ENHANCING ARTIFICIAL INTELLIGENCE (AI) LITERACY FOR ECONOMIC GROWTH AND DIGITAL TRANSFORMATION: THE ROLE OF HIGHER EDUCATION IN KAZAKHSTAN

National governments increasingly treat artificial intelligence (AI) skills as both an education reform priority and an innovation-policy instrument. The purpose of the article is to analyse and evaluate the AI Sana program as a comprehensive policy mix in the field of AI skills development in the higher education system of Kazakhstan. This paper develops a document-based case study of Kazakhstan’s AI‑Sana program, launched in late 2024 as a staged pipeline intended to move learners from foundational AI literacy to mentored projects and, for a smaller subset, startup acceleration. Using program reference materials provided by the authors and triangulating them with open-access government communications, reputable reporting, and official descriptions of comparable international initiatives, we reconstruct AI‑Sana’s policy architecture and argue that it should be analysed as a policy mix rather than a single training intervention. The mix bundles (i) mandate-backed curricular mainstreaming, (ii) platform partnerships and localised micro‑credentials, (iii) implementation capacity via regional “anchor” universities, (iv) innovation-funnel instruments linking projects to commercialisation, and (v) enabling infrastructure through national compute investments. The analysis also highlights measurement challenges typical of fast-scaling initiatives, especially the conflation of certificates, unique learners, and competency gains and treats reporting variance as an analytic finding. Building on micro‑credential governance scholarship, digital education governance research, and responsible generative AI guidance, we propose an evaluation blueprint with a minimum reporting standard and stage-aligned indicators that can support international comparability. Kazakhstan is globally informative because it combines system-wide higher-education delivery with explicit innovation translation and compute infrastructure, illuminating how national AI strategies can be operationalised through universities while raising acute questions about quality assurance, integrity, and platform dependence.

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