Redefining employee well-being and engagement in digitally enhanced, purpose-driven offices

The COVID-19 pandemic accelerated the adoption of hybrid work arrangements and the development of digitally enhanced, purpose-driven office environments. As organizations reconsider workplace strategies, these environments have emerged alongside, and in some cases replaced, more traditional office settings. Despite this transformation, comparatively little is known about how employees experience the psychosocial implications of these office environments for well-being, engagement, and work-related strain. This qualitative comparative case study examined employee experiences across six purposively selected organizations in the technology, finance, and professional-services sectors: three with digitally enhanced, purpose-driven office environments and three with traditional office environments. Data were collected between January and March 2025 through 36 semistructured individual interviews, five focus-group sessions involving 30 participants, and organizational document analysis. Thematic and cross-case analyses indicated that participants in digitally enhanced, purpose-driven offices commonly associated flexibility, spatial choice, connection, and purposeful office attendance with more supportive work experiences. However, they also described digital communication overload, hyperconnectivity, and concerns regarding equity and visibility in hybrid work. Participants in traditional offices more often emphasized rigidity, limited spatial variety, and fewer adaptive supports. Our findings highlight the dual psychosocial character of contemporary office environments and offer implications for organizational leaders, workplace designers, and policymakers seeking to integrate digital infrastructure, physical workspace, and people-management practices in ways that support employee well-being. Findings are based on self-reported qualitative accounts from a purposively selected sample of 54 unique participants and should be interpreted as contextually grounded rather than statistically generalizable.