An Examination of Management of AI-triggered Organizational Threats from Communication Practitioners’ Perspective
An Examination of Management of AI-triggered Organizational Threats from Communication Practitioners’ Perspective
Wenqing Zhao (PhD candidate), Anna Rachwalski (undergraduate student), Maranda Goke, and Yan Jin (2025). "An Examination of Management of AI-triggered Organizational Threats from Communication Practitioners’ Perspective." Journal of Contingencies and Crisis Management, 33(1), e70031. http://dx.doi.org/10.1111/1468-5973.70031
Abstract: The growing demand for using AI in day-to-day work in the communication industry brings ethical threats to organisations (i.e., misinformation, discrimination and bias, lack of transparency and disclosure, privacy violation and infringement, and copyright infringement). Meanwhile, organisational communication management also faces threats posed by external AI-driven disinformation. The internal and external threats boost the urgency of strategy development for effective organisational crisis management. This study, based on an online survey of communication professionals in the US (N = 407), provides timely input to organisations on how to manage AI-related ethical threats from inside and outside by understanding the perspective of communication practitioners. Building upon extant ethical AI challenges and the theoretical framework of the problem of many hands, this study examines communication professionals' attitudes and perceptions toward both AI ethical threats and strategies proposed to manage those threats, and the predictors of their behavioural intentions regarding threat management. We found that communication practitioners have reservations about being fully transparent about AI use to their clients. To effectively address AI ethical threats, organisations need to consider building a culture of active responsibility to prevent responsibility evasion and impunity, enhancing communication practitioners' awareness and knowledge about the pitfalls of technical systems, and improving practitioners' perceived efficacy of strategies for managing AI ethical threats.
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