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A DIGITAL LEARNING ECOSYSTEM MODEL FOR ENHANCING ARTIFICIAL
INTELLIGENCE LITERACY: SYNTHESIS AND POLICY IMPLICATIONS

Patthanan Bootchuy*¹, Wachira Brahmawong², Thanat Samanakupt³

Sukhothai Thammathirat Open University, Thailand.
1, 2
King Mongkut's Institute of Technology Ladkrabang, Thailand.
3
(*E-mail: Patthanan.boo@stou.ac.th)

ABSTRACT

The emergence of Generative AI has led to significant structural shifts in the global
labor market and the competencies required in the digital economy. The research aim of
this study is to synthesize key perspectives to propose a Digital Learning Ecosystem Model
for Enhancing Artificial Intelligence Literacy (AI Literacy). Methodologically, this
conceptual study employs a qualitative thematic synthesis and conceptual integration of
recent literature, secondary data sources, and international policy reports. The main
findings present AI Literacy as a multidimensional construct conceptualized across four
dimensions: Cognitive/Epistemic, Applied/Technical, Ethical/Critical, and Socio-emotional.
Furthermore, the findings establish a model that positions AI Literacy at its core, which is
supported by a Distance Digital Learning Ecosystem that integrates technology, pedagogy,
and learner support to foster continuous learning and workforce resilience. The
contribution and significance of this study lie in offering a systemic approach that aligns
with the Sustainable Development Goals (SDGs) by promoting inclusive and lifelong
learning. Additionally, the paper outlines actionable policy implications at the micro,
meso, and macro levels. These recommendations serve as a significant guide for
universities as they evolve into key infrastructures for lifelong learning in the digital era.
Keywords: AI literacy; digital learning ecosystem; policy recommendations.

1. Introduction
The global digital economy is highly volatile. Post-pandemic economic shifts and
technological disruptions have worsened this instability (Brynjolfsson et al., 2020).
Massive tech layoffs between 2020 and 2025 show that specialized technological
knowledge alone no longer ensures career security. As AI becomes ubiquitous, AI literacy
is now essential across the workforce (Liu et al., 2025). This change is fueled by “creative
destruction” (Schumpeter, 1942), which the rise of Generative AI has accelerated.
Generative AI can replace human labor in both routine manual tasks and, increasingly,
non-routine cognitive work (Autor et al., 2024; Acemoglu & Restrepo, 2019).
Amid this crisis, the only viable path for the economy and the workforce is to
transition from resisting technology to coexisting with and leveraging it to create new
sources of productivity (Acemoglu & Restrepo, 2019). However, the traditional formal
education system often suffers from slow curriculum development cycles that fail to keep
pace with the rapid pace of innovation. Despite the recognized urgency of this issue, a
significant research gap remains. Current literature predominantly addresses AI
competencies as isolated technical skills, revealing a profound lack of integrated AI
literacy models situated within broader digital learning ecosystems. Furthermore, there is
a notable scarcity of research explicitly linking the development of AI literacy to long-term
workforce resilience. Therefore, this article aims to synthesize a conceptual framework

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