Why is AI being introduced into evidence synthesis?
AI is being introduced because the volume and complexity of research have exceeded what can realistically be managed using fully manual processes.
In more detail
Evidence synthesis faces growing challenges from increasing research output, complex review questions and the need for timely updates. Thousands of research papers are published every week, making manual searching, screening and extraction increasingly difficult. AI offers opportunities to improve efficiency, reduce repetitive workload and support living evidence systems. However, these benefits must be balanced against risks such as bias, hallucinations and loss of transparency.
Why it matters
Understanding the problem helps prevent inappropriate uses of AI driven by novelty rather than need.
Decision rule
Adopt AI to solve clearly defined problems rather than because AI is available.
Common misconception
“AI is being adopted simply because it is fashionable.”
At a glance
- Evidence strength
- Strong
- Stakeholders
- Reviewers, Organisations, Funders
Related concepts
AI is a response to evidence overload, not an end in itself.