The Influence of Prompt Engineering Competency on Employee Performance in Private Companies Using Generative Artificial Intelligence
Keywords:
Prompt Engineering Competency, Employee Performance, Generative AI, Work Quality, Human–AI CollaborationAbstract
The rapid adoption of Generative Artificial Intelligence (AI) has transformed workplace practices by supporting writing, data analysis, decision-making, and problem solving. However, access to Generative AI does not guarantee improved employee performance because output quality depends on users' ability to formulate effective prompts. Empirical evidence regarding the influence of prompt engineering on employee performance remains limited. This study examines the influence of Prompt Engineering Competency on Employee Performance, particularly work quality, among employees in private companies using Generative AI. An explanatory sequential mixed-methods design was employed, consisting of a quantitative cross-sectional survey followed by qualitative interviews. The quantitative sample comprised 312 employees who regularly used Generative AI tools, selected through purposive sampling. Twenty participants were subsequently interviewed. Data were collected using a five-point Likert-scale questionnaire and analyzed using Structural Equation Modeling (SEM) and thematic analysis. Prompt Engineering Competency had a positive and significant influence on Employee Performance (β = 0.62, p < 0.001), explaining 38% of performance variance (R² = 0.38). Prompt Design Skill and AI Output Evaluation were the strongest competency dimensions. Qualitative findings indicated improvements in work quality, accuracy, clarity, efficiency, and problem solving. Prompt Engineering Competency is an important workforce capability for maximizing Generative AI benefits. Private companies should integrate prompt engineering training, AI output evaluation, and responsible AI practices into workforce development and organizational competency frameworks.
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