Despite its many limitations, peer review is the most preferred research assessment scheme for research proposal assessment at the individual level. Although scientometric assessment offers effective assessment frameworks, certain limitations, including the proven and potential misuse of scientometric indicators, hinder its wide adoption. Informed peer review is viewed as an effective way of harnessing the advantages of peer review and scientometric/quantitative assessment wherein one may complement the limitations of the other. Informed peer review frameworks are still prone to many inherent challenges in scientometric assessment and peer review. The importance of intelligent review frameworks that can be more advanced and effective than informed review frameworks lies there. With the advent of AI and generative AI (GenAI), a plethora of opportunities are available to convert informed peer review frameworks to intelligent review frameworks but not without challenges and concerns. In this work, we discuss the possible opportunities for effective AI intervention in an existing informed peer review framework to transform it into an intelligent review framework. Although the selected existing informed peer review framework emphasized the ‘novelty first’ policy, it did not provide any means or guidelines to execute it. The proposed conceptual ‘intelligent review framework’ addresses this very well by exploring the effective use of AI/ML techniques for the process and is envisioned to have the flexibility to adapt to future technological developments in AI, GenAI, etc. Possible challenges and a roadmap for possible evolution with anticipated technological changes, etc., are also discussed.
Lathabai et al. (2026) studied this question.