Unveiling AI washing: Bridging corporate technological gaps through a cognitive dissonance lens
Zhe Sun, Yujun Wen, Liang Zhao, Intesar Almugren, Aradhana Galgotia
Jilin University University of Strathclyde Princess Nourah bint Abdulrahman University Galgotias University
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摘要与影响
This study utilizes Cognitive Dissonance Theory to empirically investigate how ‘AI washing’, the discrepancy between AI narratives and actual capabilities, affects the corporate technological gap. Using panel data from China's A-share listed firms (2007–2022), the findings establish a significant inverted U-shaped relationship between ‘AI washing’ and the technological gap. Mediation analysis confirms this relationship is channeled through both internal R&D investment and industry-level R&D investment. Moderation analysis reveals that strong AI-enabled participatory learning capability flattens the inverted U-curve, indicating earlier corrective action. Conversely, high investor sentiment is shown to steepen the curve. Furthermore, the nonlinear effect is subdued for firms in national AI pilot zones or high-technology-intensive industries. This research advances ‘AI washing’ literature through quantitative analysis, extends Cognitive Dissonance Theory to the domain of technology strategy, and offers empirical insights for responsible AI governance. • Applies cognitive dissonance theory to analyze AI washing's impact on the corporate technological gap. • AI washing initially widens the technological gap by stifling innovation but narrows it past a threshold as firms adapt. • Firm- and industry-level R&D investments mediate the relationship between AI washing and the technological gap. • Stronger AI knowledge absorptive and participatory learning capabilities result in a flatter inverted U-shaped curve. • Effects vary by investor sentiment, firm traits, and regulations, with persistent AI washing potentially hindering sustainable progress.
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