Artificial intelligence for informal workplace learning: a problem-solving perspective - Rausch, Andreas (Frontiers in Organizational Psychology, 2025)
Rapid technological advances are constantly changing our workplaces and the organization of work. Formerly established workflows and role descriptions give way to short-term, skills-based project structures. The resulting skill shift heightens the importance of sustained informal workplace learning—ranging from unconscious, small-scale, everyday adaptation processes to intentional self-regulated learning activities. This concept paper explores informal workplace learning through the lens of problem solving, categorizing informal learning activities into reasoning, experimenting, researching, and observing, linked to personal, representative, social, and retrievable resources. It further examines how AI technologies can support these informal workplace learning activities. It is argued that AI's capacity for contextualized assistance within collaboration platforms, simulation environments and electronic performance support systems (EPSS) can support problem-solving and learning—if users maintain “process ownership” rather than delegating tasks entirely to AI. The concept of nudging (subtle prompts to foster reflection and learning) is proposed to ensure active engagement and prevent an “AI ghost-learner effect” (i.e., performing successfully through AI assistance without perceiving oneself as competent and as developing). Future research should focus on the empirical evaluation of these interventions and consider employees' utilization of AI to exploit the full potential for fostering informal workplace learning.