Making AI Work at Work: How Employee-Centered Implementation Practices Foster Meaningful Work and Performance

Abstract: Artificial intelligence is fundamentally reshaping how work is performed and experienced, raising urgent questions about implementation strategies that support both organizational effectiveness and employee wellbeing. This study examines employee-centered AI implementation (ECAII) practices—characterized by transparent communication, meaningful consultation, and targeted training—as strategic mechanisms for fostering positive outcomes during AI-driven organizational transformation. Drawing on survey data from 168 Italian knowledge workers actively using AI technologies, structural equation modeling analyses revealed that ECAII practices directly enhanced job satisfaction and performance while also operating indirectly through work meaningfulness. Moderated mediation analyses further demonstrated that these beneficial effects were significantly stronger among employees with more favorable attitudes toward AI. These findings extend high-involvement management and meaningful work frameworks to AI contexts, highlighting that successful AI adoption depends not merely on technical implementation but on participatory strategies that help employees reconstruct purpose and value in their evolving roles. From a practical standpoint, the research underscores the organizational imperative to treat AI implementation as a human-centered change process rather than a purely technological transition, with clear implications for HR strategy, leadership practices, and workforce development.

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