[Edaily Reporter Shin Yeong-bin ] A competency assessment of female scientists and engineers in the STEM field regarding the AI Transformation (AX) revealed that while their understanding of artificial intelligence (AI) and verification capabilities are high, their practical application skills—such as task automation—are relatively low.

Multicampus Corporation(067280), a corporate training specialist, announced the results of the “AX Competency Assessment” on the 31st, which was conducted among 201 female members in science and engineering from the Korea Women in Science, Engineering and Technology (WISET).

Since 2019, Multicampus Corporation has partnered with WISET to provide free e-learning job training aimed at helping women who have taken career breaks re-enter the workforce and advance their careers. This AX competency assessment was also conducted free of charge as an extension of these corporate social responsibility efforts.

The AX Competency Level Assessment is an assessment service developed by Multicampus Corporation in collaboration with Professor Kim Ju-ho of KAIST. It categorizes the AX competencies required by organizations into eight major competencies and 40 sub-competencies to analyze the level of AI utilization and competency gaps at the individual, organizational, and departmental levels.

The assessment was conducted from the 15th to the 22nd. Participants included 78 unemployed individuals, 74 employees at private companies, and 49 employees at public institutions.

The average AX competency score for the 201 women in science and technology who participated in the assessment was 57.8 out of 100. Multicampus Corporation classified this as Level 3, indicating a practical level where AI is partially applied or utilized in work.

Looking at specific competencies, there was a significant gap between the ability to understand and evaluate AI and the ability to apply it to actual work. Verifying AI outputs and understanding the characteristics and limitations of generative AI scored 71.2 points each. Data-driven decision-making also scored in the 70s, at 70.4 points.

In contrast, the score for utilizing work automation tools was only 39.9 points. Building no-code-based Agents AI scored 40.5 points, while designing AI agent workflows scored 48.0 points. The difference between the competencies for understanding and verifying AI and those for utilizing work automation reached a maximum of 31.3 points.

By employer type, employees at private companies had the highest competency scores. The overall score was highest for private-sector employees at 61.7 points, followed by public-sector employees at 56.3 points and the unemployed at 55.0 points. On a 5-point scale, private-sector employees were classified at Level 4 (application level), indicating they can freely apply these skills in their work, while public-sector employees and the unemployed remained at Level 3 (practical level).

The gap between groups was widest—ranging from 9 to 10 points—in the areas of work automation, AI technology utilization, and AI trends and leadership. These areas were also the three lowest-scoring competencies among all participants.

In contrast, the gaps between groups were relatively small—ranging from 3 to 5 points—in the areas of basic understanding of AI, AI problem-solving, and AI tool utilization. The overall average scores in these areas were relatively high, at 60 points or above. Multicampus Corporation analyzed that the greater the disparity in competency levels, the more pronounced the gap based on employment environment became.

Ko Min-jeong, Director of the AX Learning Innovation Center at Multicampus Corporation, stated, “The reason why employees at private companies have the highest AX competencies—and, among these, practical competencies such as work automation are higher than those of the unemployed or public sector employees—is likely because they have had more opportunities to apply these skills in real-world work situations.” She added, “Going forward, the success of an organization’s AX transformation will depend on whether the training content translates into practical application and the generation of results.”

Multicampus Corporation explained that by conducting AX competency assessments at the organizational and departmental levels within corporate settings, it is possible to identify gaps in execution capabilities across departments and determine training priorities. Currently, some large corporations are incorporating these assessments into their organizational AX transformation strategies, and Multicampus Corporation provides customized AX training roadmaps that progress from assessment to training, hands-on practice, and practical application.