ACIS 2024 Proceedings

Abstract

Research on the use of Artificial Intelligence (AI) for innovation has drawn attention from scholars in various disciplines. Our systematic review of 101 empirical studies drawn from information systems (IS) and other disciplines, however, reveals a narrow focus on the technology benefits offered by AI, with minimal focus being paid to the implications of AI constraints on innovation. Our review also indicates that the IS discipline has neglected this important area of research, given a limited number of studies published in mainstream journals. In response to these shortcomings, we offer a comprehensive framework of AI affordances and constraints for driving innovation, encouraging expanded research and practice on both sides of the framework. Overall, five key affordances and five key constraints are developed, with implications on important areas including drug development, creativity augmentation, and human-AI collaborations. Our review also contributes by highlighting future directions for advancing IS research in this domain.

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