Introduction
Business is changing rapidly, and sticking to a traditional approach in modern management is often a destructive strategy for an efficient, fast-paced business in a changing marketplace. Meanwhile, there is no need to maintain an essentially conservative approach because technological advances present many development opportunities. Artificial intelligence is an excellent solution that can significantly raise all business KPIs (Massaro, 2021).
Current Problem
We know that at Business House, you hold high moral values and strive to improve clients’ intellectual awareness from economic, financial, and managerial perspectives. This noble goal really needs to evolve and be realized, as it has enormous potential. In the meantime, it is impossible not to face barriers to one’s commercial and professional success. In the case of Business House, these barriers are, unfortunately, the human factor, especially under the pressure of an external agenda. High competition, changing political regulations, and even COVID-19 have serious implications for open-type companies, affecting employee turnover and evolving the company’s corporate environment (Mirzaei et al., 2021). There also no denies the element of work stress, resulting in employees remaining in the workplace but not demonstrating high performance due to emotional burnout and low motivation. Statistics tell us that about one in five employees of companies quit because of work stress (AIS, 2021). Meanwhile, it is known for a fact that it costs a company much more to fire an employee than to retrain them, which means that the company not only loses the number of effective employees but also faces serious economic losses (Paychex, 2019). In this regard, it should be said that Business House is now at a crossroads of professional development; on the one hand, the firm may face a crisis of confidence and incur losses, but on the other hand, it begin to manage change and implement technology.
Synthesis
So why don’t we take the current problem, the failure of human resource management, and combine that with promising artificial intelligence technologies? This is not a fantastic idea, and many companies are actively using the cloud for their own benefit. These companies are Amazon, IMB, and Google, which use AI to optimize hiring and manage KPIs (Manson, 2017). However, research shows that the number of such firms is much higher at 38%, or about four in ten companies worldwide use computer technology to some degree to manage to hire (Tiwari et al., 2021). No significant limitations exist to extrapolate the success of “giants” and rank-and-file companies to Business House work practices.
AI Capabilities for Hrm
Talking about how AI can be successfully integrated into human resource management practices, the first thing to focus on is the practices that can be improved. First and foremost, of course, is robust optimization by enhancing the ability to store and access data from anywhere with access. Second, AI robs practices of the possibility of human error, resulting in minimized unexpected costs. Thirdly, such systems are highly adaptive, which means that they can easily be modified to meet the needs of a manager or HR department if desired. Meanwhile, AI makes it possible to quickly summarize previous data in order to build management and strategic planning strategies based on it (Singh & Shaurya, 2021). Speediness, in general, is an iconic advantage of AI-driven systems, as, in this case, the company saves significant time in collecting, systematizing, and processing the personal data of job applicants and employees. The need to access paper archives is also eliminated, as, in this case, all the necessary data is securely encrypted in the cloud. Sixth, with the help of generalization and systematization, employee training planning issues are also solved, as artificial intelligence allows for the personalization of training strategies. It is worth saying that employees appreciate the personalized approach to them, which helps to increase their engagement and motivation (Kuhl et al., 2020). Thus, the possibilities of AI for HRM turn out to be wide-ranging and promising.
Practical Example
Any HRM problems in the Business House can indeed be solved by using AI. For better training of current employees, artificial intelligence uses KPIs accounting personalization systems to set up training strategies and not provide employees with knowledge that they already excel at. At the same time, AI will automatically monitor employee turnover and model company development based on budgeting, compensation spending, employee satisfaction, and perceived stress levels. Based on this data, HR professionals will build further engagement with employees, offer them promotions or training, and replace them if an employee is systematically underperforming.
The Importance of Strategic Planning
Based on the above, it is clear that implementing AI for human resource management is a highly desirable strategy for Business House. However, it is unacceptable to “just implement” AI systems because it will not result in the expected benefits; instead, a strategic plan must be carefully developed to manage any changes in the company in a systematic, planned, and calibrated manner. It is a fact that the use of AI for HRM will be a significant technological and operational transformation, which means that its reliable management is associated with risks and obstacles. Painless overcoming of such obstacles becomes possible only with strategic planning.
Communication Effectiveness
For a Business House in which the effectiveness of HR practices is threatened, it is critical to maintaining a high level of helpful communication. With high turnover and professionals rapidly leaving the company, communication between employees and clients is critical in the current circumstances. If clear communication is created between partners and a teacher begins to form an academically constructive environment to work with students and then leaves the company, it becomes a crisis of trust. Thus, communication in the company’s technological transformation is necessary in a strategic planning environment. All involved must be aware of the planned changes, actively discuss them, and develop networking.
The importance of communication grows especially strong when employees continue to be stressed because of their mismanagement. Staff errors, unevenly distributed workloads, and high stress become causes of tension (Vermeir et al., 2018). These tensions can undeservedly translate to students, resulting in a painful experience with Business House. AI aimed at improving HRM thus directly affects the quality of communication.
Corporate Values
An integral part of strategic planning is rethinking corporate values. In the case of Business House, values should focus on caring for customers and employees, recognizing the importance of compassion and managing for one another, unconditional mutual respect, and professional ethics. In addition, creativity and innovation should be actively encouraged, and employee expression and team building should be supported.
Three Phases of Transformation
The structure of overall change is appropriately divided into three phases. In the first phase, it is recommended to revise the expectations and skills of employees and implement an AI system for HRM. In the second phase, we must use the AI already implemented to analyze employee satisfaction and develop employee development strategies and damage minimization plans. Finally, during the third phase, provide HRM research and maintain a high level of corporate culture in the Business House to create an image of an attractive, highly moral company.
Conclusion
AI is tactical to HRM, so its operational implementation into Business House’s work practices makes sense. In the best-case scenario, the company will create a growth-friendly corporate environment in which employees and clients are willing to work for the good of the firm, sufficiently motivated, and interested in developing together. AI, in fact, will become an optimization tool that, if properly managed, will qualitatively enhance the professional level of the company. AI must be trained on a foundation of impartiality so that it analyzes employees’ KPIs based only on their professional skills and accomplishments but not on their personal lives and attitudes. AI will also improve the accuracy of selecting those candidates who will serve the company for a long time, which will reduce turnover. Consequently, it is recommended that the company begin strategic planning for this area as soon as possible in order to achieve the desired success.
References
AIS. (2021). Workplace stress. The American Institute of Stress. Web.
Manson, L. (2019). 3 technology companies are using artificial intelligence for human resources. SOMAG. Web.
Kuhl, N., Lobana, J., & Meske, C. (2020). Do you comply with AI? Personalized explanations of learning algorithms and their impact on employees’ compliance behavior [PDF document]. Web.
Massaro, A. (2021). Implementation of a decision support system and business intelligence algorithms for the automated management of insurance agents’ activities. International Journal of Artificial Intelligence and Applications (IJAIA), 12(3), 1-13.
Mirzaei, A., Rezakhani Moghaddam, H., & Habibi Soola, A. (2021). Identifying the predictors of turnover intention based on psychosocial factors of nurses during the COVID‐19 outbreak. Nursing Open, 8(6), 3469-3476. Web.
Paychex (2019). The true costs of firing an employee. Paychex. Web.
Singh, A., & Shaurya, A. (2021). Impact of artificial intelligence on hr practices in the UAE. Humanities and Social Sciences Communications, 8(1), 1-9. Web.
Tiwari, P., Pandey, R., Garg, V., & Singhal, A. (2021). Application of artificial intelligence in human resource management practices [PDF document]. Web.
Vermeir, P., Blot, S., Degroote, S., Vandijck, D., Mariman, A., Vanacker, T.,… & Vogelaers, D. (2018). Communication satisfaction and job satisfaction among critical care nurses and their impact on burnout and intention to leave: A questionnaire study. Intensive and Critical Care Nursing, 48, 21-27. Web.