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A senior Texas A&M University System official testing a new artificial intelligence tool this fall asked it to find how many courses discuss feminism at one of its regional universities. Each time she asked in a slightly different way, she got a different number.

“Either the tool is learning from my previous queries,” Texas A&M system’s chief strategy officer Korry Castillo told colleagues in an email, “or we need to fine tune our requests to get the best results.”

It was Sept. 25, and Castillo was trying to deliver on a promise Chancellor Glenn Hegar and the Board of Regents had already made: to audit courses across all of the system’s 12 universities after conservative outrage over a gender-identity lesson at the flagship campus intensified earlier that month, leading to the professor’s firing and the university president’s resignation.

Texas A&M officials said the controversy stemmed from the course’s content not aligning with its description in the university’s course catalog and framed the audit as a way to ensure students knew what they were signing up for. As other public universities came under similar scrutiny and began preparing to comply with a new state law that gives governor-appointed regents more authority over curricula, they, too, announced audits.

Records obtained by The Texas Tribune offer a first look at how Texas universities are experimenting with AI to conduct those reviews.

At Texas A&M, internal emails show staff are using AI software to search syllabi and course descriptions for words that could raise concerns under new system policies restricting how faculty teach about race and gender.

At Texas State, memos show administrators are suggesting faculty use an AI writing assistant to revise course descriptions. They urged professors to drop words such as “challenging,” “dismantling” and “decolonizing” and to rename courses with titles like “Combating Racism in Healthcare” to something university officials consider more neutral like “Race and Public Health in America.”

While school officials describe the efforts as an innovative approach that fosters transparency and accountability, AI experts say these systems do not actually analyze or understand course content, instead generating answers that sound right based on patterns in their training data.

That means small changes in how a question is phrased can lead to different results, they said, making the systems unreliable for deciding whether a class matches its official description. They warned that using AI this way could lead to courses being flagged over isolated words and further shift control of teaching away from faculty and toward administrators.

“I’m not convinced this is about serving students or cleaning up........

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