@article{MonodLissillourKoesteretal.2022,
  author    = {Monod, Emmanuel and Lissillour, Raphael and K{\"o}ster, Antonia and Jiayin, Qi},
  title     = {Does AI control or support?},
  series = {Journal of decision systems},
  volume    = {32},
  journal   = {Journal of decision systems},
  number    = {3},
  publisher = {Taylor \& Francis},
  address   = {Abingdon},
  issn      = {1246-0125},
  doi       = {10.1080/12460125.2022.2066051},
  pages     = {542 -- 565},
  year      = {2022},
  abstract  = {Many companies are currently investing in artificial intelligence (AI) because of its potential to increase customer satisfaction or financial performance. However, the success rates in implementing AI systems are low, partly due to technology-centric approaches that neglect work practices. This study draws on Bourdieu's theory of practice to highlight the potential power shift related to AI in customer relationship management, based on the concepts field, capital, and habitus. Two longitudinal case studies were conducted to understand the power shift related to AI implementation. These two AI systems were designed with the objective to support employees. However, subsequently, their implementation changed the balance of power with a significant shift towards more management control, resulting in a devaluation of employees' work practices. The paper discusses implications for theory and practice in terms of the discrepancies and power shifts following the introduction of AI systems to support customer relationship management.},
  language  = {en}
}
@article{MonodKoesterJoyceetal.2021,
  author    = {Monod, Emmanuel and K{\"o}ster, Antonia and Joyce, Elisabeth and Khalil, Sabine and Korotkova, Nataliia},
  title     = {Digital transformation consulting},
  series = {Academy of management proceedings},
  journal   = {Academy of management proceedings},
  number    = {1},
  publisher = {Academy of Management},
  address   = {Briarcliff Manor},
  issn      = {0065-0668},
  doi       = {10.5465/AMBPP.2021.12737abstract},
  pages     = {1},
  year      = {2021},
  abstract  = {As the focus on digital transformation and its unexplored opportunities is prospering, consulting firms have also turned their attention to it. Despite this increased attention, digital transformation project failure rate remains high, thereby reaffirming the "IT productivity paradox" or "AI productivity paradox. The purpose of this paper is to holistically scrutinize the current approach of digital transformation consulting. A deductive qualitative study draws upon the Human Technology Performance model to elucidate papers on digital transformation published by four major management consulting firms in 2014-2019. Whereas the focus on customer-centricity and some measures of corporate performance is prominent in the consulting approaches, the study results have revealed several "blind spots" that are still either neglected or poorly covered. Three main blind spots are particularly prominent from the analysis. First of all, consulting firms often apply a "one size fits all" approach, thereby neglecting contextual factors, such as age, size, or industry. Secondly, they neglect process level in the return on investment of IT. Thirdly, the suitability of IS development methods remains poorly considered. Hence, the paper argues that, while consulting firms purport to support digital transformation exigences and efforts, they, in fact, adhere to traditional approaches to business consulting.},
  language  = {en}
}