• EBSCO is applying AI where it can solve concrete challenges and deliver measurable value.
• Features like AI Insights and Natural Language Search are intended to make research workflows smoother without removing researcher oversight.
• Trust, transparency and authoritative data remain the foundation of EBSCO's AI strategy.

Faith, who has a background in librarianship, grounded the discussion in something familiar. AI does not lessen the value of librarians. It highlights it. Librarians have long helped people evaluate sources, ask good questions, verify information and approach research responsibly. Those same skills remain central as AI becomes a bigger part of the research process.

Napoleone noted that libraries are at different stages. Some are already exploring AI tools and gathering feedback. Others are still deciding what makes the most sense for their institution. His advice was practical: start with the use cases you are considering, then weigh them against your institution’s goals, values and priorities.

He also pointed out that AI is already showing up in research workflows, but people are using it thoughtfully. Many appreciate the speed and convenience, while recognizing the need to check sources, confirm details and stay engaged in the research process. At many institutions, guidance around AI use is still taking shape, and libraries are helping lead those conversations.

As Napoleone explained, EBSCO’s approach is focused, collaborative and continually refined. That means starting with real challenges in the research process, working closely with libraries through beta programs and conversations, and improving features over time based on feedback and results.

Faith spoke about the values guiding that work, including quality, information literacy, equity and transparency. She emphasized that trust remains central, and that trust depends on strong source material, clear documentation and thoughtful human review. 

The future of AI in research will depend not only on stronger models, but also on stronger context, stronger data and stronger verification.

The webinar highlighted two AI features EBSCO has introduced across its interfaces over the past year: AI Insights and Natural Language Search. Both are intended to make the research process easier to navigate while keeping people in control of the decisions that matter.

The webinar closed with a look ahead. Napoleone previewed additional AI capabilities on the roadmap, with more details expected in a follow-up webinar. Faith also shared examples from EBSCO’s AI Labs, where teams are exploring ideas such as citation validation, citation diversity, semantic chunk retrieval and new ways to bring trusted EBSCO search results into native AI applications.

One of the most interesting examples focused on knowledge graphs and retrieval-augmented generation, or RAG. Faith explained how authoritative linked data can help AI identify the right entities more accurately and reduce hallucinations. The larger point was clear: the future of AI in research will depend not only on stronger models, but also on stronger context, stronger data and stronger verification.

We wrapped up the webinar with 20 minutes of audience Q&A, and the conversation highlighted an important takeaway: although concerns about AI are beginning to soften, they remain very real. Attendees asked thoughtful questions about EBSCO’s approach to AI, usage trends, critical thinking, and more.