Artificial intelligence (AI) is affecting the nature of work in every sector and is also transforming human resource management functions across the employee lifecycle. It is automating routine work, improving decision-making, and enabling more personalized employee experiences. Its large-scale adoption is to increase efficiency and boost productivity which impacts how companies attract, hire, retain, and skill their employees.

Most people put AI under a common umbrella but there are different technologies used for a specific task. Artificial intelligence in human resource management can be understood by looking at how it works, what it can do, and how it adds value to organisations. From a technology perspective, AI in HR uses tools like machine learning to analyse employee data, natural language processing to screen resumes or power chatbots, and computer vision for tasks like identity verification. These technologies are often combined in modern HR systems, such as recruitment platforms that use AI to search, evaluate, and communicate with candidates. In terms of capability, most HR applications use narrow AI, implying they are designed for specific tasks like hiring, performance tracking, or employee engagement. Functionally, most HR AI systems learn from past data to improve decisions over time, such as predicting employee turnover or recommending training programmes. Most importantly, from a business perspective, AI in HR creates value in different ways: generative AI helps draft job descriptions or training materials, predictive AI supports workforce planning, assistive AI improves employee productivity, conversational AI enhances employee support through chatbots, and emerging agentic AI can automate entire HR workflows, such as onboarding or performance management, with minimal human involvement (Brandon Most, 2026).

The main benefit of AI in HRM is efficiency. By automating repetitive and time-consuming tasks, AI frees HR professionals to focus on strategic and human-centered work. It also improves consistency, speed, and the ability to process large volumes of data, which can strengthen hiring and talent decisions (Nelson Connects, 2025).

Despite bright prospects, AI in HRM raises pivotal concerns at the workplace. Research highlights risks such as algorithmic bias, limited transparency, resistance to change, and the possible dehumanization of workplace relationships. If AI systems are trained on biased data, they may provide unfair hiring or promotion outcomes. There are also ethical concerns around privacy and over-reliance on automated decision-making, especially in sensitive HR functions (Aguinis et. al. 2024).

Hence, AI can be used as an enabler at the workplace rather than a replacement for HR professionals. It needs to be introduced in a phased manner preparing employees and organisations with ethical considerations. AI needs to be introduced in a phased manner, so employees and organizations can prepare gradually, and ethical safeguards need to be built in from the start. A phased rollout reduces disruption, supports learning, and gives HR time to test and adjust to new workflows.

ORCID iD

Radha R. Sharma  https://orcid.org/0000-0002-1710-3888