At Texas A&M University–San Antonio, even defining what it means to have the title of “AI librarian” is a work in progress.
Kim Grotewold stepped into the role on September 1, 2025, but like many emerging positions tied to artificial intelligence, the scope is still evolving. “AI librarian” is only one part of her job. She also serves as a liaison to the education-specific programs under the College of Education and Human Development and oversees the operations of a newly launched Library Innovation Lab that provides large-format and 3D printing, laser engraving, and other materials and services.
That overlap makes it difficult to neatly define the role, but what has taken shape so far is a focus on people. Rather than trying to direct AI initiatives for the entire university, Kim’s work begins with library staff development and information literacy. Presently, her primary goal is to help library staff build confidence with AI tools so they, in turn, can support students and faculty.
In these early days, much of the work is exploratory. Kim has been facilitating workshops for faculty, staff, and students, often grounded in information and digital literacy competencies, but adapted for an AI-driven landscape.
Instead of prescribing how AI should be used, she encourages intentionality and personal responsibility. Why use it at all? What role should it play in research? Where are the ethical boundaries? Are you acknowledging AI use appropriately?
In one classroom session that included dual-enrollment high school students, she introduced AI as a brainstorming partner. Students used it to refine topics, generate keywords, and identify potential sources, then compared those results against library databases. The goal was not to replace research skills, but to sharpen them. Reflecting on processes and the differences between resources available through AI chat tools versus library databases pushes students to think critically and adapt their research strategies.
That same mindset carries into conversations with faculty, where questions around transparency and citation are becoming more urgent. As journals begin requiring disclosure of AI use, libraries are helping shape what responsible use looks like in scholarly work.
Kim is quick to point out that there are still gaps. Tools, policies, and infrastructure are developing at different speeds across the Texas A&M University System, and many campuses are still weighing costs, access, and long-term strategy. For now, much of the work is local, iterative, and sometimes uncertain.
For libraries across Texas, the emergence of roles like Kim’s signals a shift. AI isn’t just another technology to adopt. It’s something that is reshaping instruction, research, and the way libraries support their communities. And right now, there’s no single blueprint.
Kim’s approach offers a starting point: focus on your people, build awareness, and create space to experiment.
Because at this stage, being an AI librarian doesn’t mean having all the answers. It means being curious, open-minded, empathetic, and willing to learn.
