Investigating Market and Regulatory Forces Shaping Artificial Intelligence Adoptions

Chrissann R. Ruehle
Muma Business Review  •  Volume 4  •  2020  •  pp. 177-192
The Artificial Intelligence (AI) industry has experienced tremendous growth in recent years. Consequently, there has been considerable hype, interest, and even misinformation in the media regarding this emergent technology. Practitioners and academics alike are interested in learning how this market functions in order to make evidence-based decisions regarding its adoption. The purpose of this manuscript is to perform a systematic examination of the current market dynamics as well as identify future growth opportunities for the benefit of incumbents in addition to firms seeking to enter the AI market. The primary research question is: how do market and governmental forces reportedly shape AI adoptions? Drawing on predominantly practitioner focused literature, along with several seminal academic sources, the article begins by examining and mapping stakeholders in the market. This approach allows for the identification and analysis of key stakeholders. Semiconductor and cloud computing firms play a substantive role in the AI adoption ecosystem as they wield substantial power as revealed in this analysis. Subsequently, the TOE framework, which includes the technology, organization and environmental contexts, is applied in order to understand the role of these forces in shaping the AI market. This analysis demonstrates that large firms have a significant competitive advantage due to their extensive data collection and management capabilities in addition to attracting data scientists and high performing analytics professionals. Large firms are actively acquiring small and medium sized AI businesses in order to expand their offerings, particularly in dynamic emerging fields such as facial recognition technology and deep learning.
Artificial Intelligence, Machine Learning, Organizational Ethics, AI Adoption, Technology-Organization-Environment Framework, TOE Framework
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