MELLAN MÄNNISKA OCH MASKIN. Yrkesverksammas upplevelser av generativ AI i kommunikativt arbete

Abstract

Generative artificial intelligence has quickly become part of everyday work in media and communication professions. Tools such as ChatGPT, Gemini, and Copilot are now used for idea generation, text drafting, research, and strategic support, tasks that have traditionally relied on human expertise and judgement. Unlike earlier digital tools, generative AI produces content that can appear confident and well-structured, even though it lacks understanding or responsibility. This creates new ethical challenges for professionals who remain accountable for quality, accuracy, and credibility. At the same time, organisational policies and formal guidelines often lag behind technological development, leaving individuals to handle ethical questions on their own. Against this background, this study explores how professionals within media and communication talk about their use of generative AI and how they experience its role in their daily work. Rather than examining AI use from a technical perspective, the focus is on practitioners own descriptions, reflections, and concerns. Special attention is given to how ethical boundaries are perceived and how questions of responsibility, transparency, and professional integrity are handled when AI becomes part of creative and strategic work processes. The study addresses two research questions:

What ethical limitations and boundaries do professionals experience when using generative AI? How do they handle issues of responsibility, transparency, and professional integrity in relation to this use? The study is based on a qualitative research design using semi-structured interviews with eight professionals working in journalism, strategic communication, marketing, and public relations. All participants had experience using generative AI in their professional work, which was a deliberate choice to ensure informed and reflective accounts rather than speculative opinions. The interviews focused on how participants describe their AI use, how they reason about ethical concerns, and how they understand responsibility and transparency in AI supported work. The material was analysed using thematic analysis, allowing recurring patterns and shared perspectives to be identified across the interviews. The findings show that generative AI is widely integrated into everyday work practices, but that its use is rarely seen as straightforward or ethically neutral. Rather than relying on formal rules or clear organisational policies, participants describe how ethical boundaries are handled through personal judgement and situational decision-making. Responsibility is consistently understood as remaining with the human user. Even when AI plays a significant role in shaping ideas or content, participants emphasise that they are fully accountable for outcomes and consequences. AI is mainly described as a supportive tool, not as an independent decision-maker. The study also shows that transparency around AI use is not viewed as an absolute principle. Instead, decisions about disclosure are negotiated depending on context, audience expectations, and professional norms. Being transparent is often seen as important for maintaining trust, but participants also describe situations where AI use is treated as a routine tool and therefore not explicitly communicated. Overall, the study highlights that ethical governance of generative AI largely takes place in everyday practice rather than through formal regulation. Professional experience, judgement, and norms play a key role in managing responsibility, transparency, and integrity. By focusing on practitioners own accounts, the study challenges assumptions that professionals lack awareness of AI-related risks. Instead, many users actively reflect on ethical boundaries and deliberately position AI as support rather than a replacement for professional judgement. At the same time, this places increased responsibility on individuals, which may create new pressures in increasingly technology-driven work environments.