An analysis of the talent acquisition process using artificial intelligence and machine learning tools among hiring professionals in India

Abstract

The simulation of human intelligence by machines, particularly computer systems, is known as artificial intelligence (AI) and a subfield of artificial intelligence and computer science called machine learning (ML) employs data and algorithms to develop model is capable of carrying out specific tasks. Artificial intelligence and machine learning tools transformed talent acquisition by automating tasks, reducing bias, improving candidate experience, and providing data-driven insights for better decision-making. Implementing technologies can give organizations a competitive edge in attracting and retaining top talent however it is essential to balance automation with human insight to ensure fairness and ethical practices throughout the hiring process. Even though artificial intelligence and machine learning have promise to improve the talent acquisition process, there are several drawbacks and challenges that organizations need to consider and address to ensure fairness, accuracy, and a positive candidate experience. Balancing the benefits of automation with the need for human judgment and ethics is crucial in using technologies effectively. This study is both exploratory and descriptive with the salient purpose of gaining familiarity and accurately portraying the current position of artificial intelligence and machine learning-enabled talent acquisition processes in organizations. It explores the significance and utility of artificial intelligence and machine learning in the talent acquisition process, identifies different machine learning algorithms that can be used and their functionality, simultaneously evaluates the impact, and elaborates on the drawbacks and challenges of its application. The present study finds that the application of technology is in the growth stage and there are still doubts and barriers to its adoption, in the end, it provides suggestions and recommendations to different stakeholders of the talent acquisition process.

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