Responsible Artificial Intelligence Attention and Firm Innovation: An Attention-Based View
Mengran Xiong, Haofeng Xu, Jiao Ji, Renxian Zuo, Yichuan Wang, Hesam Olya
kHUB post date: January 2026
Originally published: November 12, 2025 (PDMA JPIM • Vol. 43, Issue 1 • January 2026)
Read time: 75 minutes
Access the Full Article
This article draws on the attention-based view (ABV) to examine whether, how, and under what conditions top management team (TMT) attention to responsible artificial intelligence (AI) influences firm innovation. We developed a 480-word responsible AI dictionary grounded in 155 academic sources and 527 corporate case descriptions, and applied it to 2452 S&P 500 earnings call transcripts (2011–2021) using natural language processing (NLP) and large language model (LLM) techniques, yielding 2670 firm-year observations. Linking these measures to US patent data, we find that greater responsible AI attention predicts more and higher-impact patents. The effect is stronger in low-technology industries and under short-term investor pressure, while the presence of a chief technology officer (CTO) does not amplify it. Mechanism analyses reveal that responsible AI attention fosters innovation by increasing investment in AI-relevant human capital and mitigating innovation risk. Theoretically, this article enriches the AI and innovation management literature by positioning responsible AI attention as a dynamic strategic asset that mobilizes resources, reduces risk, and enables contextual adaptation. Practically, findings suggest that firms can strengthen innovation by prioritizing managerial attention to responsible AI, distributing responsibility beyond technical specialists, balancing ethical safeguards with strategic flexibility, and aligning governance with investor and industry conditions.