Research in Commotion: Measuring AI Research and Development through Conference Call Transcripts

历史 媒体研究 社会学
作者
Paul E. Soto
出处
期刊:Finance and economics discussion series [Board of Governors of the Federal Reserve System]
卷期号: (2025-011): 1-1
标识
DOI:10.17016/feds.2025.011
摘要

This paper introduces a novel measure of firm-level Artificial Intelligence (AI) Research & Development—the AIR Index—derived from the semantic similarity between earnings conference call transcripts and leading AI research papers. The AIR Index varies widely across industries, with sustained strength in computer and electronic manufacturing, and accelerating growth in computing infrastructure and educational services seen after the introduction of ChatGPT in November 2022. I find that the AIR Index is associated with an immediate increase in Tobin’s Q and can help explain the cross-section of cumulative absolute returns following the conference call, suggestive of investors valuing substantive AI discussions in the near-term. A sharp rise in the AIR Index leads to persistent increases in year-over-year capex growth, lasting about a year before tapering off, indicative of the life cycle of AI-induced capital deepening. However, I find no significant effects of AI R&D on productivity or employment. Using industry level survey data from Census, I find that recent growth in the AIR Index correlates with broader AI adoption trends. The positive association of the AIR Index with capex and valuation holds across previous time periods, suggesting that Generative AI may be the latest form of an ongoing technical innovation process, albeit at an accelerated pace.

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