Investigation of the Efficacy of Artificial Intelligence in Indian I.T. Firms’ Recruitment Practices

Abstract

Focusing on organizations situated in Chandigarh, this research seeks to understand how AI might improve recruiting methods inside Indian I.T. enterprises. This study delves into how four important AI technologies Natural Language Processing (NLP), Machine Vision (MV), Automation, and Augmentation impact various stages of the recruiting process, from sourcing candidates to screening them, engaging them, and finally evaluating their performance. One hundred fifty human resources and technical staff members participated in the study by way of structured questionnaires, and secondary data came from respected academic databases. This mixed-method technique was used. To determine if AI elements significantly improved recruiting results, Structural Equation Modeling (SEM) was used. According to the results, each of the four AI skills significantly affects how successful a recruiting campaign is. Machine vision and augmentation helped provide more accurate candidate evaluations, while natural language processing and automation were particularly important in enhancing speed and equity. AI-powered solutions are making the hiring process more streamlined, data-driven, and impartial. Using these findings as a roadmap, Indian IT companies may improve operational efficiency and the applicant experience via AI-integrated recruiting tactics.

Introduction

Artificial Intelligence (AI) refers to technology that mimics human intelligence, enabling machines to learn, reason, and solve problems. While definitions vary, AI has become a transformative force across industries, particularly in business management and human resources (HR). Companies are increasingly adopting AI to streamline operations, adapt to changing environments, and maintain competitiveness.

2. AI’s Growing Role in HR Management

AI is now a core component of HR practices, helping in:

• Streamlining complex HR functions

• Accelerating recruitment

• Enhancing training and workforce planning

HR is experiencing a functional shift—from task reduction to strategic augmentation of human roles.

3. AI in Recruitment: Applications in Indian IT Firms

AI is reshaping recruitment in Indian IT firms by improving efficiency, reducing costs, and enhancing hiring quality. Key areas of impact include:

• Strategic Preplanning: AI tools assist in forecasting hiring needs, defining job roles, and aligning recruitment with business goals using predictive analytics.

• Pre-Screening: Tools like resume parsers, NLP, and chatbots automate resume filtering, evaluate communication, and reduce bias.

• Selection: AI-driven video interviews and coding simulations offer objective candidate assessments based on verbal, non-verbal, and cognitive data.

• Candidate Engagement: AI chatbots and CRM tools automate communication and personalize candidate interactions, improving employer branding and offer acceptance rates.

4. Benefits of AI in Recruitment

• Time-Saving: Faster processing of applications

• Bias Reduction: Consistent, data-driven evaluations

• Predictive Analytics: Anticipates hiring needs and candidate success

• Improved Candidate Experience: Streamlined and personalized communication

5. Challenges and Limitations

Despite its advantages, AI introduces several challenges:

• Algorithmic Bias: Risks of discrimination due to biased training data

• Lack of Transparency: AI decisions may be hard to interpret or justify

• Data Privacy: Concerns over how candidate data is used and stored

• Cost and Accessibility: High implementation and training costs can burden SMEs

• Impersonal Experience: Candidates may perceive AI interactions as lacking human touch

6. Research Objectives

1. Assess the impact of AI tools (e.g., NLP, automation) on recruitment in Indian IT firms.

2. Explore candidate interaction with AI-based recruitment platforms.

7. Hypotheses

• H1: NLP impacts recruitment and selection.

• H2: Machine vision impacts recruitment and selection.

• H3: Automation impacts recruitment and selection.

• H4: Augmentation impacts recruitment and selection.

8. Conceptual Framework

The conceptual model supports the idea that AI improves efficiency, accuracy, and fairness in recruitment. AI automates tasks like resume screening and interview scheduling, enabling faster and smarter hiring decisions while reducing time-to-fill and improving candidate prioritization.

Conclusion

In Indian IT companies, the use of AI into hiring procedures has become a game-changer. This research demonstrates that by simplifying procedures, enhancing equity, and lowering manual labour, technologies like natural language processing, machine vision, automation, and augmentation greatly improve hiring results. AI has shown particular efficacy in activities like as applicant rating, resume screening, and video-based evaluations, which have accelerated and improved the accuracy of the hiring process. Though most participants had a good opinion of AI, there are still issues with transparency, an excessive dependence on algorithms, and the incapacity to evaluate soft skills. The results support a well-rounded strategy where AI enhances human decision-making rather than takes its place. Indian IT companies should concentrate on user training, ethical implementation, and hybrid models that blend automation and human control as AI technologies advance. Through this approach, they may fully use AI while preserving equity, openness, and strategic coherence in their hiring procedures.

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Copyright

Copyright © 2025 Bhupender Kumar. This 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.