Human-Al Adoption Futures: A Foresight-Informed Reskilling Framework for Non-Technical Workforces in Emerging Economies

Debates on organizational artificial-intelligence adoption still center on technological readiness, treating the workforce as a downstream training problem. This paper argues that technical AI exposure does not become successful adoption automatically: in non-technical roles - administration and support, finance, education, health services, and management or human resources—whether exposure becomes productive augmentation and job resilience, or instead displacement and degraded job quality, is mediated by workforce readiness. The paper synthesizes recent foresight intelligence and labour-market evidence from the World Economic Forum, OECD, the International Labour Organization, and the IMF, together with peer-reviewed findings on reskilling effectiveness, to develop a conceptual, foresight-informed framework. Using a STEEP-structured signal scan and two critical uncertainties-the pace and depth of AI deployment, and the speed and quality of reskilling and role redesign-it derives four plausible ۲۰۳۰ adoption futures and shows that workforce reskilling readiness is the human-capability layer that most consistently separates a desirable future from a damaging one across them, alongside conditioning factors such as governance, trust, and infrastructure. The framework links five elements automation-exposure mapping, human-AI role redesign, future-skill development, adaptive organizational learning, and early-warning signal monitoring - into a single adoption-readiness pathway, accompanied by an illustrative ۲۰۲۵-۲۰۲۷ capability-building roadmap. It is presented as a conceptual artifact rather than an empirical study, and is especially relevant to emerging and resource-constrained economies, where automation pressure interacts with uneven digital infrastructure and fragmented training systems. The central claim is that reskilling readiness should be modelled as a mediating adoption capability, not a post-adoption labour-market response.

کلیدواژه ها:

human-AI adoption ، technology foresight ، reskilling and upskilling ، future of work ، job resilience ، emerging economies