Artificial Intelligence (AI) has a lasting transformational effect on industries worldwide. Former research has primarily focused on AI adoption as a business phenomenon without considering different industries. Those are characterized by unique attributes that may influence how modern technologies are implemented. In order to initiate non-generalized research in that field, industry-specific drivers and barriers to firm-level AI adoption in the financial services and the manufacturing industry are analyzed. Drawing on the Technology-Organization-Environment (TOE) framework, it was possible to paint a holistic picture of use cases and unique, but also general drivers and barriers of AI adoption for each industry. Ultimately, by bringing these two viewpoints together, a theory of hard (generalizable) and soft (industry-specific) AI adoption factors was developed. Therefore, the findings serve as a basis for further industry-specific research and provide business stakeholders and executives with a transparent handbook about industry insights and AI knowledge.


Paper Number 1008; Track AI; Complete Paper



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