The Role of Boundary Spanners in Organizational Adoption of Artificial Intelligence

The integration of AI solutions within companies holds significant transformative potential, particularly within sectors such as manufacturing. However, successful AI implementation requires adept orchestration of resources, with boundary spanners playing a pivotal role in bridging boundaries between different groups in organizations. Despite their importance, the role of boundary spanners in facilitating AI adoption remains underexplored. This paper aims to address this gap by empirically examining key boundary-spanning activities, assessing the relevance of various boundary-spanning roles, and analyzing the interplay between different levels of AI capabilities and boundary-spanning skills in organizations. Drawing upon empirical data obtained from 215 representatives of German companies, our study underscores the criticality of all relevant boundary-spanning activities in the context of AI implementation. Furthermore, certain roles, notably project managers, emerge as widely endorsed and suitable boundary spanners, while others such as employee representatives and HR personnel exhibit comparatively less relevance. Our findings indicate that companies with higher AI capabilities exhibit markedly superior levels of boundary-spanning skills compared to their counterparts. Similarly, our regression analysis demonstrates that the extent of current AI utilization significantly influences the availability of boundary-spanning skills in organizations. Interestingly, companies operating within the manufacturing industry display notably lower levels of boundary-spanning skills when juxtaposed against those from other sectors. In sum, our study empirically underscores the significant role and thus the imperative of investing in boundary spanning to augment AI adoption processes, particularly within manufacturing companies.