AI experience: the perception of marketers on AI text-to-image generators. A qualitative approach to customer experiences of AI image generators
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2023-07-11
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en
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Abstract
This research is aimed at capturing the experience of marketers surrounding AI text-to-image generators. Following a qualitative and exploratory approach to research, this study is based on a literary review of appropriate research papers and 16 semi-structured interviews conducted among various types of marketers. This study has leveraged CX and AI text-to-image generator literature, among with the qualitative interview process, to explore 9 concepts that could impact the CX outcomes of satisfaction, loyalty and word of mouth. The hedonic value components were found to be 1) Job insecurity, 2) Aesthetic experience, 3) Sense of discovery, 4) Fear of the unknown. The utilitarian value components were found to be 5) Ease of use and 6) Usefulness. The customer characteristics that influenced CX were 7) Technology readiness, 8) Risk perception and 9) Self-efficacy. Findings of this research contribute to CX literature by exploring effects of hedonic and utilitarian value on CX outcomes, emotions and cognitions on CX and customer characteristics on CX, all in the novel context of marketers experiencing AI TTIG’s. Findings include advice on understanding the implications of technology readiness in marketers, possible ways to reduce fears of AI and recommendations on dealing with aesthetic flaws of AI TTIG’s.
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Faculteit der Managementwetenschappen