Artificial Intelligence Based Strategic Human Resource Management (AISHRM) for Industry 4.0

Business organizations face significant obstacles as a result of globalization. A highly competitive market has emerged as a result of globally interconnected processes and dynamically changing customer expectations. In order to gain an advantage over competitors in the industry, innovation and technological adaptation have become essential requirements. Therefore, the way to gain a competitive advantage with human capital is to align the aforementioned activities with organizational strategy (Siddiqui, 2018). With the help of technology, HRM activities are becoming more efficient, and artificial intelligence has emerged as a trend. The world is currently in the transitional era known as Industry 4.0, which is characterized by the use of big data to connect people and machines. Continuous digitization and digital transformation of the value chain using artificial intelligence will facilitate data exchange (Cezarino, 2020).

In the business world of Industry 4.0, machines will be connected to data and operate more effectively than humans during the production process. Robots that can work independently will eventually take over the labor market. Because each job requires a different set of skills, each job will be unique. However, there will be essential skills that will be in high demand and ought to be developed by the human resource management function. HRM would serve as the foundation of industry 4.0, which is the era of advanced and intelligent production (Davari, 2018). Sivathanu & Pillai (2018) states that HRM process like recruitments, development of skills should align with the business strategy of an organization. It also mentioned about the need for problem-solving skills that will be highly required to manage the internet of things (IoT), Big data, and AI (Sivathanu & Pillai, 2018).

The goal of industry 4.0 is to work with robots and other devices that are more efficient than humans, have human-like thinking, and are connected to each other via big data to increase industry productivity and efficiency at a lower cost. In the business climate of industry 4.0, choosing the best-talented staff for the association ought to be the procedure for HRM to guarantee that the organization will drive towards economical upper hand. Online job portals and electronic formats have replaced paper-based curriculum vitas, and millennials have adopted them. Electronic profile exercises and information, for example, Facebook, LinkedIn has turned into the foundation of up-and-comer determination interaction and HR supervisors right now utilizing web-based entertainment and expert organizations like LinkedIn to do the scouting (Davari, 2018).

According to Reilly (2018), AI has made it easier for businesses to find qualified employees by providing platforms that are more accurate and efficient, which improves the relationship between employers and applicants. Any business would anticipate that the strategic HRM task in industry 4.0 would be the screening process and decision-making regarding talent and skills that are in line with the company's strategy. The ideal company that specializes in software development based on artificial intelligence demonstrates how, while cutting recruitment costs by 70%, it can reduce biases in the candidate selection process through data screening and AI-supported decision-making (Reilly, 2018).

However, Dennis M (2018) shows the danger in using AI in ethical decision making by giving an example from college recruitment. Despite the fact that man-made intelligence is dependable in design acknowledgment and calculation, it can't supplant human. We can, however, directly disagree with the article because AI has the ability to recognize patterns, learn from past experiences, and recognize new patterns more effectively than humans. The best part of artificial intelligence is that it is based on big data, analytics, and machine learning systems that can learn from successful and unsuccessful recruitments in the past. AI that is used for strategic HRM should concentrate on HR analytics that are emerging in the HRM industry and learn from them (Dennis, 2018). Mc Kenney talks about how they came up with the idea of feeding HR analytics into a machine learning algorithm to find patterns and behaviors and find and predict employees who might quit. One of their customers has reduced unwanted attrition and reduced the retention bonus by $20 million thanks to big data gathered during series of exit interviews and ongoing HR data tracking. The aforementioned factors demonstrate the requirement for HR analytics as an AI-based strategic HRM process for industry 4.0 (Siddiqui, 2018).

From the Sri Lankan setting, organizations who are into computer-based intelligence based key HRM programming improvement ("C-SUITE HR," 2019) show evolvement of their vocation directing bot "SIA" in to HR examination based man-made intelligence answer for key HRM. Its examinations the information from the alumni level, and as a vocation direction bot, it shows a profession way as per the abilities of the up-and-comer. In addition to the candidate's preference, social media context, a series of interview inputs, and interview words will be analyzed for analysis and prediction. It demonstrates how HR analytics of a specific user are captured throughout their career and provides an organization-wide prediction (Davari, 2018).

Another major obstacle for HRM in industry 4.0 is the pressure to cut costs and the aging workforce that won't be replaced by younger generations. In industry 4.0, cost reduction will be a major consideration, and there will be pressure to complete products at the product level. As a result, human resource management (HRM) ought to be in line with utilizing the existing workforce's knowledge and abilities and carrying out operative trainings. In addition, HRM should consider cost-effective solutions that do not involve significant recurring costs. There is neither a process nor an application for robotic process automation. It's a technique that uses technology to automate a process to take the place of a person. RPA, which combines HRM and IT, has become ingrained in people's lives, serving as personal assistants like SIRI and Alexa. Here, artificial intelligence will play a crucial role in RPA's workforce development. RPA is a technology that enables businesses to set up bots or robots that can perform tasks or processes more efficiently than humans without human intervention.

SHRM ought to think about creating preparing projects and handover and assume control over process mechanization and recognize where a machine can work better compared to people and make the expense decreases. According to Blitz Technologies' paper "Robotic process automation - Automating the automation," RPA is the next technology that requires human judgment. However, as the preceding literature demonstrates, RPA will be able to operate with a high level of HR analytics that can gain through cyber-physical agents, align it with company strategy with a resource-based view, and stretch the algorithm through AI that is capable of handling aging staff and alleviate the pressure on a company to reduce costs.

 Conclusion

Industry 4.0, also known as industry revolution 4.0, is going to be a business environment in which machines that can think like humans will take over the labor market. Companies' value chains will be connected to data. Operations that were previously carried out by humans will be carried out by robots equipped with artificial intelligence. Additionally, they will perform such activities with greater precision and effectiveness. As a result of this revolution, businesses will need to pay more attention to strategic HR management. In industry 4.0, where organizations will be able to gain a long-term competitive advantage through human capital, human capital will be a much more valuable asset. In industry 4.0, artificial intelligence (AI) will be the engine. The vast majority of the workforce will be comprised of AI-based machines.

References

Cezarino, 2020. Smart industry and the pathways to HRM 4.0: implications for SCM. International Journal of Supply Chain Management, 8(2), pp. 5-19.

Davari, 2018. Industrial Artificial Intelligence for industry 4.0-based manufacturing systems. Internationa Journal of Management, 45(5), pp. 33-38.

Dennis, 2018. A conceptual artificial intelligence application framework in human resource management. International Journal of Human Resource Management, 20(8), pp. 11-28.

Reilly, 2018. A model for HRM strategic integration. International Journal of Human Resource Management, 5(2), pp. 99-112.

Siddiqui, 2018. Robotic Process Automation: The Virtual Workforce. International Journal of Future Revolution In Computer Science & Communication Engineering, 10(5), pp. 14-24.

Sivathanu & Pillai, &., 2018. New models of strategic HRM in a global context. International Journal of Human Resource Management, 12(6), pp. 78-86.