The effectual application of AI to human resources problems and extended e-hrm adoption practice presents very different challenges. They cover anything from practical to conceptual, like the fact that the nature of data science analyses when thematically used on people has serious conflicts with criteria societies usually see as crucial for making significant decisions about individuals. We give consideration to the gap between the fact and promise of artificial intelligence in human resource management and suggest just how progress might be made. E-HRM has multi varied functions with the scope of AI capabilities i.e., updating Employee Information, training, recruitment, Automation of low-value tasks, employee engagement & AI in human capital management. Whereas barriers and challenges in adopting AI in e-HRM is absence of skilled talent, privacy concern, ongoing maintenance & complex integrating capabilities. Organizational Managers can conduct skill gap assessments and accordingly plan digital training opportunities for employees. Conversational AI can help managers and employees track such training and development. AI may or can be effectively embedded into the entire employee lifecycle association with the organization, from the comfort of recruitment and onboarding, to HR solution distribution and profession pathing thereby providing a bespoke employee experience. As HR is evolving day by day, trends will keep on changing in rapid pace. Some organizations have previously embraced the trends, while others are still to adjust to this noticeable change, being unable to anticipate the future or shortage of real information.

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Keywords: HR, Human Resource, e-HRM, Artificial Intelligence, AI, Machine Learning, Deep Learning.