Unveiling AI washing : bridging corporate technological gaps through a cognitive dissonance lens

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Sun, Zhe and Wen, Yujun and Zhao, Liang and Almugren, Intesar and Galgotia, Aradhana (2026) Unveiling AI washing : bridging corporate technological gaps through a cognitive dissonance lens. Technological Forecasting and Social Change, 225. 124511. ISSN 0040-1625 (https://doi.org/10.1016/j.techfore.2025.124511)

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Abstract

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 channelled 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.

ORCID iDs

Sun, Zhe, Wen, Yujun, Zhao, Liang ORCID logoORCID: https://orcid.org/0000-0001-8481-9926, Almugren, Intesar and Galgotia, Aradhana;
CORE (COnnecting REpositories)