AI Disclosure in Strategic CSR Communication: Examining the Impact of Narratives, Source Labels, Message Transparency, and Organizational Perceptions on Behavioral Intentions

Abstract

Despite identified advantages, AI poses challenges for strategic communication practitioners when considering effective and ethical disclosure of such technologies. This study explores the labeling of AI within narrative messages about corporate social responsibility (CSR) initiatives, building on source credibility theory (SCT) and theories of narrative communication. A 2 (message type: narrative vs. expository) × 4 (source label: human, AI-assisted human, AI, no source) between-subjects online experiment (N = 277) investigates how various AI and human source labels used in narrative or expository messaging impacted stakeholder perceptions and behavioral intentions. Results indicate that AI source labels elicited lower perceived message transparency (accuracy and disclosure) and organizational transparency in comparison to human source labels but did not otherwise impact stakeholder perceptions or behavioral intentions. Moreover, exposure to narrative (vs. expository) messaging generated higher perceptions of message transparency (accuracy and clarity) and organizational transparency. Theoretically, these findings contribute to applications of narrative communication and SCT in strategic communication contexts and provide a novel examination of AI disclosure in CSR communication. Practically, these findings provide guidance for practitioners to navigate stakeholders’ responses, or lack thereof, to disclosing AI use in strategic storytelling.

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