This paper presents a conceptual analysis of the evolving relationship between corporations, artificial intelligence, and the future workforce. As AI systems become increasingly embedded within organisational structures, their impact extends beyond efficiency and productivity into the deeper dimensions of human identity, agency, and purpose. Drawing on sociological and philosophical frameworks, the study examines how work functions as a central component of identity formation and meaning-making. It explores how the automation and augmentation of roles through artificial intelligence are reshaping traditional understandings of labour, shifting human contribution from direct task execution towards oversight, interpretation, and coordination. A key contribution of this paper is the introduction of the concept of identity displacement, defined as the disruption of an individual’s sense of self and purpose resulting from the transformation or reduction of their role within AI-integrated systems. This concept highlights that the implications of artificial intelligence are not limited to economic outcomes, but extend to the psychological and existential dimensions of work. The analysis further argues that corporations, as efficiency-driven systems, are structurally aligned with artificial intelligence, reinforcing patterns of optimisation that may overlook human-centred considerations. However, the future of work need not be defined by displacement alone. By reframing human roles around creativity, ethical judgement, and relational intelligence, artificial intelligence can function as an augmentative tool that enhances, rather than replaces, human capability. Ultimately, this paper calls for a more holistic and human-centred approach to the integration of artificial intelligence within corporate systems, emphasising the importance of preserving meaning, agency, and identity in an increasingly automated world.
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Joanna Lloyd
Netherlands Institute for Radio Astronomy
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Joanna Lloyd (Wed,) studied this question.
www.synapsesocial.com/papers/69d896676c1944d70ce07c8d — DOI: https://doi.org/10.5281/zenodo.19470062
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