ScholarWorks@성균관대학교

초록

The rise of generative artificial intelligence (AI) represents a new marketing phenomenon, particularly in the context of phygital ecosystems, where customers experience value through the convergence of physical and digital worlds. Given the novelty of generative AI and phygital in marketing and the scarcity of academic literature, but the readily available thought leadership of practitioners, this article conducts a review of practice articles to explore the impact of generative AI on phygital customer experiences, thereby revealing both its bright and dark sides. To do so, the review adopts the experiential research methodology using experiential screening of practice articles, guided by the phygital research paradigm and the sensemaking approach of scanning, sensing, and substantiating. In doing so, the review identifies that the bright sides of deploying generative AI for phygital customer experiences include creativity and innovation through analysis of market trends and customer feedback, generation of insights that guide new solutions, product and service innovation, and enhanced creative outputs in phygital marketing; data security and ethical considerations supported by predictive analytics that enable proactive issue resolution and real-time insights in phygital settings; efficiency and productivity through automation of routine tasks, focus on complex phygital interactions, quicker response times, improved customer satisfaction, and higher productivity; and personalization and engagement through tailored marketing messages and product recommendations, individualized offers, and customized experiences across phygital touchpoints that enhance engagement and satisfaction. Whereas, the dark sides emerge when outputs are inaccurate or biased and lead to misinformed phygital marketing decisions that suppress creativity and innovation and expose brands to potential brand-reputation damage; when data security and ethical concerns around privacy, transparency, and fairness heighten vulnerability to breaches and cyberattacks; when integration with phygital infrastructures and interoperability across platforms are complex and consistent quality in AI-generated responses is hard to maintain, thereby eroding efficiency and productivity; and when personalization and engagement are perceived as impersonal and raise expectations, particularly for tasks that require a human touch, thereby reducing satisfaction. These bright and dark sides of generative AI for phygital customer experiences are also discussed using relevant theories, thereby providing a theoretical foundation to spur and support future research in this nascent yet promising area of marketing.

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