Description:Artificial intelligence can be referred to as a technique that acts like an individual’s brain and apply human intelligence in numerous disciplines to enhance the efficiency and productivity of various industries. It consists of diverse inputs to provide outputs in the field of HRM. It includes three essential mechanisms - advanced algorithms, high- speed computation large volumes of quality data, which differentiates it from an ordinary software. This technology uses algorithms which connects quality data with fast computation services and can perform multiply tasks that require human cognition. With the advent of AI, organizations have undergone a revolutionary change in the decision-making process and has redefined various management models. AI technology offers important opportunities for enrichment of various HR processes, such as talent acquisition, payroll, self-service transactions, policies and procedures and reporting. HR professionals believe that collaboration of AI with various HR practices will enhance the people related decision making process. The advancement in HR technology, has encouraged the availability of real-time data for organizations but they still rely on their intuitions and instincts for drawing insights from data. This creates delays in drawing insights from the data which gradually becomes outdated. AI helps HR to extract insights from data and provide suggestions on real time basis. AI can eliminate various human biases and discrepancies in a sensitive function like Human Capital Management. Hence, decisions are more data- driven, consistent and unbiased. The application of AI is seen majorly in five HR functions such as analytics and metrics, time and attendance, talent acquisition, training and development, and compensation and payroll.
Incorporating technologies like AI and analytics in HRM have proved to be way beyond just a tool. Previous studies have illustrated the impact of AI on various HR functions such as using techniques of data mining and extraction tools in employee selection and recruitment, detect knowledge hiding, a smart sensory mechanism for assessing productivity of employees and intelligent agent technologies for employee development. Nevertheless, till now the studies have emphasized the role of AI in human resource at a functional level. However, the emergence of AI-powered machines such as robots and its application in various tasks related to human interaction and collaboration including product development, customer service delivery and industrial production have established a new domain for research. Though these technologies have now become an integral part of the businesses, their still exists many controversies regarding the application of AI-based analytics within the human resource functions. Hence, the managers and the employees have an obligation to use, augmented reality and games, big data analytics, simulations, algorithms, social media, machine learning in day to day lives which helps to support the decision- making processes.
In spite of several articles on AI and analytics, there are very few research-based studies on its integration in HR. Hereafter, there is a paucity of academic research carried out in the field of AI and HR. The aim of this invention is to look at different HR practices and understand how digitization plays an important role to enhance its efficiency. Previous studies have illustrated the difference between the promise and reality of AI in HRM. Nonetheless, this gap is deteriorating with the quick expansion of AI applications. This is qualitative research which adds to the concept of integrating AI and analytics in HR. This study describes various HR functions where AI has been incorporated and how it has benefitted these functions more effectively and systematically. The findings illustrate that by gathering and analyzing meaningful data through HR analytics and AI organizations can improve expenditure, operations, and productivity for the better. Finally, the key challenges faced by the organizations in adoption of HR technology are highlighted. The study concludes with illustrating various strategies for the implementation and promotion of AI-based HR technology to enhance organizational performance as well as future research implications. Fig.1 Depicts the HRM in the AI -Age.

In today’s era of technological innovation, organizations are continuously being influenced by different HR interventions. Various functions in HR department like recruiting, selecting, motivating, developing and retention of high performing employees in the organization continue to remain significant, but needs incorporation of different approaches to work. Many companies have adopted complicated data collection technologies and analytics for improving process of talent acquisition, therefore verifying the technological transformation in HR processes. The use of technology in HR can increase efficiency and effectiveness of service delivery, reduces the administrative functions, and permits HR to focus more on the strategical aspect. With the increase in easy access to data there is a paradigm shift from being administratively oriented to being more strategically oriented in the HR department, which has led to the re-structuring of decision- making processes thus generating novel HR opportunities for individuals who are involved in “complex, judgment-oriented and demanding tasks and responsibilities”. The advancement in HR technologies has encouraged the evolution of sensors and decision-making through composite algorithms for real-time monitoring of employee and work place.
The terms Artificial Intelligence (AI), Machine Learning (ML) and Big Data have evolved in the business world. The concept of AI was first coined by John McCarthy also known as father of AI. It can be defined as “an intelligent machine which includes automation theory, information processing and cybernetics” which can help to solve various cognitive problems and execute activities similar to an intelligent individual. AI includes Machine Learning and Predictive analytics. Big data can be referred to as huge, fast flowing, and high-variety data which acts as the fuel essential for advanced predictive analytics and machine learning. The top priority for CEOs is to have right talent strategy as the organizations need to grow in an increasingly complex, competitive business landscape. HR leaders rely on analytics to inform, measure, and refine their strategies. HR analytics has gained substantial importance in last few years. Artificial intelligence (AI) and machine learning (ML) are fueling HR Analytics advancement with competences to predict high- performing employees and identify talent at risk. Organizations have realised the importance of integrating AI in HRM so as to gain competitive advantage in global economy. As HR organizations mature in their analytics capabilities from descriptive to diagnostic to prescriptive and predictive, the key challenge for HR professionals is interpreting the data to resolve issues and effectively advise business leaders. Having the data is not similar to being able to use it effectively. The need of an hour is to convert this raw data into meaningful information which eventually has led to the rapid growth and development of HR analytics. The capability and inventiveness of HR have turn out to be chief mechanisms of a successful business. As a result, the main challenge for the businesses is to win the battle to acquire superior HR talent. Consequently, numerous methods and means of evaluating the HR have been developed.
The concept of evaluating, rating, and gathering HR intelligence is known as HR analytics. It can also be termed as HR intelligence, predictive analytics, talent analytics and workforce intelligence and people analytics. It can be referred to as a procedure that includes data mining, workforce forecast models and investment analysis or as a methodical procedure of collecting and analyzing data and further communicating the meaningful analytics result to support organizations accomplish their strategic goals. HR analytics practices include HR metrics, selection research, and benchmarking and employee surveys. Considered HR analytics as an evidence-based approach for making better people-related decisions to solve certain HR issues. Competitive intelligence has empowered HR department to focus more on the bottom line of the organization. Findings from different researches have concluded that performance of the organizations that are using HR analytics is better than their competitors as they tend to recognize the best talent among the workforce and identify the innovative opportunities.

1. AI and HR Analytics – Talent Acquisition:
Talent acquisition is among the most important functions in HR. HR professionals and recruiters devote a lot of fruitful time in screening and sourcing resumes, attracting best talents, scheduling and conducting assessments and preliminary interviews, informing the applicants about the status of their interview and finally, onboarding. Such tasks have been reduced enormously with the help of analytics and AI. The talent acquisition software has eradicated nearly 75% of the work associated with the recruitment process. Inclusion of AI in HRM can encourage organizations to revamp their organizational strategy. HR analytics can correlate large volumes of data and give insights about attrition, diversity, employee satisfaction and demographics of the current workforce. These insights can suggest some impressive employee proposition that can lead to retention and attraction of good talent. HR analytics tools can help to evaluate measures like number of visits made by the candidates to the career page and how many of them have actually been converted fruitfully. It helps to focus on engaging existing employees in the recruitment drives and encourage hiring through referrals. Also, some analytics tools lay down parameters beforehand to identify good, average and bad quality candidate for successful hiring. The most difficult task for the HR department is to find and hire employees that could convert innovative ideas into a successful venture or brand. People Analytics or Talent Analytics is the process of collecting and processing data that helps to predict whether or not a given candidate will be a good fit for a given job. Analytics can be used to identify key features in job and employees and matching these job variables with pool of candidates, predicting the retention and attrition rate of the employees and recommending some monetary/non-monetary rewards and other compensation packages to encourage longevity. Fig.2 Depicts the benefits of HR analytics.
Artificial Intelligence can make hiring tasks simpler and quicker by using different data analysis tools and predictive analysis. AI is free from all kinds of conscious and unconscious biases and discriminations. Hence when people are identified by means of the algorithms, it is much quicker, more precise, and reasonable as it eliminates bias which results in healthy work culture and minimizes grievances and complaints on the part of employee and further improves employees’ satisfaction level. One of the crucial functions of the hiring process is acceptance of offer letter acceptance and onboarding process. Many candidates, these days, dropout post acceptance of offer letter. Hence it is important to keep a follow up with them at regular intervals which are done with the help of AI. Lastly, orientation program for all new joiners is conducted by all companies to familiarize them about the company’s profile, work environment, policies and procedures, rules and regulation. Nevertheless, during these orientation programmers’, nearly 90% of the employees overlook or skip important information. Thus, intelligent bots help HR executives in generating new employee profiles and also employees can interconnect with these chatbots that are programmed to explain the doubts regarding company guidelines and procedures, employee benefits and insurance of employees. Additionally, Industry 4.0 inspired smart HR 4.0 have been employed in HRM to redesign processes such as talent offboarding and onboarding and talent development.

2. AI and HR Analytics – Training and Development:
The knowledge, skills and attitudes of employees play a vital role in achieving overall goals of the organization in an efficient, cost effective & sustainable manner. With each year passing by, organizations are spending approximately $350 billion on workplace training worldwide. The advent of big data in learning process has enhanced the interactive learning “anytime/anywhere” experience. Over the years, different methods of training including traditional or technology- enhanced classroom training, and eLearning have, revealed interesting results. Around 20 to 30 percent of concepts studied during leadership trainings, transform into actual practice. Hence, a strong analytical base is very necessary for designing the right Training and Development Course for the employees, which will enhance their performance according to company’s desired standard. Analytics can predict needs of company which helps to make right decisions to new skills. Based on these needs, the existing employees can be trained in the most cost-effective manner rather than hiring new staff. This will help to assess the exact need and help to make the right decisions to bring new skills in the organization. HR analytics also specifies if that skill set is a short or long-term requirement, which gives an insight into whether to hire a contractor or to invest in expensive training. Analytics can help to inspect the training requirements of employees and facilitates in advance arrangements of training material and coordination. Thereafter, proper recording of training and development evaluation of undertaken course is mandatory and referred in next course for the consistent improvement in their efficacy and relevancy for business needs.
nalytics also measures the effectiveness and efficiency of various training programs, assesses how well the succession programs train the employees to acquire important positions in order to ensure smooth functioning of the processes. Analytics gives insights into the impact of training on employee retention, for example associating training cost with turnover rate and training programs with the longest tenure employees. It enables to track the proportion of high- performers to non-high performers, identify training needs, measure performance enhancement after training and analyse impact of certification and training programs on the organization’s financial performance. Learning data can quantity and identify the employee groups which have the lowest engagement and factors which may contribute to small score, and whether more training is required for the improvement of the situation. It helps to correlate learning metrics to business metrics and can investigate specific training programs which had an impact on this financial performance of the organization. The introduction of AI in training and development has accelerated the personalized learning experiences among employees. An AI-enabled intelligent tutoring system (ITS) pre- existed since 1980s which was used at the college level and in the military services. More than two eras ago, experts have discovered that intelligent systems entrenched with techniques built on cognitive science, might drastically enhance the learning results in high school students who were learning algebra. Subsequently, a chain of arduous researches has verified those results when applied to other levels and subjects.

3. AI and HR Analytics – Employee Retention:
The most significant obstacle that businesses must overcome in the present environment is not only to effectively manage their human resources but also to keep their employees. Considers the retention of employees to be the most important aspect of companies' concerns with human resources (reducing employee turnover and attrition). Within the realm of predictive workforce analytics, the predictive retention analysis is thought to be among the most advanced and trouble-free solutions that have been put into place. Sometimes, the algorithms are even able to spot the employees before they have actively developed a desire to leave the firm. For the purpose of predicting employee turnover, businesses are developing predictive statistical models that are based on the signals and behaviours employees exhibit in the course of their normal work. This information can be utilised by managers in a variety of ways to encourage employee retention, such as through the provision of awards and recognition as well as individualised incentives. As a consequence of employees leaving the company, predictive analytics can also assist in determining the characteristics of the line managers. Several different metrics relating to former employees, such as their routines, performance ratings, feedback, compensation levels, and levels, could be helpful in understanding the leader's profile and the relationship between the actions of a former manager and the reasons why employees left their positions.

4. AI and HR Analytics – Performance Appraisal:
Performance feedback and appraisals are a usual part of any workplace. Some organizations are still relying on the traditional methods of appraisal systems which does not demonstration the actual potential of the employee. It also involves a lot of biases as the manager might rate an employee based on favoritism. Hence it is necessary to employ data-driven strategical tools such as analytics and artificial intelligence (AI) that is capable of enhancing human opinion while gathering feedback of the performance. It has been observed that top-performing organizations are relying on analytics instead of intuition for decision-making which distinguishes them from low- performing organizations. The huge data collected is of little use, if it cannot be transformed into meaningful information. Also, analytics makes it simpler to collect, retrieve and document various types of data related to performance from various resources (both internal and external) which offers manager with better insight to witness employee performance in terms of both behaviour and outcome. It reduces a lot of subjectivity biases and makes the entire process of performance appraisal more reliable and accurate. Hence, HR analytics can help upsurge perceived accuracy of the performance appraisal system by providing more accurate and unbiased data linked to employees’ performance behavior.

Various researches have illustrated the challenges faced by the organization in the implementation to technologies such as analytics and AI in HRM with regards to employees losing jobs, different professional demands, need for new skills development and talent management dynamics. On the contrary, a report published by KPMG revealed that most of the CEOs are confident that AI will generate more opportunities for employees in comparison to the number of opportunities it reduces, however most of HR managers carry a different opinion. This perceptional difference is because the organizations consider integration of technology in HR from functional perspective as employees feel that their jobs will be relaced by AI. However, not much research has been carried out on the AI-powered robots and its interaction with human workers, which will in turn act a dynamic tool Moreover, most of the HR managers lack the skills and capabilities to use technology-enabled tools such as analytics in HR. Previous researches have addressed various barriers to the adoption of technology in HR such as lack of organizational support , lack of resources and workplace culture and illustrated the importance of quality data for effectual analysis. Though organizations are generating large volumes of data, identifying the meaningful and structured data which is updated continuously, is essential for successful implementation of HR analytics. Additionally, employees and their managers sometimes misuse the IT resources and share the confidential information of the organization. Apart from this, employees face several psychological challenges like burnout, anxiety and stress along with “impossible expectations” owing to continuous technology change in the organizations. New-age organizations have realized the significance of HR analytics and AI to make decisions more data-driven, quantified and objective. The increasing perception to quantify HR function has paved the way for substantial usage of HR Analytics. AI and HR analytics have transformed the human resource department which in turn will result in various challenges for HR. , Claims:1. HR professionals believe that collaboration of AI with various HR practices will enhance the people related decision making process. The advancement in HR technology, has encouraged the availability of real-time data for organizations but they still rely on their intuitions and instincts for drawing insights from data.
2. However, the emergence of AI-powered machines such as robots and its application in various tasks related to human interaction and collaboration including product development, customer service delivery and industrial production have established a new domain for research.
3. Various functions in HR department like recruiting, selecting, motivating, developing and retention of high performing employees in the organization continue to remain significant, but needs incorporation of different approaches to work.
4. The concept of evaluating, rating, and gathering HR intelligence is known as HR analytics. It can also be termed as HR intelligence, predictive analytics, talent analytics and workforce intelligence and people analytics.
5. Artificial Intelligence can make hiring tasks simpler and quicker by using different data analysis tools and predictive analysis. AI is free from all kinds of conscious and unconscious biases and discriminations.
6. The knowledge, skills and attitudes of employees play a vital role in achieving overall goals of the organization in an efficient, cost effective & sustainable manner. With each year passing by, organizations are spending approximately $350 billion on workplace training worldwide.
7. New-age organizations have realized the significance of HR analytics and AI to make decisions more data-driven, quantified and objective. The increasing perception to quantify HR function has paved the way for substantial usage of HR Analytics.