Preparing students for AI-integrated workplaces: a programme-level process framework for digital capability development and graduate career readiness

Introduction The integration of artificial intelligence (AI) into workplaces is changing the capabilities expected of graduates, while higher-education curricula often adapt more slowly to labour-market developments. This article addresses the need for a structured, accountable process through which academic programmes can respond to AI-integrated work. Methods The study uses a purposive conceptual synthesis of literature on digital capability, labour-market information, constructive alignment, human capital, stakeholder participation, socio-technical systems, and responsible AI governance. Kenya is used as an illustrative context rather than as a site of empirical validation. Results The synthesis produces a programme-level process framework comprising six stages: sensing, validation, diagnosis, redesign, implementation, and outcome review. These stages are supported by cross-cutting conditions involving data infrastructure, stakeholder participation, faculty capability, ethical governance, and academic authority. AI is positioned as a decision-support resource for interpreting labour-market signals and identifying potential competency gaps. However, stakeholder validation, academic prioritisation, formal authorisation, curriculum decisions, and outcome review remain subject to human and institutional accountability. Conclusion The framework integrates previously separate strands of research into an evidence-to-model process with explicit decision gates and traceability requirements. It offers propositions for empirical testing and provides a basis for programme-level curriculum review and renewal. The framework does not establish that AI-enabled curriculum processes improve graduate employability; such effects must be evaluated through programme-level pilots and longitudinal studies.