The adoption of Artificial Intelligence (AI) has become increasingly prevalent in the Fourth Industrial Revolution, particularly among Electrical and Electronics (E&E) Small and Medium-sized Enterprises (SMEs) in Malaysia. AI has the potential to enhance operational performance of E&E SMEs. Despite the growing potential of AI, the adoption rate in Malaysian SMEs is slow. This is largely due to a lack of readiness and awareness regarding the key factors that influence AI adoption and its impact on operational performance. Previous studies examined various factors to study the AI adoption and there tends to be an empirical gap where none of the study covers all five important factors in a single study. To fill in the empirical gap, this conceptual paper proposes a framework that integrates five important key factors influencing AI adoption in organizations such as human, technological, organizational, environmental, and data management factors within a single study in alignment with the TOE Framework. In addition, in align with dynamic capability theory, this framework also introduces process innovation as a mediating variable to better explain the relationship between AI adoption and operational performance. The proposed conceptual framework aims to provide valuable insights for researchers and practitioners seeking to enhance operational performance through AI adoption in Malaysian E&E SMEs with support of process innovation.
Pavithran et al. (Wed,) studied this question.