TY - JOUR
T1 - Analyzing the market's reaction to AI narratives in corporate filings
AU - Basnet, Anup
AU - Elias, Maxim
AU - Salganik-Shoshan, Galla
AU - Walker, Thomas
AU - Zhao, Yunfei
N1 - Publisher Copyright:
© 2025 The Authors
PY - 2025/9/1
Y1 - 2025/9/1
N2 - The recent surge in artificial intelligence (AI) interest and investment, driven by advances in large language models, has led the market to reward adopters and penalize laggards. Yet, AI integration predates this “AI gold rush,” with earlier adopters reaping significant benefits. Drawing on a 2005–2018 sample, a formative period before AI became mainstream, this paper examines how early AI adoption and its disclosure in corporate filings affect U.S. firms. Analyzing 10-K filings, we categorize AI-related mentions as actionable, speculative, or irrelevant. We establish causal links between these disclosures and firm value, with innovation and productivity as likely channels. Our findings indicate that markets distinguish between substantive AI initiatives and opportunistic signaling, swiftly pricing anticipated future gains. Actionable disclosures outlining clear implementation plans yield significant valuation benefits, particularly upon first introduction, whereas speculative or irrelevant disclosures have no impact. Moreover, firms with substantive AI disclosures subsequently increase innovation activities, evidenced by higher R&D spending and patent filings, which are a key step in a pathway to modest, lagged productivity gains and ultimately improved valuation. We further find that these innovation activities act as concurrent signals of strategic reorientation towards AI, reinforcing the market's swift positive valuation. We show that early adopters of actionable disclosures gain competitive advantages, while peers that either remain silent or offer only vague AI disclosures face market penalties. These findings highlight that the strategic communication of genuine technological initiatives can significantly impact a company's perceived value and competitive positioning in the market.
AB - The recent surge in artificial intelligence (AI) interest and investment, driven by advances in large language models, has led the market to reward adopters and penalize laggards. Yet, AI integration predates this “AI gold rush,” with earlier adopters reaping significant benefits. Drawing on a 2005–2018 sample, a formative period before AI became mainstream, this paper examines how early AI adoption and its disclosure in corporate filings affect U.S. firms. Analyzing 10-K filings, we categorize AI-related mentions as actionable, speculative, or irrelevant. We establish causal links between these disclosures and firm value, with innovation and productivity as likely channels. Our findings indicate that markets distinguish between substantive AI initiatives and opportunistic signaling, swiftly pricing anticipated future gains. Actionable disclosures outlining clear implementation plans yield significant valuation benefits, particularly upon first introduction, whereas speculative or irrelevant disclosures have no impact. Moreover, firms with substantive AI disclosures subsequently increase innovation activities, evidenced by higher R&D spending and patent filings, which are a key step in a pathway to modest, lagged productivity gains and ultimately improved valuation. We further find that these innovation activities act as concurrent signals of strategic reorientation towards AI, reinforcing the market's swift positive valuation. We show that early adopters of actionable disclosures gain competitive advantages, while peers that either remain silent or offer only vague AI disclosures face market penalties. These findings highlight that the strategic communication of genuine technological initiatives can significantly impact a company's perceived value and competitive positioning in the market.
KW - Artificial intelligence
KW - Corporate disclosure
KW - Firm value
KW - Narrative
KW - Textual analysis
UR - http://www.scopus.com/inward/record.url?scp=105007145029&partnerID=8YFLogxK
U2 - 10.1016/j.irfa.2025.104378
DO - 10.1016/j.irfa.2025.104378
M3 - Article
AN - SCOPUS:105007145029
SN - 1057-5219
VL - 105
JO - International Review of Financial Analysis
JF - International Review of Financial Analysis
M1 - 104378
ER -