Adopting GenAI applications in the workplace: managerial implications and insights from ICT professionals

Purpose This study explores how information and communication technology (ICT) professionals adopt and integrate generative artificial intelligence (GenAI) applications in organizational settings. It examines perceived benefits and challenges, the influence of social and organizational dynamics and the role of professional function in shaping adoption practices. Design/methodology/approach Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT), the study employs a qualitative–interpretive approach based on semi-structured interviews with 20 ICT professionals across diverse sectors. Inductive content analysis was used to identify thematic patterns and role-based distinction. Findings The results affirm UTAUT's core constructs: performance expectancy, effort expectancy, social influence and facilitating conditions, while introducing “local filters”: contextual mediators shaped by professional role, sectoral norms and organizational culture. These filters influence how GenAI is evaluated and adopted across occupational domains. While some organizations support strategic integration, others impose restrictions that lead to covert usage. The findings also highlight the dynamic nature of GenAI technologies and the need for flexible, role-sensitive integration strategies. Practical implications This study provides actionable insights for business and organizational leaders on integrating Generative AI (GenAI) technologies. It highlights the importance of fostering user acceptance, providing targeted training, and cultivating a supportive organizational culture. These findings help businesses and organizations navigate GenAI adoption effectively, ensuring both operational efficiency and employee alignment with technological advancements. Originality/value The study extends UTAUT by incorporating role-based differentiation and contextual sensitivity, offering a more nuanced understanding of GenAI adoption. Practically, it highlights the need for clear institutional policies, robust AI literacy programs, and differentiated deployment models tailored to professional roles. By foregrounding the interplay between technological capabilities, professional identity, and institutional readiness, the research contributes to the evolving discourse on AI integration in the workplace.