In recent years, Artificial Intelligence (AI) has become one of the most discussed topics in research on public governance and national development. However, most existing works tend to approach AI from the perspective of technology, digital transformation, or administrative reform. The book "Applying Artificial Intelligence to Build Vietnam's Public Service in the New Era," edited by Prof. Vu Minh Khuong, takes a different path: placing AI in relation to state capacity, the quality of the public service, and Vietnam's national development prospects in the 21st century.
Notably, the book does not treat AI as its central subject. Instead, AI serves as a "lens" through which to re-examine the core issues of development governance: Why do some countries achieve breakthrough success while others fall into the middle-income trap? What determines the state’s development-enabling capacity? And as AI reshapes the way society is organized, how should the public service be redesigned to continue driving development? It is this framing that gives the work its academic value and timely relevance.
The book’s first major argument is the need to shift the approach to public service research from the narrow scope of administrative reform to the broader domain of national development capacity. This is not merely a technical adjustment but a profound shift in mindset.
In many studies on the Vietnamese public service, focus is typically placed on structural organization, job positioning, public HR management, administrative procedure reform, or civil service ethics. While these issues remain essential, they mostly answer the question of how to make the state apparatus run more efficiently. Prof. Vu Minh Khuong’s book asks a larger question: What role does the public service play in building national development capacity?
To answer this, the author dedicates significant coverage to analyzing the experiences of Japan, South Korea, Singapore, and China. The common thread drawn is not a specific institutional model or policy, but the presence of a public administration apparatus possessed of superior learning capabilities, strategic capacity, and executive execution. From this, the author puts forward a notable observation: the public service is not merely a policy-executing mechanism, but a "locomotive for national development."
This is arguably the book’s most important theoretical contribution, expanding public service research from public administration into the realm of development governance.
The work's second contribution lies in its effort to update the theory of the Developmental State within the context of digital technology and AI.
Inheriting classic studies on the developmental state, the book reaffirms the central role of state capacity in developmental success. However, rather than stopping at traditional factors such as coordination or strategic planning capacities, the author adds a new dimension: the capacity to harness data, knowledge, and technology.
Under this approach, AI is not merely a tool to automate administrative workflows; it becomes a resource that enhances the state's cognitive capacity. The ability to access global knowledge, analyze big data, forecast trends, and evaluate policy scenarios is viewed as an increasingly critical component of national governance.
This is a highly stimulating argument as it expands the understanding of state capacity in the 21st century. However, to a certain extent, the book still dedicates more space to the potential of AI than to the institutional conditions required to realize that potential. For instance, issues regarding public data quality, cross-sector data sharing, and the digital literacy of civil servants are mentioned only as supporting conditions rather than analyzed as structural bottlenecks. This remains an avenue of research that warrants further clarification in the future.
If one were to choose the most innovative contribution of the work, it would likely be its approach to policy learning in the AI era.
Contrary to the popular belief that AI primarily supports administrative processing or public service delivery, the book views AI as a tool to enhance the state's learning capacity. According to the author, the main challenge in today's world is no longer a shortage of information, but a lack of capacity to filter, synthesize, and transform knowledge into actions tailored to the national context. AI is proposed as a vehicle that allows the state apparatus to access international experience faster, identify lessons of success and failure, and support data-driven policy scenario modeling.
This argument shifts the focus from "using AI to work faster" to "using AI to learn better." In many respects, this is the very distinction between an administrative digitization mindset and a national development capacity-building mindset.
Nevertheless, the question remains whether technology alone is enough to generate learning capacity. The developmental history of East Asian nations shows that learning capacity is not just a technological matter, but also a function of organizational culture, institutions, and human resource quality. Therefore, AI may be a necessary condition, but it is not yet a sufficient one to form an effective learning state.
The overarching message throughout the book is that in the AI era, competition between nations is, first and foremost, a competition over institutional quality and the quality of the public service.
This argument carries great weight as Vietnam enters a new phase of development. Rather than viewing AI as a mere technological fix, the author emphasizes that its true value can only be unlocked when combined with a public service equipped with learning capabilities, strategic thinking, and an innovative spirit.
However, the book also leaves behind several questions for future research. For example: What constitutes an "elite public service" under Vietnamese conditions? What criteria can be used to measure and evaluate public service capacity in the AI age? And what is a feasible roadmap to transition from the current public service model to a data- and knowledge-driven one?
Falling short of fully answering these questions does not diminish the work's value. On the contrary, it may be one of the book’s major contributions: opening up new research directions for administrative science and public policy in Vietnam.
The outstanding value of Applying Artificial Intelligence to Build the Vietnamese Public Service in the New Era lies not in providing a flawless, finished model of public service in the AI age, but in its ability to connect issues that are often studied in isolation: national development, the developmental state, civil service reform, policy learning, and artificial intelligence.
From an academic standpoint, this is a highly stimulating work that expands the research landscape for public governance and development administration amidst digital transformation. From a practical standpoint, its arguments offer valuable reference material for cadre and civil servant training, as well as for institutional refinement and national governance capacity building.
More importantly, the book raises an issue of strategic significance for Vietnam's future: in the AI era, a nation's competitive advantage lies not just in technology, but primarily in the state’s capacity to learn, adapt, and enable development. That is the central thesis underpinning the academic and practical value of this work.