Enhancing the efficiency of R&D project IP management in the context of digital transformation

The article examines the transformation of IP management in R&D projects within a large industrial company amid digital transformation and the rapid growth of scientific and technical information. The aim of the study is to show how the integration of patent analytics, language models, and expert verification against primary sources changes the role of the IP function from a controlling unit to a proactive participant in technological and business decision-making. The research materials include corporate practices of IP support for R&D projects, results of patent information studies, industry and academic publications, and internal cases related to search and analytical tasks. The methods combine a case-study approach, structural and functional analysis of IP support processes, expert interviews with developers, and a comparative applied assessment of digital tools using operational criteria such as the quality of information structuring, the speed of primary analytics, reproducibility of results, and verification requirements. The scientific novelty lies in describing an end-to-end scenario for using language models in IP support for R&D, from data aggregation and initial semantic interpretation to the generation of analytical hypotheses and mandatory validation of findings against patents and scientific publications. The findings show that systematic use of these tools accelerates analytical cycles, improves problem framing, enables earlier identification of legal and commercial risks, and expands the contribution of IP managers to project IP strategy. The article may be useful for IP managers, R&D executives, technology experts, patent analysts, and corporate innovation teams.

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