@inproceedings{387f7625d9124e418619c85696214efc,
title = "Artificial Intelligence Ambidexterity, Adaptive Transformation Capability, and Their Impact on Performance Under Tumultuous Times",
abstract = "Over the past two years, scholars have increasingly paid attention to firms{\textquoteright} capability to adapt to their increasingly turbulent business ecosystem environments. This study embraces the dynamic capabilities theory, uses ideas from the accelerated corporate transformation, and posits that adaptive transformation capability, driven by ambidextrous artificial intelligence (AI) use, i.e., routine and innovative use in practice, serves as a mechanism for firms to gain superior organizational performance under COVID-19. Using a composite-based structural equation model (SEM) approach, we use survey data from 257 C-level practitioners with key decision-making roles and experience in AI and digital transformation initiatives. We used this data to analyze the theorized relationships. Outcomes show that the ambidextrous use of AI positively enhances a firm{\textquoteright}s adaptive transformation capability. This capability, in turn, fully mediates the impact of AI ambidexterity on competitive performance during COVID-19. These outcomes have important theoretical and practical implications.",
keywords = "Adaptive transformation capability, Ambidexterity, Artificial intelligence, Competitive performance, Composited-based SEM, COVID-19, Dynamic capability, PLS-SEM",
author = "{van de Wetering}, Rogier and Patrick Mikalef and Denis Dennehy",
year = "2022",
month = sep,
doi = "10.1007/978-3-031-15342-6_3",
language = "English",
isbn = "978-3-031-15341-9",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "25--37",
booktitle = "The Role of Digital Technologies in Shaping the Post-Pandemic World",
address = "United States",
note = "I3E 2022 : Conference on e-Business, e-Services and e-Society, I3E 2022 ; Conference date: 13-09-2022 Through 14-09-2022",
}