From Code to Culture : Exploring internal Communication and Trust in Stockholm’s Tech Sector

Sammanfattning

As artificial intelligence (AI) becomes more integrated into business operations, internal communication on AI risks is critical for building trust and ensuring responsible implementation. This study investigates how Stockholm-based IT organizations anticipate, debate, and coordinate internal responses to AI threats, focusing on trust, transparency, and organizational readiness. While earlier research has focused on external-facing AI ethics and governance, few studies have examined the internal dynamics that influence how employees interact with and respond to AI tools. This study addresses that gap by looking into how IT organizations in Stockholm communicate and collaborate internally in response to AI-related concerns. This study, which is based on risk communication and organizational trust theories, takes a qualitative, interpretive approach using semi-structured interviews with professionals from various Stockholm-based IT organizations. The findings demonstrate that, despite investing in advanced technical detection systems, firms usually lack coordinated communication channels and escalation processes that involve individuals other than core AI teams. As a result, AI risk management is typically separated, resulting in ambiguity about responsibilities, inconsistent risk reporting, and low trust in AI outputs among non-technical staff. The research underlines the importance of organizations shifting away from executive-led AI strategies in favor of more inclusive, transparent, and participatory approaches. Cross-departmental collaboration, increased role communication, and acceptance of employee concerns are all required for effective internal AI governance. While skepticism regarding AI is not inherently negative, unanswered worries could hinder implementation and long-term advancement. This study contributes to the growing literature on responsible AI deployment by shedding light on how organizational structures influence trust in AI, as well as offering practical suggestions for organizations looking to balance technological advancement with ethical and communicative readiness.