Leading higher education into the AI era: policy, governance and future workforce competencies in Türkiye
Berrin Yanιkkaya, Hatice Karaman, Ege Simge Demirel, Onur DemirPurpose
This paper evaluates how Türkiye's national and institutional higher education AI policies align with future workforce competencies identified in the World Economic Forum Future of Jobs Report (2025). It examines how leadership and governance discourses in these texts support, or limit, scalable AI literacy and ethical adoption in higher education.
Design/methodology/approach
A theory-driven document analysis was conducted on a corpus of national strategies, reports, sectoral policy papers, and twenty-four institutional higher education policy documents. The leadership analysis was extended to eight internationally issued reference documents (three European Union and five UNESCO) on AI and digital education for comparative purposes. Turkish texts were translated into English for natural language processing. Using spaCy, we conducted lexical analysis and constructed sentence-level co-occurrence networks, then mapped salient terms and patterns against WEF 2025 competency clusters. Leadership language was analysed using a predefined lexicon for transformative, strategic, and empowered leadership in higher education, and the corpus was further assessed against pedagogical leadership as the integrative grounding mechanism connecting policy-level dimensions to instructional practice.
Findings
The corpus strongly emphasises technical AI competencies (AI and big data) and ethics, while under-representing adaptive attitudes (e.g. resilience, curiosity), management and talent-management skills, foundational literacies, and civic or engagement competencies. Transformative leadership language (future, change, innovation, vision) dominates, whereas strategic and empowered leadership vocabularies, operational detail, and inclusive governance mechanisms are limited. Comparison with the eight EU and UNESCO reference documents shows that strategic vocabulary is more developed internationally, particularly in the EU AI Act, but that the empowered, distributed, and pedagogical-grounding registers are similarly thin across both Turkish and international corpora, indicating a shared international gap rather than a uniquely Turkish one. These imbalances suggest a risk of producing technically proficient but civically and managerially under-prepared graduates, and a policy landscape that lacks the operational conditions necessary for sustained, instructionally grounded AI integration.
Research limitations/implications
The analysis is restricted to published policy documents and does not capture informal practices or implementation outcomes.
Practical implications
Findings highlight the need for broader competency aims, explicit curriculum frameworks, and empowered leadership roles (e.g. AI Ethics Officers, Educational Data Scientists) to enable scalable, ethical AI integration in higher education.
Social implications
The findings carry direct social implications. By emphasising technical AI proficiency while under-representing civic, ethical, and adaptive competencies, current Turkish policies risk producing graduates equipped to operate AI systems but ill-prepared to navigate the social, ethical, and democratic challenges these systems generate. This imbalance threatens equitable workforce readiness, public trust in AI deployment, and the capacity of higher education to cultivate engaged citizens. Without explicit attention to inclusive governance, pedagogical grounding, and competencies such as resilience, curiosity, and civic engagement, AI integration risks widening rather than narrowing existing social inequalities and weakening the public-good function of higher education.
Originality/value
The study integrates computational text analysis with leadership theory to assess AI policy readiness in higher education. It applies a triadic leadership framework comprising transformative, strategic, and empowered leadership, complemented by pedagogical leadership as an integrative grounding mechanism and by distributed leadership as the cross-level enabling architecture, to evaluate whether policy texts encode the conditions for translating leadership vision into instructional practice. It provides an empirically grounded map of misalignments between policy discourse, future-skills frameworks, and leadership approaches, situates the Turkish profile against an international reference corpus, and offers system-level recommendations for AI governance and competency development in Turkish higher education.