As generative artificial intelligence becomes increasingly embedded in everyday work practices, organizations face the challenge of understanding not only whether employees adopt AI tools, but how AI use translates into meaningful value in practice. This study examines workplace AI use at Nedap through a mixed-method design that moves beyond adoption metrics to explain why employees choose to use AI, how they integrate it into daily work, and how AI-related value can be better supported through interaction design. Drawing on the Unified Theory of Acceptance and Use of Technology and its extensions, a quantitative survey (N = 97) examined determinants of employees’ intention to use AI tools. Principal component analysis revealed that the resulting factor structure aligned more closely with the Theory of Planned Behavior, with Trust emerging as a critical AI-specific extension, than the original proposed model. Partial least squares structural equation modeling revealed that intention to use AI is primarily driven by attitude toward AI and trust (in both AI systems and organizational governance), while subjective norms and perceived behavioral control played no significant role. Complementing these findings, qualitative interviews (N = 7) explored how employees enact AI use in everyday work. The interviews show that AI is predominantly used as an assistive and augmentative tool to reduce friction, support learning, and provide starting points in situations of uncertainty, while human judgment and responsibility remain central. These insights help explain the significance of attitude and trust in the survey results: employees value AI not because it is easy to use or socially expected, but because it can support autonomy and sense-making when its limitations are actively managed. Building on the combined findings, a design-based intervention, the Prompt Coach, was developed to address recurring interaction challenges related to unclear prompting and unreliable outputs. Together, the study demonstrates that effective workplace AI use depends less on enforcing adoption and more on fostering positive attitudes, calibrated trust, and supportive interaction design that enables employees to translate AI use into sustained organizational and individual value.