Copyright © 2026 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{206132,
        author = {Douglas P. Roberts and Bhaskar Sinha and Courtney Jane},
        title = {Leveraging Artificial Intelligence to Enhance Online Faculty Recruitment},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {2},
        pages = {578-586},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206132},
        abstract = {The rapid growth of online education has transformed the teaching-learning paradigm in higher education worldwide, creating a strong demand for qualified faculty capable of delivering effectively for online and hybrid modalities. Academic institutions are facing challenges in recruiting good instructors who possess not only subject matter expertise but are also instructional competent, technology savvy, and flexible to virtual teaching-learning settings. Traditional faculty recruitment practices and methods using labor intensive outreach, manual screening, and subjective assessment often fail to identify appropriate candidates suited for online instructions. Artificial Intelligence (AI) has emerged as a transformative solution capable of modernizing faculty recruitment by enhancing efficiency, accuracy, standardization, and workforce planning. This paper investigates how Artificial Intelligence (AI) platforms and systems can be leveraged to improve faculty hiring processes, specifically for online teaching-learning settings.},
        keywords = {Academic collaboration, adjunct faculty, data analytics, DSS, explainable AI (XAI), hybrid instruction, LMS, NLP, search committee, structured evaluation.},
        month = {July},
        }