How to Do Research With AI: An Austrian Capital Theory Approach

Scholarly outputs are the final goods of a heterogeneous, multi‐stage, temporally extended production process. Austrian capital theory provides a way to analyse how artificial intelligence changes that process. This paper conceptualises large language models and related tools not as labour substitutes but as a portfolio of capital goods whose productive role depends on how researchers (as entrepreneurs) specify and integrate them into a plan. AI adoption deepens and rearranges the capital structure of research. Because complementarity is plan‐relative, the effects of AI are intrinsically heterogeneous across researchers and fields, concentrating benefits where AI fills “holes” in an existing workflow and where complementary human capital is strongest. The framework yields practical and institutional implications, including changes to coauthorship incentives, disruptions to writing quality as a screening signal and a coordination problem as evaluation and peer‐review institutions adjust to a newly capital‐deepened production process.