Special feature on 'The Future of Digital Employment Services' covers research on the Goyong24 platform and generative AI applications, including analysis of approximately 198.54 million logs, machine learning-based job recommendations and AI counseling support

The cover of the Korea Employment Information Service's quarterly journal "Employment Issues" [Korea Employment Information Service]
The cover of the Korea Employment Information Service's quarterly journal "Employment Issues" [Korea Employment Information Service]

The era of generative AI editing cover letters and analyzing individual skills and interests to recommend suitable careers is becoming a reality.

Amid a rapid shift toward AI and data-driven platforms in public employment services, the Korea Employment Information Service published the spring 2026 issue of its quarterly journal "Employment Issues" on Monday, themed "The Future of Digital Employment Services." The issue features research on digital innovation in employment services, centered on the Goyong24 employment platform, covering user experience improvement, data-based job recommendations, generative AI counseling support and data-driven performance management.

A lead study titled "Diagnosing Service Bottlenecks and Improving UX Through Goyong24 User Log Data Analysis" examined approximately 198.54 million access logs and 1.98 million session logs to empirically identify the friction points and drop-off factors users encounter on the platform. The research team proposed ways to improve the quality of public employment services based on user behavior data.

The study found that women accounted for 53.5 percent of Goyong24 users, outnumbering men at 46.5 percent, while users in their 50s made up the largest age group at 22.0 percent. Some 91.3 percent of all users were returning visitors, reflecting strong demand for recurring administrative tasks such as applying for and certifying unemployment benefits, filing parental leave requests and checking job listings.

Another notable study, "Machine Learning-Based Job Fit Assessment and Advancement of Employment Service Recommendations," used data from Korea's National Job Information System (KNOW) to analyze the required competencies, interests and values across 537 occupations and proposed a machine learning model for assessing job suitability. The research found that intrinsic factors such as work environment and personal interests may carry more weight in determining job fit than technical skills or knowledge.

Research on generative AI-assisted counseling found that career counselors showed strong demand for features including automated initial assessments, career roadmap design, core competency feedback and cover letter generation. The research team said generative AI has the potential to evolve beyond simple information retrieval into a collaborative tool that supports the day-to-day work of career counselors.

The issue also includes a study analyzing the labor market value of youth certifications. By linking employment data from young workers at South Korea's top 500 companies with national technical qualification records, the research confirmed significant differences in labor market outcomes across certifications. Technical qualifications showed relatively higher value in manufacturing, while service-related certifications also ranked highly in non-manufacturing sectors.

Additional research covered a decade of change at university job-plus centers and proposals for data-driven performance management reform, outlining a path forward for public employment services in the digital transformation era. The issue highlighted the need to build real-time performance management systems based on user journeys and establish data feedback loops.

Kim Young-ho, head of the AI Employment Service Strategy Division at the Korea Employment Information Service, said: "The spring issue of 'Employment Issues' presents research aimed at developing public employment services into a more precise and intelligent system grounded in data and AI." He added: "Going forward, public employment services will evolve within a structure where data, AI and user experience are organically integrated — more actively identifying and connecting career opportunities for each individual citizen."


fact0514@heraldcorp.com