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Practice co-evolution: Collaboratively embedding artificial intelligence in retail practices

Author

Listed:
  • Francesca Bonetti

    (University of the Arts London)

  • Matteo Montecchi

    (King’s College London)

  • Kirk Plangger

    (King’s College London)

  • Hope Jensen Schau

    (University of Arizona)

Abstract

Many retailers invest in artificial intelligence (AI) to improve operational efficiency or enhance customer experience. However, AI often disrupts employees’ ways of working causing them to resist change, thus threatening the successful embedding and sustained usage of the technology. Using a longitudinal, multi-site ethnographic approach combining 74 stakeholder interviews and 14 on-site retail observations over a 5-year period, this article examines how employees’ practices change when retailers invest in AI. Practice co-evolution is identified as the process that undergirds successful AI integration and enables retail employees’ sustained usage of AI. Unlike product or practice diffusion, which may be organic or fortuitous, practice co-evolution is an orchestrated, collaborative process in which a practice is co-envisioned, co-adapted, and co-(re)aligned. To be sustained, practice co-evolution must be recursive and enabled via intentional knowledge transfers. This empirically-derived recursive phasic model provides a roadmap for successful retail AI embedding, and fruitful future research avenues.

Suggested Citation

  • Francesca Bonetti & Matteo Montecchi & Kirk Plangger & Hope Jensen Schau, 2023. "Practice co-evolution: Collaboratively embedding artificial intelligence in retail practices," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 867-888, July.
    • Handle: RePEc:spr:joamsc:v:51:y:2023:i:4:d:10.1007_s11747-022-00896-1
    DOI: 10.1007/s11747-022-00896-1
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