Does AI-Driven Scientific Output Lead to Technological Innovation? A Scientometric and Patent Citation Analysis Approach

Hooman Shababi

doi:10.21061/jts.449

Does AI-Driven Scientific Output Lead to Technological Innovation? A Scientometric and Patent Citation Analysis Approach

Journal of Technology Studies

Volume 51 (2026): Issue 1

By: Hooman Shababi

Open Access

|Jul 2026

Abstract

The integration of artificial intelligence (AI) into scientific research is transforming knowledge production, yet its impact on technological innovation remains underexplored. This study examines how AI-assisted research contributes to downstream innovation by analyzing publication and patent citation data from 2023 to 2025. Focusing on fields like biomedical sciences, materials science, and energy, we use data from the Web of Science, PATSTAT, and Google Patents to trace forward patent citations of AI-driven scientific papers. Results show that while AI accelerates research output and promotes interdisciplinarity, only a portion of this output leads to technological applications. Key factors influencing this translation include the research domain, institutional context, and industry collaboration. The study provides empirical insights into how AI-enabled science can foster innovation and offers recommendations for science and technology policy aimed at maximizing the societal benefits of AI-assisted research.

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