Developing capabilities: Lifelong learning in the age of AI

Abstract Due to the ongoing digitalisation of workplaces and educational settings, human activity underpinning learning and work is increasingly mediated by technology. The advancement of artificial intelligence (AI) and its integration into everyday technologies influences how people are exposed to information, interact, learn and make decisions. We argue that technology, data and evolving AI applications affect how humans enact and experience life and work, changing the context for learning. Hence, as this paper argues, the current notion of lifelong learning needs a revisit to embrace technology at its foundation. To bring freely chosen goals and ownership in one's learning to the fore, in the context of the coming AI age, we argue for the telos of learning to shift from human capital to human development, with the spotlight on capabilities. The paper draws on the capability approach to inform individuals and organisations of how they can support human development throughout lifelong learning. We then move to provide examples of how technologies underpinning workplace practices can be seen with the focus on capabilities as individuals learn to create value. Practitioner notes What is known about the topic? The primary notion of lifelong learning refers to adult learning processes. The policy perspective that dominates organisation of lifelong learning opportunities focuses on human capital development. Technologies mediate learning and work. What this paper adds Technology is not explicitly addressed in meanings associated with lifelong learning. AI‐based technologies dynamically interact with human cognitive and social practices. The paper argues for a stronger focus on human development instead of human capital in the telos of lifelong learning opportunities. Capability approach is a viable alternative to human capital perspective on LLL. Data used to support learning can focus on learner agency and systemic factors that enable and constrain lifelong learning. Implications for practice and/or policy LLL interventions should promote systemic support for learner agency and ownership. LLL interventions should focus on negotiated value creation. Workplaces should embrace human‐machine integration but in ways that support capability and human development, not human capital.