Challenges and opportunities of artificial intelligence adoption in human resources management within the ICT industry in Armenia

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Type of the article: Research Article

Abstract
This study investigates the challenges and opportunities of artificial intelligence (AI) adoption in human resources management (HRM) within the ICT industry of Armenia. Utilizing a mixed-methods approach, the analysis is based on a structured survey and in-depth interviews conducted with 30 HR specialists from Armenian ICT companies in Yerevan between January and February 2025. The results of the expert survey were analyzed using descriptive statistics, frequency analysis, and cross-tabulation tests in SPSS software. The findings revealed significant opportunities for using AI in human resources management within the ICT sector. These opportunities include improving management processes for employees and saving time and financial resources through the effective use of artificial intelligence in HRM. However, there are also evident challenges, such as the comparatively slow rate of AI integration in HRM (only 43.4% use AI tools in HRM), and risks associated with human–AI imbalance (27.8%), information protection (27.8%), job displacement (18.5%), AI bias (16.7%), and resistance to change (9.3%). Nevertheless, the findings revealed no correlation between company size and the level of AI implementation in HRM (Pearson Chi-Square = 0.143, p = 0.931), which does not support the hypothesis of a ‘digital divide’ within the sector whereby larger companies are more likely to implement AI than small and medium-sized enterprises. The study highlights the importance of balancing AI technology with the human factor, developing ethical standards, investing in AI literacy, and implementing targeted training programs.

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    • Figure 1. Distribution of the companies by size and AI usage in HRM
    • Figure 2. The most compelling reasons why AI is not yet being utilized in HRM
    • Figure 3. Distribution of responses (%) on the potential risks of AI integration in HRM
    • Table 1. The composition of the expert panel by the size of the company
    • Table 2. Main questions included in the questionnaire
    • Table 3. Considering training implementation related to the use of AI tools in HRM
    • Table 4. Chi-Square tests
    • Conceptualization
      Armen Grigoryan, Anahit Melkumyan
    • Project administration
      Armen Grigoryan
    • Supervision
      Armen Grigoryan
    • Writing – original draft
      Armen Grigoryan, Anahit Melkumyan, Lusine Karapetyan, Maria Sahakyan, Meri Badalyan, Bella Gabrielyan
    • Writing – review & editing
      Armen Grigoryan, Anahit Melkumyan, Lusine Karapetyan, Maria Sahakyan, Meri Badalyan, Bella Gabrielyan
    • Formal Analysis
      Anahit Melkumyan
    • Methodology
      Anahit Melkumyan, Lusine Karapetyan
    • Data curation
      Lusine Karapetyan, Maria Sahakyan, Bella Gabrielyan
    • Validation
      Lusine Karapetyan, Maria Sahakyan, Meri Badalyan
    • Resources
      Maria Sahakyan
    • Software
      Maria Sahakyan
    • Funding acquisition
      Meri Badalyan
    • Investigation
      Bella Gabrielyan