Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{153760,
        author = {Satish S. Narkhede and Isha P. Kulkarni},
        title = {Automated Recruitment Tools: Current Trends and Further Directions },
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {8},
        pages = {439-443},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=153760},
        abstract = {Exponential and multifold increase in the requirements for diverse job profiles and subsequent flooding response for the vacancies, pose a serious limitation on the time bound manual hiring process. In such a scenario automated recruiter systems are emerging to facilitate the screening, background verification, payroll, and other administrative task which not only can save time, money, and efforts and also ensure selection of the best candidate. Artificial Intelligence powered recruiting systems are studied and presented in this research study. Role of Machine Learning algorithms like Decision trees for predicting the suitability and the performance is explored.  Various current research trends and algorithmic developments are summarized and future directions are listed from the perspective of practically deployable automated recruiting systems. },
        keywords = {Artificial Intelligence, Automated Recruiting, Machine Learning.},
        month = {},
        }