Abstract
Purpose. Artificial intelligence (AI) is increasingly explored in organizational settings before formal adoption through discussions, vendor demonstrations, evaluation activities, limited use, and strategic planning. In organizations with substantial governance and compliance requirements, concerns about security, privacy, ethics, policy, and resources may constrain AI use and extend the introduction phase. Information technology (IT) professionals play a central role during this period as they evaluate tools, advise leadership, and anticipate infrastructure, governance, and support needs. However, the literature reviewed provided limited direct insight into how IT professionals experience AI before formal organizational adoption. The purpose of this qualitative phenomenological study was to explore IT professionals’ lived experiences of AI introduction within their organizations.Theoretical Framework. Guided by Technostress Theory and the Technology Acceptance Model, the study examined how organizational constraints, uncertainty, trust, and anticipated usability shaped early AI experiences. These frameworks supported examination of stress, role ambiguity, usefulness, usability, and sensemaking before AI becomes fully operational.
Methodology. Data were collected through semi-structured phenomenological interviews with six IT professionals who had exposure to organizational AI discussions, evaluations, planning activities, limited use, or exploratory engagement. These activities were treated as lived experience within the organizational context, including situations involving informal or indirect exposure to AI before formal organizational adoption. Interview data were analyzed phenomenologically to identify significant statements, meaning units, and themes reflecting shared participant experiences.
Findings and Conclusions. Findings indicated that participants experienced AI introduction as cautious, uneven, and interpretive. Six themes emerged from the analysis: AI was introduced through informal and decentralized processes; AI was used as a task-specific support tool in IT work; trust in AI was conditional on verification and transparency; organizational readiness lagged behind AI introduction; personal AI use often exceeded organizational use; and AI positioned IT professionals as evaluators and decision-makers. These findings suggest that early AI experiences were shaped by organizational communication, governance clarity, professional responsibility, and the need to verify AI outputs before workplace use.
Recommendations. Findings may inform organizational communication, training, governance, policy guidance, and support during early AI exploration.