Published in 2026, this study is particularly relevant amid the increasing adoption of AI for data processing, administrative support, public service enhancement, and decision-making assistance. For public sector organizations, AI readiness is not merely about providing technology systems and infrastructure. Employees' ability to use technology critically, securely, and responsibly is equally vital to digital government transformation.
AI Readiness Requires More Than Just Technology
Using AI in the public sector carries different considerations than in private business. Governments must address transparency, accountability, public data protection, privacy, security, algorithmic bias, and human oversight.
Consequently, government personnel need more than basic operational skills with AI tools. They must understand digital information, communicate and collaborate via technology, solve digital issues, safeguard data, and critically evaluate technology-generated outputs.
In his study, Herdian used the DigComp 2.2 framework to evaluate digital competence. The framework categorizes digital competence into five main areas:
Information and data literacy: The ability to search, evaluate, and manage digital content.
Communication and collaboration: The ability to interact and cooperate using digital tools.
Digital content creation: The ability to generate and edit digital materials.
Safety: Protecting devices, personal data, privacy, and digital well-being.
Problem-solving: Addressing technical challenges and adapting to new technologies.
Meanwhile, AI readiness in this research was assessed through three dimensions: AI knowledge and literacy, practical AI skills, and an orientation toward responsible AI usage.
Involving All 131 Civil Servants
The study applied a quantitative approach with a survey design. The target population comprised 131 civil servants at the West Java Regional Office of the Ministry of Law. Because the population was small and fully accessible, Herdian conducted a census method, including all 131 civil servants as respondents.
Data were gathered using a five-point Likert scale questionnaire (ranging from strongly disagree to strongly agree) and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4.1.
Demographic data showed that 68 respondents (52%) were female, while 63 (48%) were male. The largest age group fell between 41–50 years old, representing 54 respondents (41%).
Regarding education, the majority held a bachelor's degree (95 respondents or 73%). Position-wise, 93 respondents (71%) held functional roles.
Digital Competence Explains 70.8 Percent of AI Readiness
The empirical testing yielded robust findings. Digital competence was proven to have a positive and significant effect on AI readiness.
The path coefficient reached 0.841, with a t-statistic of 33.880 and a p-value < 0.001. Therefore, the hypothesis asserting that digital competence positively influences AI readiness was supported.
Additional statistical insights include:
$R^2 = 0.708$: Digital competence accounts for approximately 70.8 percent of the variance in AI readiness.
$f^2 = 2.423$: Indicates a large effect size.
$Q^2_{\text{predict}} = 0.704$: Demonstrates positive predictive relevance for the model.
Outer loading values across all dimensions of digital competence and AI readiness ranged from 0.807 to 0.897, confirming adequate representation of their respective constructs.
These metrics confirm that employees with stronger digital competence foundations display higher readiness for AI adoption.
However, Herdian noted a point of caution: an HTMT value of 0.956 suggests that digital competence and AI readiness share a very close empirical relationship. Thus, the strength of this linkage should be interpreted carefully and re-evaluated in future studies.
Digital Competence is a Foundation, Not a Substitute for AI Training
These findings do not imply that general digital skills alone make civil servants fully prepared for AI. Instead, digital competence serves as a foundational step for learning and adapting to AI systems.
Personnel accustomed to evaluating digital data, solving technical issues, securing information, and collaborating digitally bring relevant experience when interacting with complex technologies like AI.
In public administration, this foundation is vital because AI usage must be paired with professional judgment. Employees need to understand AI limitations, verify generated outputs, safeguard sensitive information, and preserve human decision-making authority.
Herdian's findings also suggest that AI training should not follow a one-size-fits-all model. Public organizations should provide foundational AI literacy to all staff, followed by specialized training tailored to roles requiring more intensive AI interaction.
Under this approach, capability development can begin with basic information literacy, problem-solving, security, and digital collaboration, before expanding into AI-specific knowledge, technical application, and ethical frameworks.
Implications for Government Digital Transformation
For public organizations, this research highlights that digital transformation extends beyond acquiring new technologies; investing in human capital is equally critical.
Capacity building for civil servants should emphasize analyzing digital content, solving technical problems, managing data security, working digitally, and adhering to AI ethics.
The study also provides a basis for developing more comprehensive AI readiness frameworks. Future research could explore additional factors such as dedicated AI training, organizational support, digital leadership, innovation culture, digital infrastructure, AI self-efficacy, and AI governance.
Ultimately, public sector AI readiness is best understood not only as an individual capability, but as the result of interactions among employee competence, organizational support, technology, and public governance structures.
Author Profile
Irvan Ramdhani Herdian is an academic and researcher from Widyatama University. His work focuses on the relationship between digital competence and AI readiness among public sector personnel. He is listed as the corresponding author of the study. Specific academic credentials and specialized fields were not listed in the publication metadata.
Research Source Details
Title: Digital Competence as a Predictor of AI Readiness in Public Sector Organizations: Evidence from Indonesian Civil Servants
Author: Irvan Ramdhani Herdian
Affiliation: Widyatama University
Year: 2026
Journal: International Journal of Management and Business Intelligence (IJMBI)
DOI: 10.59890/ijmbi.v4i4.38
E-ISSN: 3025-5589
Core Finding: The stronger a civil servant's digital competence, the higher their readiness to effectively and responsibly understand, utilize, and respond to artificial intelligence in government settings.
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