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Rysbekova, Gulzhan (2026) MIRTE: a psychological contract framework for AI transformation success. In: The 2026 Conference of the Department of Human Resource Management & Employment Relations: Shaping the Future of Work., 6 May, 2026, King's College London, London, UK.
Despite substantial organisational investment in artificial intelligence (AI), automation, and algorithmic management, recent industry evidence indicates that only around a quarter of organisations succeed in moving beyond proofs of concept to generate tangible value from AI at scale, with a majority of initiatives failing to progress or to deliver expected benefits (BCG, 2024). At the same time, these studies consistently show that people-related issues, such as organisational resistance and weak governance, account for most implementation difficulties, while technical limitations represent a much smaller share of reported obstacles (BCG, 2024; Vial, 2019; Kellogg et al.,2020). Together, these findings suggest that transformation difficulties stem predominantly from employee-side misalignment rather than from technological inadequacy.
Psychological contract (PC) research - employees' beliefs about reciprocal obligations (Rousseau, 1995) - provides a powerful lens for understanding employee reactions to organisational change. However, dominant PC models, primarily focused on transactional and relational dimensions, remain insufficient for diagnosing vulnerability in contemporary transformations, because they do not fully capture the complexity of modern work as experienced, perceived and evaluated by employees.
This paper introduces MIRTE (Meaning-making, Ideological, Relational, Transactional psychological contracts, and their Effects), a comprehensive, integrative framework designed to explain why AI-enabled transformations succeed or fail from an employee perspective. Positioned within the Future of Work literature, the paper addresses the need for a practical yet theoretically rigorous mutually exclusive and collectively exhaustive (MECE) model that enables organisations to assess and manage people-side alignment during AI-enabled and hybrid work transformations.
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