AI-Enabled Strategic Planning for Educational Institutions:

An Education Technology Readiness Framework for

Transformation

Aaras Y. Kraidi1,*

1 Department of Engineering, University of Technology and Applied Science, Shinas, Sultanate of Oman

Received: July 06, 2024 Revised: September 26, 2024 Accepted: November 11, 2024 ⋆ Corresponding author

ABSTRACT

Educational institutions are under growing pressure to integrate artificial intelligence (AI) and education technology

(EdTech) in ways that improve teaching, governance, and service delivery rather than merely expand digital

procurement. Strategic planning is therefore a core institutional capability: it aligns infrastructure, teacher readiness,

student access, digital learning resources, and governance routines into a coherent transformation agenda. This

study develops an AI-enabled strategic planning framework using the public 2023 World Bank EdTech Readiness

Index (ETRI) pilot evidence. The framework converts traffic-light dashboard indicators into pillar-level maturity

scores, strategic gaps, and a multi-criteria readiness benchmark. Empirical analysis of the Ho Chi Minh City and

Dominican Republic pilot dashboards shows that school management is the strongest readiness domain in both

settings, whereas connectivity and digital education resources remain more constrained. The paper contributes a

managerial decision model that translates readiness evidence into institutional priorities, implementation roadmaps,

and governance checkpoints. Unlike tool-centred studies, the analysis treats AI as a decision-support capability for

educational planning. The framework offers a transparent and reproducible approach for organising EdTech strategy

while keeping final decisions anchored in professional judgement and educational value.

Keywords: Artificial intelligence in education Education technology Strategic planning Institutional transformation

EdTech readiness Decision support TOPSIS

1. INTRODUCTION

The expansion of AI and digital learning tools has reshaped

the strategic agenda of educational institutions. The central

question is no longer whether schools and universities should

adopt technology, but how they should sequence capabilities,

govern risks, and connect digital initiatives to educational

value. Recent scholarship shows that AI in education

has moved well beyond intelligent tutoring and automated

assessment toward broader institutional concerns involving

governance, implementation, and leadership [1, 2, 3, 4]. In

this context, strategic planning becomes a practical governance

problem: leaders must decide which capabilities are

foundational, which are developmental, and which should be

postponed until institutional readiness improves.

This challenge is especially visible in systems attempting to

scale AI-supported teaching, analytics, and digital services

while still dealing with uneven connectivity, weak support

structures, and inconsistent access to digital resources. The

concern is not simply one of infrastructure. Decisions about

AI and EdTech also involve teacher capability, student participation,

implementation support, data use, and policy align-