Adapting to AI-mediated workplaces: how STEM trainees navigate new challenges and opportunities

Abstract

Purpose The integration of artificial intelligence in workplaces is rapidly transforming employment structures, skill requirements, and decision-making processes. This study examines how AI-mediated workplaces (AI-MWP) impact STEM trainees entering the workforce. Specifically, it explores their preparedness, the challenges and opportunities presented by AI-MWP, and the role of socio-digital skills in shaping their career trajectories. Design/methodology/approach This study employs a socio-technical systems (STS) approach to analyze the experiences of science, technology, engineering and mathematics (STEM) interns. Using qualitative research methods, including interviews and case studies, we investigate how AI-MWP influence information sharing, task allocation, workplace interactions and the professional development of recent graduates. Findings The findings highlight that AI-MWP introduce new challenges for STEM trainees, particularly in navigating socio-digital skills, workplace autonomy and task ownership. AI-mediated communication reduces informal learning opportunities, impacting trainees' ability to develop professional networks and contextual understanding. Revealing a growing gap in employability frameworks that fail to address the evolving socio-technical demands of modern work, the study also underscores the necessity of digital fluency, adaptability and interdisciplinary collaboration as essential competencies for thriving in AI-MWP. Originality/value This study extends STS thinking into the AI-mediated work domain, offering new insights into how digital transformation reshapes employment dynamics. By identifying socio-digital skills as a critical yet overlooked component, we provide actionable recommendations for STEM educators and employers to improve training strategies and bridge the gap between academic preparation and AI-MWP.

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