企業環境下人工智慧應用之評估與策略

Abstract

Artificial intelligence as a research topic is prevalent, and interest from the corporate world is increasing, with organizations looking into how they can incorporate AI technology. However, applying AI within companies doesn’t go with much ease. Many AI projects tend to fail, either because they are terminated early or because they didn’t meet the expectations of the decision-makers. For that reason, researchers and organizations are asking themselves whether there are ways to prevent failure or improve the odds of AI projects. Research explores important antecedents, enablers, inhibitors, and AI capabilities. There is also much research on organizational learning, project, and organizational success. With all that, one question seems to remain, what if an AI project isn’t going well and an organization is facing adversity in its undertaking? With that question, this research steers in the direction of organizational resilience and, more precisely, adaptation, anticipation, and coping capabilities. The research focused on conceptualizing this research subject and the essential related variables to answer the main research question. A theoretical framework and a measurement scale were developed to hypothesize how adaptation, specific AI-anticipation and coping capabilities can help an organization face adversity during its AI projects. At the end of this research, the measurement tool is still unvalidated. But the implication of both the framework and measurement scale is that a new research field suddenly reveals itself, providing a better understanding of potential future research. Furthermore, it led to several suggestions and advice for organizations wanting to or deploying AI.

Artificial intelligence as a research topic is prevalent, and interest from the corporate world is increasing, with organizations looking into how they can incorporate AI technology. However, applying AI within companies doesn’t go with much ease. Many AI projects tend to fail, either because they are terminated early or because they didn’t meet the expectations of the decision-makers. For that reason, researchers and organizations are asking themselves whether there are ways to prevent failure or improve the odds of AI projects. Research explores important antecedents, enablers, inhibitors, and AI capabilities. There is also much research on organizational learning, project, and organizational success. With all that, one question seems to remain, what if an AI project isn’t going well and an organization is facing adversity in its undertaking? With that question, this research steers in the direction of organizational resilience and, more precisely, adaptation, anticipation, and coping capabilities. The research focused on conceptualizing this research subject and the essential related variables to answer the main research question. A theoretical framework and a measurement scale were developed to hypothesize how adaptation, specific AI-anticipation and coping capabilities can help an organization face adversity during its AI projects. At the end of this research, the measurement tool is still unvalidated. But the implication of both the framework and measurement scale is that a new research field suddenly reveals itself, providing a better understanding of potential future research. Furthermore, it led to several suggestions and advice for organizations wanting to or deploying AI.