Embedding library collections into reading lists in the age of Academic AI

Turning reading lists into a strategic advantage for academic libraries

Academic libraries invest heavily in collections that support teaching and learning. Yet many of those resources never appear on course syllabi. Faculty work under tight timelines, rely on familiar sources, and often prepare course materials outside library systems. The result is underused library collections, delayed access for students, higher costs and inconsistent copyright compliance.

A new global study about the impact of Academic AI examined how libraries are addressing this gap by embedding the library into the syllabus and course preparation process. The findings suggest that when reading list solutions align with existing faculty workflows, libraries can improve access and affordability while extending their reach across more courses.

Why the syllabus matters more than ever
The syllabus is where decisions about course materials are made. It determines what students read, how they access materials, and what they pay. For libraries, it is also the point at which collections either become part of the curriculum or remain separate from it.

Meeting faculty where they already work
Faculty adoption depends largely on ease of use. Tools that require instructors to change how they prepare courses often face resistance. With the Leganto Syllabus Assistant processing, instructors can upload a syllabus and automatically generate a structured, editable reading list. References are identified, matched against library collections, and linked for student access, without requiring faculty to adopt new workflows or rethink how they teach.

As Sarah Bateup shared:

“Leganto speaks for itself. Lecturers take one look and get it immediately. It is so much more efficient than what we had before.”
Sarah Bateup, Faculty Librarian, Health Sciences and Medicine, Bond University

Scaling support without sacrificing professional review
Course readiness during peak periods remains a challenge for many libraries. Manually reviewing syllabi and building reading lists limits how many courses can be supported and can delay access for students.

The Academic AI Impact Study found that introducing AI at the most labor-intensive stages increased capacity significantly:

Libraries reported supporting two to four times more courses
50 to 60 percent of reading lists were available immediately after AI processing
70 to 90 percent of AI-generated outputs were accepted with only minor edits

Professional review remains central to the process. Librarians validate matches, confirm licensing, and apply their expertise where it adds the most value.

As Sarah Bateup commented:

“The Leganto solution has encouraged us to share ideas and best practices and has optimized our collaboration, all of which has made a big difference.”
Sarah Bateup, Faculty Librarian, Health Sciences and Medicine, Bond University

Improving affordability and access for students
When library-licensed and open resources are embedded directly into reading lists, students encounter fewer unexpected costs and gain earlier visibility into required materials. Centralized access also reduces confusion created by scattered links and personal file uploads.

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Turning syllabi into measurable library impact
Libraries already hold much of the content students need. The challenge is connecting those collections to the curriculum at scale. This whitepaper presents research-based findings from a global study, documented library outcomes, and practical insight into how modern reading list solutions can strengthen the library’s role in teaching and learning.

Download the whitepaper to explore the full findings and see how libraries are placing reading lists at the center of academic experience.