student assignments, evaluating academic work using assessment criteria, and summarizing student evaluation reports.

Anthropic also analyzed how often educators utilized AI to augment their work (collaborative use such as validation, task iteration, or learning) vs. how often they used it to automate their work (delegating tasks entirely to AI). Tasks with "higher augmentation tendencies" included:

• University teaching and classroom instruction, including creating educational materials and practice problems (77.4% augmentation);
• Writing grant proposals to secure external research funding (70.0% augmentation);
• Academic advising and student organization mentorship (67.5% augmentation); and
• Supervising student academic work (66.9% augmentation).

Tasks with "higher automation tendencies" included:

• Managing educational institution finances and fundraising (65.0% automation);
• Maintaining student records and evaluating academic performance (48.9% automation); and
• Managing academic admissions and enrollment (44.7% automation).

The use of AI for automated grading remains concerning, Anthropic noted. "In our Claude.ai data, teachers used AI for grading and evaluation less frequently than other uses, but when they did, 48.9% of the time they used it in an automation-heavy way. That’s despite educator concerns about automating assessment tasks, as well as our surveyed faculty rating it as the area where they felt AI was least effective…. This disconnect — between what's being attempted and what's viewed as appropriate — highlights the ongoing struggle to balance efficiency gains with educational quality and ethical considerations."

The full report is available here on the Anthropic site.