A Study on the Impact of Artificial Intelligence on Human Resource Management
SUBMITTED BY
Oishi Biswas , Prerana Sharma , Shreyashi Das, Laxmi Bharti
MBA 4TH Sem
Commerce and Management
Kalinga University, Naya Raipur
UNDER THE GUIDANCE OF:
Mr. Rakshak Bharti
Assistant Professor
Kalinga University, Naya Raipur
ABSTRACT
The impact of artificial intelligence (AI) on human resources management (HRM) is profound, driving major shifts in how organizations approach workforce management. AI is fundamentally changing key HR processes such as recruitment, performance management, employee development, and HR administration. In the recruitment space, AI-powered tools can automate the initial stages of hiring, streamlining tasks like resume screening and interview scheduling. These technologies are able to analyze large pools of applicants, matching their qualifications and skills to the job requirements. This can lead to faster, more accurate hiring decisions and help organizations build diverse, high-performing teams. However, there is a potential risk that biases embedded in the data used by AI systems could reinforce inequalities, making it crucial for companies to ensure that their AI tools are regularly audited for fairness and inclusivity.
In performance management, AI is transforming how employees are evaluated and developed. Traditional performance reviews can often be subjective and inconsistent, but AI can introduce a more objective and data-driven approach. By continuously tracking key performance indicators (KPIs) and employee behaviors, AI can provide real-time insights into performance trends, identify potential areas of improvement, and even predict future challenges. This enables HR professionals to tailor development plans for individual employees, fostering personal growth and enhancing overall productivity. However, the reliance on AI for performance evaluation raises concerns about employee privacy and the potential for over-monitoring, highlighting the need for clear ethical guidelines and transparency in how data is collected and used.
