Understanding Generative AI-mediated User Engagement with Academic Library Resources

This study investigates the emerging role of generative AI as a discovery tool for academic library resources. As students increasingly use AI platforms like ChatGPT to synthesize information and locate sources, libraries face a shift in how users encounter their collections. The researchers analyzed Google Analytics (GA4) data from Drexel University Libraries between August 2023 and October 2025 to quantify the scale of AI-mediated traffic, identify which AI platforms are driving this engagement, and determine which types of library content are most frequently surfaced by these algorithms.

The analysis reveals a clear upward trend in AI-mediated traffic to library resources, with a notable surge following the implementation of linked citation features in major AI tools. The primary platforms driving this traffic are ChatGPT, Perplexity, and Gemini. A key finding is that AI systems disproportionately surface content from institutional repositories—specifically electronic theses and dissertations. This suggests that AI retrieval mechanisms favor resources that are open access, freely available, and possess high-quality, structured metadata with stable permalinks. The study highlights that AI is effectively acting as a new, non-traditional gatekeeper for scholarly content.

This research provides an empirical foundation for understanding how AI ecosystems are reshaping information-seeking behaviors. By demonstrating that AI algorithms prioritize well-structured, open-access library materials, the findings suggest that metadata optimization and the maintenance of stable digital infrastructure are critical for institutional visibility. As AI becomes a primary starting point for academic research, libraries must move beyond viewing these tools as speculative and instead develop strategic responses to ensure their curated resources remain discoverable and authoritative within AI-generated responses.