View of Computer Aided HR in the Era of Artificial Intelligence

Computer Aided HR in the Era of Artificial Intelligence

Associate Professor, Amity Business School, Amity University, Uttar Pradesh, India.

b_{Associate Professor, Vivekanand Education Society’s Institute of Management Studies and Research, Mumbai, India.} c_{Trainee – HR, DHL Supply Chain, Mumbai, India.}

Article History: Received: 10 January 2021; Revised: 12 February 2021; Accepted: 27 March 2021; Published online: 20 April 2021

Abstract: AI has immensely revolutionized the various human resource practices like, recruitment, employee engagement during work from home, compensation, benefits, and payroll etc leading to improved decision-making etc. However, it is imperative to understand the pre-requisites (i.e. skill sets and competencies) that HR professionals need to possess for successfully adapting AI and working effectively and efficiently in the era of uncertainty like the COVID times.The paper focuses on gathering insights from professional around the world in the area of AI and Human Resource Management. The methodology used in the paper is semi structured interview technique. The results of the study have been used to build the AI-HR readiness framework, which can be used to design various training programs for HR professionals to achieve a sustainable AI integration into HRM to ensure better preparedness to deal with uncertainties in business.

Keywords: Artificial intelligence, Human resource management, Training, Readiness, Remote working

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Artificial Intelligence (AI) is an area which contains wide range of algorithms and machine learning tools that can rapidly ingest data, identify patterns, optimize and predict trends. Due to its high potential, its adoption is being treated as the fourth industrial revolution, commonly referred to as Industry 4.0 (March 06, 2020).HR is an organizational function dealing with the biggest asset of any organization, its employees. Although it may be a little too early to sound the alarm, McKinsey’s latest forecast of AI’s impact on the global economy suggests that AI will generate $13 trillion in global economic activity by 2030, Christopher has also reported that the use of AI is expanding in the HR, there are challenges like training and privacy which can be addressed (Christopher, 2019). Scott O’Connor has reported the top 3 applications of AI in HRM and these are:

1.Recruitment and onboarding

2. Internal mobility and employee retention 3. Automation of administrative tasks

As the rollout of technology within the workplace becomes more and more prominent, it seems more HR and recruitment leaders have begun to adopt AI. Gartner’s latest survey found that 23% of organizations which were already using AI, were employing this in the recruiting domain. He said that presently human are living in an era in which AI capabilities are reaching new heights and have a major impact on how the businesses (Helen Poitevin, 2018). HR executives believe that merging AI into HR administrative functions will benefit and improve the overall employee experience. Humans and learning machines are working together to produce an ever-increasing quantum of HR data in the cloud, and the use of AI analyses offer better insight into how to execute and operate. The success of any organization depends on how effectively it combines people, process and technology intelligently to deliver transformational value at optimized cost. HRM should use AI with alacrity to boost its functions. The present COVID -19 has forced organizations to realign their business strategies and the various HR strategies to fit to wide varied situations like work from home, number of hours spent on television, stress level etc using various AI tools.

Present research study focuses on the penetration of the use of AI into the HR functions worldwide. It also highlights the challenges that an organization might face while adopting this technology along with the steps that the organization takes in order to ensure a smooth implementation of AI into the HR functions.

2. Literature Review

AI is already making inroads into human activities in several ways and such changes were never even envisioned before. AI is revolutionizing HR processes, facilitating improved decision-making and waiving out human bias (Bersin, 2018). AI (including deep machine learning and automation) is not any mysterious computerised unit, but a way to predict, learn and optimise decisions, based on several criteria. Embarking with recruitment, AI has started spreading its roots in other HR areas too, viz. employee development and learning, management and leadership, fraud and compliance, well-being and employee management, employee self-service and candidate management (Bersin, 2018).

46% of the HR professionals feel that they will be using AI at a high degree by 2023. However only 14% strongly agree with the fact that they are knowledgeable in the area of AI (myHRfuture, 2019). Though most of the workers these days normally use software to handle their workflow, however, very few use information technology to run the entire HR process (Paget, 2019). In fact, it is being widely felt that HR should take the initiative and it should be a leader in driving AI software into the workplace, revolutionizing the HR functions and improving the employee experience and satisfaction (Meister, 2018).

Technological advancement has transformed how HR professionals use to functions and emphasise on greater competencies to sustain in the competitive environment (Choi, 2015). An HR professional needs to be tech smarter as these modern technologies need to be monitored by personnel who have an acumen and fundamental knowledge of HR to ensure its appropriateness and legality (Andors, 2005). George and Thomas (2019) have reported that AI would help to streamline and boost the efficiency and agility of HR functions.

The growing technology has changed the core competencies in HR giving rise to e - HR domain which is one of the most important function of HR. It indicates how technology provides ease in carrying out various HR functions such as recruitment, people management, skill development, training, career planning, and performance management. While the modern machines can do the mundane work, HR can work on more critical aspects such as counselling an employee and retaining programmes (Lobo, 2018).

Automation is the next step in HR‘s evolution especially in the following five priority tasks: (i) Applicant tracking and onboarding, (ii) Time and attendance, (iii) Records management and reporting, (iv) Benefits enrolment, and (v) Payroll (Diassi, 2016). Robotic Process Automation (RPA) is a technology which is producing notable labour and cost saving efficiencies, and improving data management for HR.

RPA is carrying out rules-based, transactional processes in the HR domain that need minimum or no human judgment (Zielinski, 2018). A study conveys that with advent of E-HRM, the HR professional can focus on strategic development, value creation, green HRM, knowledge management and intellectual development (Obeidat et al, 2016, Sharma, 2014, Sharma, 2016). E-HRM has 2 important goals (1) Decrement in cost, (2) improving HR services (Ouk et al, 2009). Monotonous, time-consuming but important administrative tasks which were done manually before by the HR team are slowly being handled by automated machines and software. Embracing AI within HR will accelerate processes and create more time for achieving the human touch (Pickup, 2018). Sheilla et al. (2018) have also reported on the opportunities of the applications of emerging new age AI techniques on the human resource management.

Smolcic et al. (2014) conducted a research study on affordability and advantages of Human Resource Information System (HRIS)in the small business sector. Advantages being immense and plausible, the surge of technology has brought with it many pocket-friendly solutions in the market.

Automation, internet of things and artificial intelligence is creating concern for many HRs (Taylor, 2018). Advancement in technology can be considered as a new opportunity since new jobs will be created which never existed before (Poulos, 2018). In fact the loss of jobs and value-addition both are associated with AI, and will be implemented in the HR functions faster than what the experts think (Poirier, 2018). HR, as a profession, will see minimum job displacement because human intervention is the core of HR which cannot be replaced (Allinson, 2018).

AI’s impact on HR practices is far reaching, which has not only improved the decision-making but also strengthened the interpersonal relationships between an employee and an employer (Michailidis et al., 2018). An understanding of HR leaders to disregard AI’s technological aspects and instead, grasp the flavour of what it is trying to achieve, will precede a very important time for HR. (Yano, 2017).

Creative thinking, judgement, problem solving, and empathy are some salient differentiating factors that humans have over machines. Those whose root purpose is critical and creative thinking, and building human networks, will thrive. In order to sustain and flourish, it is important to work with technology, and not compete with it (Pasupathy, 2018).

The HR professional will be facing a series of challenges in regards with diversified workforce like rising skill shortages, reconstructing talent infrastructure and talent practices and creating a new way of working that creates win-win situation for everyone (Porter et al, 2011).In comparison with human mind, the speed of AI to process data is much faster, however, to be valuable, the quantum of data should be huge (Kevin Wheeler, Future of Talent Institute, 2018). Better decisions and accurate predictions are the result of bigger data (Maurer, 2017).

As a result of the speedy and uncertain changes, stepping into AI should be systematic. Its impact on people losing their job in nowhere near what was expected a few years ago. Everyone is excited about the new opportunities that the wave of AI and deep machine learning is bringing into the work force. (Poulos, 2018).

The future generation is more inclined towards gig economy as it provides them with working flexibility and to work on their specialized area of interest (Wang, 2018). Since Millennials and Generation Z are the largest workforce and the generation that will represent nearly 75% of the workforce by 2030 (Fromm, 2015), freelancing and contract base jobs are increasing at an alarming rate (Cunningham, 2015). Organizations that focus on catching up with world-class performance as a result of their HR activities must focus on the following 5 areas: (i) Digital Transformation (ii) Decision-making and Analytics (iii) Resource allocation (iv) Service Design and Delivery (v) Business Partnership (El-Khoury, 2017).

HR, as a sector, is still learning how automation and deep machine learning can fit into its offered services. However, it would not take much efforts to incorporate that into the services because of the resilience and creativity

that HR people possess (Ward, 2018). Rewriting competencies so that they are more simplified, on account of AI and automation, identifies not just leadership and collaboration but also what is called effective communication. It is also being able to weed out the fluff as one goes through the levels, without the unnecessary diversions (Wilson, 2018).

There are differences in the AI investments in China and the U.S., beckoning what they believe will confirm their competitiveness. Enhancing the employee experience and enabling self-serve HR is what the U.S. focuses on. On the other hand, China emphasises on talent intelligence and automated talent management (Bravery, 2019).

While the evolution of AI continues and gets smarter its uses will become more ubiquitous. Not only will AI transform the HR tasks for talent management, recruitment, and employee engagement, but it will also improve benefits management by lowering the costs for the employer (Clark, 2018; Given, 2019). Gilbert (2018) has reported that HR would need to get a little more comfortable with the thought that AI could be making a decision but is not necessarily able to explain why.

The times of COVID-19:

In this pandemic situation, employees are getting more comfortable with technology and tools and employers are able to take advantage of this with a greater ease. The AI tools have really helped in to make this happen (Ken Lazarus, August 2020). The COVID situation has definitely aided the world to take a leapfrog of five years in using the advanced digital technologies with their ability to enhance efficiency, automate processes, cut down on operational costs, and leveraging the use of AI technology in abundance (McKinsey, 2020). From handheld devices like Tracesafe to Ahura AI tools, many HR digital devices can be integrated to improve productivity. This process of change management is at the heart of the technological transition led by COVID wherein the HR professionals are more focused on how to retain talent, how to engage their employees, how to motivate the employees for the maximum productivity in the work from home scenario, and last but not the least, what new specialist talents to hire (Uma Ganesh, May 2020).

AI & Work from Home (WFH):

AI can be the engine in speeding up disruptive innovation by introducing a data-driven approach to invention and creation. In order to do so, the imperative is to embrace change and innovation (Daryl Lim, 2018). More than half expect AI and automation to replace 20 percent of their companies' current jobs, but Mercer noted that the World Economic Forum expects these technologies to create a net 58 million new jobs by 2022 (Future of Jobs, 2020).

Digital transformation technologies such as Cloud, Internet-of-Things (IoT), Blockchain (BC), Artificial Intelligence (AI), and Machine Learning (ML), constitute a bulk of the of what is being adopted by organizations as part of their transformation effort (Rahul De et al, 2020). The Telegram assisted E-work media developed could help entrepreneurial learning and could be used as supporting media for blended learning with the features that have been available. Also, the trainer could control the cognition through a quiz feature (Diana Pramesti, 2020).

2.1. Objectives

To enlarge the understanding of usage of AI in HRM in the changed scenarios the research paper attempts to study the application of emerging AI tools used for augmenting HR functions and to answer the following research questions:

1. How AI is used for various HR functions around the world 2. Which HR functions can be easily integrated with AI

3. What are the various challenges faced by HR professionals while integrating AI in HR functions 4. Which readiness framework can be proposed for HR professionals for usage of AI in HR

3. Methodology and data

The explorative research method was used in this research and the data was collected from HR professionals working worldwide and engaged in the area of HR. By exploring the perceptions of professionals who have had experiences with the usage of AI in HR functions, it was possible to gain multiple insights in the area of AI and HR. Each individual ascribes certain characteristics and attributes to any given situation. The questionnaire was designed to gain an understanding of these variations in the interpretation of utilisation of AI. Merriam (1998) had noted that qualitative research delivers the greatest promise of making significant contributions to the knowledge base and practice of education, because it is focused on discovery, insight, and understanding from the perspective of those being studied. The sampling method was stratified sampling where respondents were chosen and interviewed only if they were experienced in using AI in the field of HR. HR professionals who do not use AI in any of their processes were not catered to.

Being a global study, the participants were discovered, identified and contacted via LinkedIn. The semi structured interviews were conducted through phone, mail, skype and other mediums. The 26 respondents were spread globally.

Analysis – The responses generated through e-mails were compiled in an Excel sheet. Interactions and discussions over skype and telephone were held to clearly understand and gain sufficient and tangible information and knowledge about the responses based on the questionnaire. These responses were further scanned, analysed and studied through critical analysis by seeking further clarifications where required to complete the data sheet. The respondent data notes were screened and categorised to compile the detailed analysis. In fact, for every

question, a distinct response was recorded and analysed, by every participant. Ultimately, all unique responses were paraphrased as per each question and these were used to arrive at final results.

4. Analysis

Figure 4.1. Countries of the respondents:

Figure 4.1 shows the countries of the respondents. The respondents belonged to countries like US, UK, Netherlands, Nigeria, Canada, Israel, India, Ireland, Jersey and France. 54% (14 out of 26) of the respondents are from US, followed by 11.5% from UK.

Figure 4.2. Designations of the respondents:

Figure 4.2 shows the various designations of the respondents.The respondents had designations of Director, Consultant/Advisor, HR leader, Founder, Chief Executive Officer, Manager and Team Leader (about 15-16 % each) (Figure 4.2). Thus the respondents seemed had sound and requisite knowledge in the areas covered in the questionnaire. The category of ‘Others’ included HR professionals and executives who are very much indulged in the use of AI for HR Functions.

Figure 4.3. Experience (in Years) of the Respondents:

1 1 1 1 1 1 1 2 3 14 0 2 4 6 8 10 12 14 16 C o u n t Country

Countries

France Jersey Ireland India Israel Canada Nigeria Netherlands UK US

4% 16% 16% 15% 15% 19% 15%

Designations

Chief Executive Officer Counsultant/Advisor Director

Founder HR Head/Leader Others

Figure 4.3 shows the experience of the respondents. 58% (35% with more than 3 decades) of the respondents had a rich experience of 20 - 40 years in the HR field and those having 1-10 years of experience were the minimum of 11.5%.

4.4 AI adoption in HR

It was found that 92% of the respondents believed that HR professionals are not well prepared for the AI wave. The HR professionals pointed out that the personnel working in the HR area do not possess a clear understanding of AI and appreciate its optimum usage in HR function. They lacked the required knowledge in the AI and thus would require time to understand the application of AI and its importance in taking sound business decisions. It was observed that at times HR employees are kept out of the loop on a technological transformation initiative. Therefore, in such cases, the role of the HR is discounted by the IT professionals. A few respondents also pointed out the lack of technological orientation of HR professionals. A lot of organizations are yet to adopt cognitive technologies, so HR professionals in such organizations continue to work in the same manner as they have always worked. In the essence of the trainings, certifications and certificate programs on cognitive technologies that are tailored towards the HR function, some HR professionals do not go the extra mile in seeking out the knowledge that is available. It was found that the future HR roles are still evolving; hence some HR professionals are at a loss as to how to develop themselves accordingly. As a result of this some are adopting a ‘wait and watch approach and they continue to embrace the status quo. Very few find the incentives of learning and innovation. Another observation was that hardly anyone was keen and progressive towards new innovations. Adopters of AI were few and there were several inhibitors.

A couple of respondents believed that HR is prepared for this transition. In one of the largest global bio pharmaceutical company, employees were interested and eager to engage in AI practices. They did not know much about the technology, however, simple ways should be adapted to make them interested in learning and adapting the same. As HR professionals become more digital, they use the Pareto principle to focus on the solution that solves most of the problems. Perfection is the enemy of completion. As HR professionals understand the business more, they begin to ask better questions and they begin to normalize the data they require. As the data becomes normalized and digitized, AI can then build logic to help.

4.5. Penetration of AI into HR functions

Some respondents also felt that despite the broad horizon of various HR functions, the effective penetration of AI has been quite less. Nonetheless, the area of talent acquisition and recruitment have experienced a shift worldwide. A respondent brought out that all the areas in HR need to develop a more data driven approach. The most analytical approach he saw, is in recruitment. AI is becoming a key driver behind job - candidate matching and automating communications with candidates, including applicant feedback. These are arguably the two big areas where AI is most effective, and this eliminates human bias and results in increasing efficiency in candidate assessment and communication.

AI has 3 branches: (a) Robotics- Physical movement, (b) Machine learning, (c) Linguistic programming. In HRM, Machine learning and linguistic programming has been used in functions like recruitment: screening candidates, application tracking system (ATS.). Some chatbots would be prepared in future for Q and A for policies, e.g.: vacations in balance etc., PTO (pay-time off vacation), regulations regarding health.” Other areas like employee engagement, payroll and daily administration also see a major shift towards automation. Companies feel that they had looked at employee churn and worked on predicting employee resignations. All other areas are open and there are opportunities. It is Predictive analytics for me. Companies like TrenData offering future forecasting of people but people in HR would find it too advanced for them.

General observation was that all areas of HR would be affected by AI but differently and in different percentages. Respondents feel that no area of HR has been penetrated effectively yet. The most activity is currently

3 8 6 9 0 1 2 3 4 5 6 7 8 9 10 1 - 10 11 - 20 21 - 30 31 - 40 N O . O F PS EXPERIENCE (YEARS)

Experience (in years)

in Talent Acquisition as ATS vendors try to add AI capabilities to their aging and cumbersome (and increasingly ineffective) ATS systems. Early automation initiatives target Onboarding. They do not feel that expect that eventually Payroll will be almost entirely automated, followed by Benefits Administration (US), Training Administration, Compensation Administration, Time and Attendance (PTO), Stock Administration, Government Reporting, Two examples have been highlighted presently:

i. IBM Watson – IBM when calling its prospective candidates detects the geographical location of the candidate and suggests the candidate to interact with the IBM employees located at nearby location who are willing to interact. Also, AI is used more in cultural engagement – Data scientists analyse the data to build employee engagement.

ii. Amazon – In Amazon every morning when the employee logs in he is asked the question how do you feel about the company?

4.6 AI Implementation

The responses were analysed to bring out the following main issues in implementing AI in making the HR functions of the companies more effective.

Introducing AI in HR – A Strategy: A properly defined entry strategy in order to ensure a smooth amalgamation of AI into the HR processes would require the following:

1. Vision – Define clearly the objective of AI implementation.

2. Education – Identify the skill gaps, and also the people with interest and capability to lead the transformation. People need to learn about what AI is and that they not have fears but should be willingly and happily embracing

3. Reskilling – As soon as any automation initiative is announced, the organization needs to simultaneously announce the reskilling efforts that the organization will be undertaking to address those employees who will be affected by the automation initiatives.

4. Change Management – Continuous and ongoing communication with people affected directly and also the rest of the organization which will be apprehensive about it, even though their area may not be directly affected by it (yet).

5. Job Reconfiguration – All jobs will need to be reconfigured to reflect the automation of routine, repetitive tasks that will then be replaced by tasks and activities of higher order of critical-thinking skills.

The implementation phase would take into account the readiness and acceptability of the employees, their training outcomes, process mapping, sorting, cleaning and tabulating the data, running small pilots and trials, and accept the transformation as a “Process Redefinition”.

A respondent also noted, that the Proof of concepts are important to understand the efficacy of these technologies. Scope and attaching a value to these implementations are next. Continuous measurement of pre- and post - metrics will give more confidence for future implementations.

Implementation challenges for an organization: AI is often an answer looking for a question. Lots of organizations are keen to implement AI as they hear so much about it, but they seldom start with a concrete business problem. Most of the respondents listed down the following challenges that organizations face while implementing AI:

i. Data aggregation – very few companies have all their data completely residing in one system. The ability to aggregate, normalize and cleanse the data real-time is something only very few companies can do.

ii. Business acumen – HR people typically do not have good business acumen and do not understand the business problem they are solving through AI.

iii. Cultural and organizational issue – The reasons why so many of the digital transformation initiatives are now reporting as not meeting their business objectives is because too many organizations viewed them primarily as technology projects and not primarily as people projects.

iv. Change management, training of employees, redesigning infrastructure and other issues related to ethics, legality, compliances, and security fall in the way.

One example can cited that recruiters feel that they are being replaced and not that they are just getting assistance with the AI tools. The shift to AI will also affect the type of activities in workers roles. First challenge will be to get support from the users in large scale, the second will be to first understand the shift in roles activities, and how to handle this shift.

It may be understood that the application of cognitive technologies in organizations is still at an early stage, some organizations are yet to define a digital transformation strategy and for those who have, HR’s role in the digital transformation journey may not be clearly defined. In such situations, it becomes difficult for HR to determine if there is a need for AI implementation as C-level support and resource allocation for such initiatives may be lacking. It is difficult to gain confidence of the upper management and show return on investment.”

“Even when HR department in organizations have defined the areas to deploy AI, they also need to determine whether they want to buy AI solutions off-the-shelf or (if the organization has the technical capacity internally) deploy tailor-made solutions developed in-house. Irrespective of which option is adopted, there will be the need to ensure that adequate capacity exists within the organization to monitor output from AI solutions and confirm that they do not generate biased outcomes.

Implications in the gig economy era: As the implementation of AI solutions becomes more pervasive, some jobs that gig workers currently do will become less available as AI solutions will be relied upon to handle such roles.

Another way to look at this is: that people at times quickly shift from one job to another. However, companies would want to retain the employees AI can be used in the learning processes on how to retain talent and encourage the role of happiness in an employee life cycle.”

Humans are complex elements whereas robots do not get tired, do not ask for a pay raise, and do not go on strike and have a more predictable output. As machines replace the workforce, a company becomes ever more competitive, delivering goods quicker and cheaper. Employees are made redundant and out of a job. Efficiency does not sound so good then. Half of the workforce is expected to be replaced by robotics in the next 20 years. Some go further and predict 80% of jobs to disappear in the next 10 years. Such drastic change to the employment landscape is already starting to happen and is a real threat to the stability of the society. However, present authors feel that there could be other views also that the implantation of AI would generate several other types of jobs replacing the present ones as happened with advent of computers and IT.

In the industrial revolution, as some jobs became redundant, it created new jobs as the need arose. Now, as autonomous vehicles become a reality, truck and taxi drivers will have to retrain and learn new skills. As mobility is enhanced and costs are lowered, a whole new world of requirements for our everyday life will be created, and jobs with it. Take entertainment for example: effortless and cheap transportation will increase the need for entertainment as it becomes easier to move about. May be new sports will be created. Robots, in whatever shape they come, will very soon be taking over most dull, dirty and dangerous jobs. Driving, warehouse fulfilment, deliveries and even apple picking, when the fruit is perfectly ripe, will all be done by robots. Artificial intelligence will go a step further by assisting complex tasks such as financial auditing and speech writing for politicians and other leaders in order to positively influence the largest number of voters possible or sustain the share price of a listed company. Even coding will be impacted on by artificial intelligence, allowing code to heal itself and correct bugs. Just like at the time of the industrial revolution, some jobs will disappear and others will be created.

“AI cannot work without big data, so the gig economy can provide even more data, despite the differences in the model. Popular platforms are already using AI to enable easy access to resources. AI will change the world as one knows it in every industry, so with the gig economy, AI can be efficient and enable humans to connect with a range of people and resources.”

If people in the gig economy are in task-specific roles (i.e. data entry replaced by Optical Character Recognition), that could be problematic. Those in the gig economy need to consider broadening their skill sets to make themselves more marketable and focus on jobs that are not as specialized as before.

A few respondents view the implication of AI in the gig economy as a threat. IT will give a false sense of security to some, that in the long run will blow up in their faces. “The biggest issue in the gig economy era is going to be finding candidates who are not actively searching for a new gig. AI should be applied to predicting which potential candidates could be approached to join an organisation for a specific gig rather than waiting for them to apply.

4.7 Role of Emotional Intelligence in the application of AI

EI will be the most important competency for people, especially in the AI era. By understating people involved, and its effect on them, takes implementation a long way. Key issues will be in the Ethics domains not EI – how AI is used, with what permissions, with what protection for privacy, with what confidence Algorithmic bias is minimised, etc. That is not to rule out the importance of EI – but that is the key to everything that HR does and not specific to AI implementation. There are attempts to put EI into AI and that of course is a big and interesting topic. There are and in near future there would be many more AI products that would generate vast amounts of new data on organisational mood and sentiments, providing HR [ and others ] with more nuanced and timely insights that should – with good EI in HR - lead to more sensitive, engaging and responsive communications, feedback and engagement with employees.

One of the respondents suggested that AI brings with it a lot for EI. He had observed that his four year old daughter yells at Alexa when it does not do what she had expected it to do. Skills need to learn interpersonal management, upskilling, and how to work with machines.

One of the respondent has pointed out that AI is a machine, therefore, it definitely misses EQ. On the other hand, humans have a lot of emotions. In order to have a balance between professional and personal life, work has to be made emotionless. Humans do empathise with each other, but at the end of the day, as professionals, one needs to act mature. Robots do the robotic work and humans do the human work. We need humans to become more emotionally intelligent, empathetic and caring to one another. One needs robots and AI to focus on the inhuman work of data analysis, number crunching, routine, repetitive, precise work that fallible humans are inherently not good at doing anyway.

While AI solutions will be able to provide output at a higher rate and level of efficiency than humans, human judgement in decision making will still be greatly required. As such, emotional intelligence for the human workforce will be an even more important skill in the world of work.

Stronger competencies/training for HR professionals: Respondents mentioned the following competencies that any HR professional should possess in this era:

ii. Basic Technological Understanding of AI iii. Data Analytics

iv. People Analytics v. Project Management

Apart from these, HR professionals need to be familiar with the concepts and the different facets of AI but they do not necessarily need to become technical experts in AI. More important for HR professionals are to focus on the HR core competencies which will be most necessary in helping their organizations to adapt to the AI in the digital age. Those competencies are; Organizational Design, Change Management. Re-skilling, Job Design, Talent Resource Management, Contingent Staffing, Performance Management, Worker Contracting, Career Path Design, Employee Experience/Engagement, Data Visualization. In addition, they need to develop their “soft skills” in Creativity, Communications, Collaboration, Critical Thinking, Problem Solving and Empathy.

Training for HRs should include the following: i. Ethics and AI

ii. Case studies on successful and failed AI implementations iii. An understanding of GDPR and other data protection regulations iv. General knowledge on AI

One of the respondents revealed that for AI to be truly impactful it should require very little training, it should be embedded in existing processes, technology and programs, and it should not stand on its own. It’s an enabling technology, not an end result in itself. So it should take much to enable HR or the business to utilise it, when it is effectively implemented.”

What is new in the role of HR? With the revolutionary wave of AI (machine learning, robotics and automation) in HR, few of the tasks which are now being handled by humans would be performed by machines efficiently and the roles of HR would change dramatically over the next 5 years. The new roles would be much different from what they are today. A part of the change would be identifying all repetitive tasks and re-focusing efforts on tasks that require more variety, cognition, problem solving and over-seeing bias creep and other harming things that a machine can do inadvertently.

A few of the designations crafted by the respondents are as follows:

Table.4.1

One of the respondent suggests the birth of a Talent Innovation Hub, where everyone does not look at the routine and follow the herd. “In the near future, we will need a bunch of people who think out of the box and brings in something new every day.”

5. Framework for AI Readiness in HR Professionals

The integration of AI in HRM is definitely going to be challenging but strategically impactful. With the amazingly evolving world and introduction of some mind-boggling technologies, AI in HRM is indeed going to be a milestone for HR professionals. According to Fig. 5, it all begins with HRs being trained on AI tools and Analytics. It does not indicate that one must be technologically advanced or intelligent but one must understand the implications well. It is very important for an HR to know which AI tool serves which HR function the best. Also, the HR must know to analyse and interpret the results that the AI tool portrays. For eg: The Hogan Assessments offers a Hogan Personality Inventory (HPI) which reveals the bright-side personality of a person. This can help a Recruiter to assess the job-fit for the candidate and make a decision accordingly. However, this is possible only if the Recruiter understands the analysis made by the Inventory or any other tool for that sake. Also, even if the candidate lands up on a positive result, the Recruiter must be wise enough to predict if that personality would fit in the job role as well as the organization well. Thus, to become a full-fledged AI trained HR professional, one will require a huge quantum of database, perfectly designed HR jobs, complete understanding of deep learning machines, their applications and their implications.

A completely AI trained HR professional can use his/her knowledge and database to ease out the everyday functions and mundane routine tasks. The functions of Recruitment, Hiring and Onboarding is going to sweep the most advantage of AI tools. Harver’s proprietary AI algorithm measures a candidate’s aptitude, culture fit, soft skills ability to succeed in career. Netflix, KPMG and Cognizant is already using this AI tool and have won an upper hand in hiring the best candidates (AIHR Digital, July 2020). Low valued repetitive tasks being replaced by AI and machines will definitely lead to more time which can be utilised for effective and improved decision-making. GeneSys Integrated Assessment System is a service of Psytech International which generates

Project Manager HRIS Analyst

Chief Data Analytics Officer Chief Experience Officer

Analytics Translator

HR Technology Wizard/ Digital Officer Chatbot Operator

AI Ethics Advisor HR Evangelist

profile charts and in depth narrative reports for decision-making and feedback. This assessment is already being used by multinationals like Deloitte, HSBC, Coca Cola, Tesco, Nokia and many more (AIHR Digital, July 2020). The introduction of Talent Innovation Hub is the most interesting and admirable suggestion of one of our respondents, where everyone does not look at the routine and follows the herd. In the near future, we will need a bunch of people who think out of the box and bring in something new every day. This will indeed result into attraction and retention of eccentric and quirky talent for one’s organization.

HRM, as a whole, will revive with the integration of AI tools. Strategic decisions related to succession planning and manpower planning with become easier and faster. Latest human capital management (HCM) technology and the emergence of AI and machine learning are now making it much simpler for organizations to identify and provide ongoing development for large populations of employees, which can help prepare them for senior leadership roles. However, organizations must be thoughtful and deliberate in creating processes that take advantage of all of the tools and capabilities that modern HCM can bring. Thom Brockbank and Ed Turi (Feb 2018) have proposed an elaborated 4-step guide for using AI and machine learning for succession planning. Use of such latest technologies also promotes internal mobility and interactions, thus strengthening employee-employer bonds. Automation of administrative tasks like scheduling of an interview and onboarding of an employee can be taken over by chatbots and robots respectively. Ultimately, all of this stimulates a model of remote working which seems to be of utmost importance in such a crisis time where Covid-19 is dictating the terms and conditions of world economy. Upscaling the use of technology and advocating its ease and advantages will surely create AI-HR evangelists in the long-term.

The spread of COVID-19, across the globe, and the related lockdown made digital work no longer just an option, but the new norm for many office workers. Many of us have now begun to make sense of a unique range of benefits of digital work tools. Many employees have subconsciously or consciously correlated digital work with not being able to meet their office peers and colleagues. However, it is COVID -19 to be blamed and not digital work that imposed physical distancing. Hence, it is important to keep in mind that digital work does not impose reducing the number of physical interactions. It instead allows focusing on bonding when meeting physically and for reducing travels to meetings that could also easily be held online (A. Richter, 2020).

6. Conclusion

In the coming years, the use of AI will definitely lead to sophistication of processes. It would unload the mundane administration and handle the data more maturely. AI would impact the era of Diversity and Inclusion by eliminating biases, discrimination and paving a way for absolute justice and fairness. “Adapt or Die” – is a mantra for all.

AI and Predictive Analytics will have a profound impact on the HR profession over the next 10 years. Spreadsheets and static analysis will be replaced with real time data analysis updates that are easy to interpret and take action. HR will be in the data business in a big way and HR professionals will be well served to get trained, educated and be continuously learning about AI and Analytics. The HR profession, partly as a consequence of tapping into the full power of data and AI, is in position to have meaningful impact on the running of the business and providing the CEO with powerful guidance, based on data, on key areas of the business affected by Human Capital performance. This represents an unprecedented opportunity for HR to fulfil its mission of driving business outcomes and having impact on the success of the enterprise by leveraging AI applied to Human Capital data.

“For the near future AI is a supplement. It will take some time before HR can be replaced. This should be motivation for HR professional to learn the business or become Techno-Functional. One can no longer just know theory. One must know application of theory and most likely technology (further application of theory).” While some look at the business leveraging side of AI, one of the respondent points out the human benefit. AI is going to make HRs more human and less technical. Too many HR professionals have been stuck behind screens and keyboard to address HR’s current data processing needs. That will be all done now by robots and smarter (deep learning) machines. That will leave HR professionals to focus on the individual employees and helping with the organization’s talent resources and creating employee experiences that will connect employees emotionally, mentally and spiritually to their work and engage their whole beings in fulfilling the missions of their organizations. Robotics companies may also help HRM in handling recruitment, hiring, data analysis, collecting the information, automation of low value repetitive tasks, reducing employee attrition, knowledge management, cognitive – supporting decision making etc.

Despite the fast-paced inclusion of AI and technology into the diverse HR domain, the human factor will be as important as ever. HR will not disappear because of AI, but HR will become more strategic, stream lined, efficient and agile. Some tasks will disappear but the human factor will be important. Where AI solutions take on large scale repetitive tasks previously handled by HR professionals, there will be faster turnaround time and HR professionals will also be able to free up time and resources to engage in more strategic responsibilities. The large volume of data that will be generated from greater process automation with AI will provide HR with an opportunity to develop deeper data-driven insights for the benefit of organizations. This will also help foster evidence-based HR practices.

A pandemic can have severe and lasting consequences, including changing the political contour of the world, destroying empires, and creating nations (Rahul De et al, 2020). In case of this Covid-19 pandemic, we can already witness and experience a dramatic shift in digital usage with impacts on all aspects of work and life. What this change brings to us is like a mystery, largely dependent on our acceptance and response to shaping of the emerging trends and dwelling them into our routine. And what good time, other than this distancing phase, do we need to make the most of it as a facilitator for adopting technologies like AI.

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