AI as a Tool for Improving Work Efficiency and Well-Being

Ernest Górka, Michał Ćwiąkała, Gabriela Wojak, Dariusz Baran, Janusz Soboń, Adam Muszyński, Kamil Saługa, Daniel Zawadzki, Marcin Agaciński, Monika Wyrzykowska-Antkiewicz and Jan Magda

EconStor Open Access Articles and Book Chapters, 2026, vol. 29, issue 1, 607-618

Abstract: Purpose: This paper examines how artificial intelligence (AI) tools influence employees' work-life balance (WLB) in contemporary organizations. It analyzes both the opportunities and the risks associated with the implementation of AI in work design, communication, learning, and performance management. The study also explores how AI-supported practices may affect employee motivation, well-being, and organizational effectiveness. Design/methodology/approach: The article adopts a conceptual research approach based on a critical review of literature on work-life balance, digital work, artificial intelligence, and human resource management. The analysis integrates perspectives from organizational behavior, management studies, and selected business practice examples. Particular attention is given to AI-enabled flexibility, task automation, and the ethical implications of digitally mediated work systems. Findings: The analysis suggests that AI may positively support work-life balance by automating routine tasks, enabling more flexible work arrangements, and personalizing learning and work processes. At the same time, AI may also intensify boundary erosion, permanent connectivity, and performance pressure if implemented without appropriate safeguards. The findings indicate that the impact of AI on WLB is not inherently positive or negative, but depends on organizational design, managerial practice, and the human-centeredness of implementation. Research limitations/implications: The paper is conceptual and based on secondary sources rather than original empirical data. Future research should examine how specific AI tools influence work-life balance across occupations, sectors, and demographic groups. Additional empirical studies could also assess the long-term effects of AI-supported flexibility on motivation, burnout, and employee retention. Practical recommendations: Organizations should adopt a human-centered approach to AI implementation and ensure that digital tools support rather than undermine employee well-being. HR departments should combine AI deployment with transparent governance, flexible work policies, digital boundary protection, and ethical data practices. AI should be used to reduce unnecessary workload, increase autonomy, and strengthen employee support systems.

Keywords: Artificial Intelligence; work-life balance; digital work; human resource; management; employee well-being; flexible work. (search for similar items in EconPapers)
JEL-codes: J24 M12 M54 O33 (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:espost:339721

DOI: 10.35808/ersj/4334

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