Paper Type

Complete

Paper Number

1387

Description

Artificial intelligence promises great potential to change, modify and enhance processes, products, and business models. Yet, many organizations struggle to leverage those potentials as they are not able to successfully implement AI technologies. While previous literature has already revealed success factors that are important to be considered when implementing AI projects, academia still lacks a sufficient overview in this field. With this background, this paper reviews existing literature on success factors related to the adop- tion of AI and provides a structured overview of 36 factors that have already been investigated by previous scholars. Specifically, we draw from the Technology-Organization-Environment (TOE) framework and reveal 12 factors related to the technological dimensions, 13 related to the organizational dimension, and 11 related to the environmental dimensions. Our results can help scholars and practitioners to include those factors in theory development and to implement AI projects more successfully.

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Aug 9th, 12:00 AM

Success Factors for the Adoption of Artificial Intelligence in Organizations: A Literature Review

Artificial intelligence promises great potential to change, modify and enhance processes, products, and business models. Yet, many organizations struggle to leverage those potentials as they are not able to successfully implement AI technologies. While previous literature has already revealed success factors that are important to be considered when implementing AI projects, academia still lacks a sufficient overview in this field. With this background, this paper reviews existing literature on success factors related to the adop- tion of AI and provides a structured overview of 36 factors that have already been investigated by previous scholars. Specifically, we draw from the Technology-Organization-Environment (TOE) framework and reveal 12 factors related to the technological dimensions, 13 related to the organizational dimension, and 11 related to the environmental dimensions. Our results can help scholars and practitioners to include those factors in theory development and to implement AI projects more successfully.

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