Artificial Intelligence Agent to Identify the Correct Human Resources

This system presents an innovative approach to streamline traditional recruitment processes and assist human resources in selecting the ideal candidates who align with the company's objectives. By addressing individual job requirements, the system ensures a good match between candidates' personal traits and company goals, creating a favorable environment for interviews. The Smart Recruiting System consists of four stages: Resume Parsing and NER(Named Entity Recognition) Tagging, Skill Set Classification using Big Data Analysis, Communication with New Recruiters through a Chatbot, and Improving Productivity with a Human Resource Management Portal and Skill Matrix. The process involves using advanced NLP models to extract information from resumes, including Named Entity Recognition and custom entity recognition. Big Data Analysis is used to predict job-specific skill sets and identify appropriate candidates. An automated interview system is created, analyzing candidates' behavior based on the Big 5 model. The system utilizes ASR, NLP, and deep-learning models to improve objectivity and efficiency. The Human Resource Management Portal integrates behavior analysis and candidate selection data, evaluating performance, training, and learning activities. The system identifies gaps in skills and connections, promoting cross-training and targeted development. This innovative approach combines advanced NLP, AI, and Big Data analytics to revolutionize recruitment practices. The demonstrated accuracy, efficiency, and objectivity show great potential for improving candidate selection, aligning individual skills with organizational goals, and ultimately enhancing the recruitment process.

I. Introduction

The caliber of an organization's human resources is a major factor in determining its performance, thus hiring the best personnel is essential to efficient operations. Effective Human Resource Management (HRM) strategies are necessary in Sri Lanka due to the country's expanding employment market in order to draw in and keep talented workers. There are inherent drawbacks to traditional recruiting approaches, including subjective biases and labor-intensive procedures. Those methods of candidate selection, such as assessing individual competencies, often fail to align with organizational goals. By concentrating on updating HR recruiting tactics to match individuals to job roles, increase efficiency, and decrease hiring errors, this study fills a research vacuum in HRM. Artificial Intelligence (AI) in HR recruiting is a potential option, but in order to maximize the matching process, cuttingedge technologies like deep learning and natural language processing. This allows recruiters to prioritize interviewing candidates, by lowering the likelihood of wrong recruiting while reducing high turnover rates and costly mistakes[1][2]. This paper explores the use of data-driven insights in job role analysis to streamline recruiting, identify talent gaps, and customize training and development plans, aiming to advance knowledge on HRM and AI integration in a rapidly expanding job market.