From policy to practice: AI demands institutional shift in higher education

A new policy-oriented study underscores the pressing need for higher education institutions (HEIs) to treat AI not merely as a support tool, but as a strategic imperative. The paper, titled “Artificial Intelligence: Objective or Tool in the 21st-Century Higher Education Strategy and Leadership?”, published in Education Sciences, warns that institutions that fail to develop responsible, transparent, and forward-looking AI strategies risk falling behind in a digital transformation that is fundamentally reshaping research, teaching, and academic culture.

Against the backdrop of disruptive global trends, from digital acceleration and climate change to political instability and ethical dilemmas, the study argues that higher education must confront the question of AI integration not as an optional innovation, but as a central governance challenge. It draws on global surveys, two institutional case studies, and a meta-analysis of current practices to evaluate how AI is being implemented across universities and how leadership can steer this transition effectively and ethically.

How is AI transforming higher education institutions?

The study finds that AI is reshaping higher education across all three core missions of teaching, research, and societal service. However, rather than displacing the humanistic mission of academia, AI is described as an amplifier of distinctly human capabilities. Critical thinking, creativity, and empathy are presented as even more vital in the era of generative tools like ChatGPT and autonomous academic agents. Despite this, most institutional mission statements still fail to formally acknowledge AI, suggesting a lag between technological reality and strategic documentation.

Universities now face mounting pressure to reinterpret their roles in a rapidly changing world defined by the Fourth Industrial Revolution. AI is positioned not only as a means to improve operational efficiency but also as a driver of profound pedagogical shifts. While globalized access to AI promises improvements in personalization, assessment, and research productivity, it also introduces challenges in privacy, academic integrity, authorship, and information reliability.

One notable finding of the study is that AI should be understood both as a catalyst for achieving current strategic objectives and as a standalone strategic goal requiring long-term institutional vision. The dual role of AI demands that HEIs reconfigure organizational structures, allocate resources to digital literacy, and articulate values-based principles of implementation. This strategic repositioning, the study suggests, should be driven by inclusive stakeholder engagement and iterative evaluation, not short-term compliance or tech opportunism.

What makes AI a strategic objective and not just a tool?

The central argument advanced in the research is that while AI is often approached as a tool to enhance learning, its disruptive nature mandates that it also be treated as a long-term strategic objective. In this dual framing, AI becomes both a means and an end: a mechanism to achieve quality outcomes and a phenomenon requiring its own management framework.

The study contends that HEIs must move beyond fragmented or faculty-specific AI policies and develop institution-wide strategies with clearly defined goals, responsibilities, and evaluation mechanisms. Successful implementation is described as dependent on proactive governance, integrated planning, and alignment with the institution’s overarching mission. Moreover, the formulation of an AI strategy must be iterative, frequently reviewed and updated in response to rapid technological evolution.

Through in-depth case studies of Ghent University and HOWEST, the paper demonstrates how tailored AI governance models can differ depending on institutional philosophy and academic orientation. Ghent University, for instance, permits and even encourages responsible AI use in student writing and thesis preparation, embedding AI literacy within existing program outcomes. Conversely, HOWEST, a university of applied sciences with strength in gaming and cybersecurity, adopts a detailed and structured framework that aligns AI strategy with innovation and labor market relevance.

These examples illustrate the diversity of approaches but reinforce the study’s central recommendation: regardless of structure or size, all HEIs must articulate coherent AI policies that reflect ethical concerns, technological potential, and institutional values.

What kind of leadership and culture is needed to guide AI integration?

According to the study, managing AI integration effectively requires a radical rethinking of academic leadership and organizational culture. AI, the author argues, accelerates existing demands for visionary, ethical, and inclusive leadership rather than replacing traditional models altogether. Institutional leaders are urged to shift from a logic of control and hierarchy to one of empowerment, co-creation, and trust.

The study emphasizes that institutional culture, defined by values, beliefs, and shared purpose, is just as crucial as technology in navigating the AI transition. Leaders must not only develop policies but also embody the principles of transparency, accountability, and critical reflection. Without a strong cultural foundation, even the most technically sound AI strategies are unlikely to take root.

The research further calls for dissolving outdated disciplinary silos in favor of collaborative, project-based models that reflect the interdisciplinary nature of AI. This shift, it argues, will be essential to cultivate adaptive learning ecosystems where both staff and students develop AI-related competencies alongside broader civic and ethical awareness.

Institution-wide training, workshops, help desks, and open forums are also recommended to facilitate knowledge transfer and ensure broad participation in the AI governance process. The author warns that failure to establish such mechanisms risks deepening digital divides and undermining institutional legitimacy.