Related Experiment Video
Updated: Jan 18, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Exploring the Role of Artificial Intelligence in Evidence Synthesis: Insights From the CORE Information Retrieval
Claire H Eastaugh1,2, Madeleine Still1,2, Fiona R Beyer1,2
1NIHR Innovation Observatory Newcastle University Newcastle-upon-Tyne UK.
Introduction:
Information retrieval is essential for evidence synthesis, but developing search strategies can be labor-intensive and time-consuming. Automating these processes would be of benefit and interest, though it is unclear if Information Specialists (IS) are willing to adopt artificial intelligence (AI) methodologies or how they currently use them. In January 2025, the NIHR Innovation Observatory and NIHR Methodology Incubator for Applied Health and Care Research co-sponsored the inaugural CORE Information Retrieval Forum, where attendees discussed AI's role in information retrieval.
Methods:
The CORE Information Retrieval Forum hosted a Knowledge Café. Participation was voluntary, and attendees could choose one of six event-themed discussion tables including AI. To support each discussion, a QR code linking to a virtual collaboration tool (Padlet; padlet.com) and a poster in the exhibition space were available throughout the day for attendee contributions.
Results:
The CORE Information Retrieval Forum was attended by 131 IS from nine different types of organizations, with most from the UK and ten countries represented overall. Among the six discussion points available in the Knowledge Café, the AI table was the most popular, receiving the highest number of contributions (n = 49). Following the Forum, contributions to the AI topic were categorized into four themes: critical perception (n = 21), current uses (n = 19), specific tools (n = 2), and training wants/needs (n = 7).
Conclusions:
While there are critical perspectives on the integration of AI in the IS space, this is not due to a reluctance to adapt and adopt but from a need for structure, education, training, ethical guidance, and systems to support the responsible use and transparency of AI. There is interest in automating repetitive and time-consuming tasks, but attendees reported a lack of appropriate supporting tools. More work is required to identify the suitability of currently available tools and their potential to complement the work conducted by IS.
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