MYSKILLS: An AI-Powered Employee Skill Rating and Project Assignment System for Intelligent Workforce Management

Human resource management requires accurate employee skill assessment and efficient workforce allocation to ensure successful project execution. Traditional skill evaluation approaches rely heavily on manual assessments and static records, resulting in outdated information, subjective decisions, and inefficient resource distribution. This paper proposes an AI-powered Employee Skill Rating and Project Assignment System that integrates competency validation, natural language processing, and weighted skill matching for intelligent workforce management. The proposed framework enables employees to submit skill ratings, allows managers to validate competencies, and uses artificial intelligence to analyze project descriptions and extract required skills with corresponding importance weights. The system utilizes the Google Gemini API for natural language-based skill extraction and employs a weighted matching algorithm to rank employees according to project requirements. A three-tier architecture consisting of Next.js, Express.js, and Prisma-based data management provides scalability, security, and efficient workflow management. Experimental evaluation demonstrates reduced project requirement analysis time, improved skill verification, and effective candidate recommendation. The proposed system bridges the gap between conventional HR management approaches and AI-driven workforce optimization by combining automated analysis with human validation.