The DOI matches its Crossref record; 73 of the 74 references it cites were found in a registry or an index, and 1 are not checked yet.
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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Majerová, J., Nadányiová, M., & Pátík, L. (2024) · Intellectual Economics · doi:10.13165/ie-25-19-2-06 · Cited by 5
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Corporate AI communication: Public responses, organizational practice, and governance in Korea
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Do “AI-assisted” labels reduce perceived quality of scenarios? An exploratory experimental study
Malekifar, F. (2026) · European Journal of Futures Research · doi:10.1186/s40309-026-00301-y
The Effect of AI Labeling on the Spread and Governance of AIGC Misinformation
吴联仁, Yu, G., Yang, P., Song, J., & Qi, J. (2026) · Lecture notes in computer science · doi:10.1007/978-981-92-6913-6_18
Metadata
- Authors
- Buckley, C., Norman, M., Troy, C., Yang, Y., Bao, J., Overton, H. K., & Jung, Y.
- Affiliations
- University of Florida (US)
- Pennsylvania State University (US)
- Corresponding author
- Buckley, C.
- Venue
- International Journal of Strategic Communication
- Publisher
- Informa UK Limited
- Published
- 2025-07-06
- Volume
- 19
- Issue
- 5
- Pages
- 696-719
- ISSN
- 1553-118X (ISSN-L)
- 1553-1198
- OpenAlex
- W4412097654
- Cited by
- 12
- References
- 73
- Citations by year
- 2026: 11
- FWCI
- 11.41
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Strategic Communication (publishedVersion)
- Funders
- Arthur W. Page Center for Integrity in Public Communication
- Topics
- Social Sciences › Communication › Public Relations and Crisis Communication
- Social Sciences › Business, Management and Accounting › Strategy and Management › Corporate Social Responsibility Reporting
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Keywords
- AI disclosure, CSR communication, organizational transparency, narrative communication, source credibility theory, behavioral intention, stakeholder perspectives, strategic storytelling
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