AI-DRIVEN TRANSFORMATION OF HR MANAGERS ROLE IN TRAINING OF EMPLOYEES
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INTRODUCTION. 4
1. LITERATURE REVIEW 8
1.1 Artificial Intelligence: foundational concepts, ethics and impact 8
1.2 Evolution and role of Human Resource Management 12
1.3 The role of Artificial Intelligence in Human Resource Management 16
1.4 Human Resource Management and employee training 21
1.5 Application of Artificial Intelligence in employee training 27
1.6 Summary 34
2. RESEARCH METHODOLOGY. 37
2.1 Research design 37
2.2 Secondary data collection 38
2.3 Primary data collection 39
2.3.1 Respondent selection 39
2.3.2 Data collection 41
2.4 Reliability and validity of research 44
2.4.1 Reliability 44
2.4.2 Validity 45
2.5 Summary 46
3. EMPIRICAL PART. 48
3.1 Application of Artificial Intelligence in employee training 48
3.2 Transformation of HR managers’ role and responsibilities 50
3.3 Challenges encountered with AI-based employee training 52
3.4 Comparison of Artificial Intelligence application in employee training in Russia and Europe .... 53
3.5 Summary 55
4. CONCLUSION AND IMPLICATIONS 56
4.1 Conclusion 56
4.2 Theoretical contribution 59
4.3 Managerial implications 61
4.3 Limitations and further research 63
REFERENCES 65
APPENDICES 74
Appendix 1. Interview guide 74
Appendix 2. Respondent profile 75
Appendix 3. Overview of coding process 76
1. LITERATURE REVIEW 8
1.1 Artificial Intelligence: foundational concepts, ethics and impact 8
1.2 Evolution and role of Human Resource Management 12
1.3 The role of Artificial Intelligence in Human Resource Management 16
1.4 Human Resource Management and employee training 21
1.5 Application of Artificial Intelligence in employee training 27
1.6 Summary 34
2. RESEARCH METHODOLOGY. 37
2.1 Research design 37
2.2 Secondary data collection 38
2.3 Primary data collection 39
2.3.1 Respondent selection 39
2.3.2 Data collection 41
2.4 Reliability and validity of research 44
2.4.1 Reliability 44
2.4.2 Validity 45
2.5 Summary 46
3. EMPIRICAL PART. 48
3.1 Application of Artificial Intelligence in employee training 48
3.2 Transformation of HR managers’ role and responsibilities 50
3.3 Challenges encountered with AI-based employee training 52
3.4 Comparison of Artificial Intelligence application in employee training in Russia and Europe .... 53
3.5 Summary 55
4. CONCLUSION AND IMPLICATIONS 56
4.1 Conclusion 56
4.2 Theoretical contribution 59
4.3 Managerial implications 61
4.3 Limitations and further research 63
REFERENCES 65
APPENDICES 74
Appendix 1. Interview guide 74
Appendix 2. Respondent profile 75
Appendix 3. Overview of coding process 76
People are using Artificial Intelligence (AI) more and more nowadays for different purposes. According to Forbes, within five days of its launch, ChatGPT had one million users, and between 2023 and 2030, AI is predicted to increase at a pace of 37.3% annually (Haan and Watts, 2023). AI is causing a significant change that affects not only technological fields but also healthcare, education, business, finance, criminal justice, and everyday life, and it is truly a social and technological phenomenon (Cheng, Varshney K and Liu, 2021). It is important to note that artificial intelligence has emerged as one of the 21st century's most significant technical revolutions in recent years. According to Makridakis (2017), like the digital revolution, which began in 1995, the Artificial Intelligence revolution is expected to peak in the next 20 years and likely have an even bigger influence than the combined effects of the industrial and digital revolutions. Moreover, the neural network ChatGPT has demonstrated by example that anyone can use AI in everyday tasks. For instance, OpenAI's freely available GPT-3, which exemplifies the state of the art today, generates cohesive and fluid language on a wide variety of subjects (Sokolova and Arkhipov, 2023).
Today world is experiencing a tectonic shift in the development of generative Artificial Intelligence, and it will have a significant impact on all business processes. Algorithms are integrated into apps that facilitate organizational processes as part of enterprise cognitive computing, which involves using artificial intelligence to enhance company operations (Tarafdar, Beath and Ross, 2019). Organizations are increasingly relying on Artificial Intelligence to improve operations and boost efficiency in the quickly changing business landscape of today. Using Enterprise Central Component (ECC) applications to automate routine and repetitive processes can greatly increase the speed at which information is analyzed, as well as improve the quality and reliability of the outputs (Tarafdar, Beath and Ross, 2019). According to a Forbes Advisor poll, a sizable 64% of companies think that Artificial Intelligence would help them become more productive overall (Haan and Watts, 2023). This illustrates the increasing belief in AI's ability to revolutionize corporate processes. Artificial Intelligence can also be applied in Human Resource management (HRM). According to Personio, during the next five years, 60% of corporate executives intend to improve their HR department through greater automation and Artificial Intelligence (Personio, 2023). Furthermore, an astounding 61% believe that AI will eventually replace HR professionals, particularly in light of recent developments in generative AI technologies like ChatGPT (Personio, 2023). Moreover, according to 66% of corporate executives, automation and Artificial Intelligence have a great deal of promise to solve issues like the requirement for the HR department to be more productive and efficient (Personio, 2023). The rapid application of AI in many industries proves their advantage, which should be applied in professional education. To provide quick and efficient training, deep learning networks have been considered a key area for instructional efforts (Sokolova and Arkhipov, 2023). It is worth noting the fact of application of neural networks in the system of training as an innovative method of rapid information processing, expanding the toolkit of training methods (graphics, sound, visualization), forming individual training programs, increasing the adaptability of training programs and reducing the time and labor intensity of training (Sokolova and Arkhipov, 2023).
Artificial Intelligence has the potential to transform the way businesses find, hire, and train new employees as well as evaluate and investigate opportunities for professional growth (Sucharita, 2024). Artificial Intelligence has great potential in a number of important areas in Human Resource (HR), including staff development and training. AI integration into training programs has emerged as a strategic requirement as businesses aim to upskill their employees and maintain their competitiveness. Moreover, using AI in training and development could cut down on HR participation and training duration (Sucharita, 2024). According to Guenole (2018), the most promising field is AI labeling of educational materials. The swift advancement of robotics and Artificial Intelligence has fundamentally changed how Human Resource Management is handled digitally (Chaplaev, Mazhiev and Idigova, 2023). In order to maintain the high pace of business development, new, modern technologies in the field of Human Resource Management are needed to quickly respond to the changing conditions of the external environment. HR specialists can take on the responsibility of handling routine tasks, while digital technologies can automate the process of solving production problems, providing a significant relief for business managers (Chaplaev, Mazhiev and Idigova, 2023).
The particular attention should be paid to how the digitalization of HR departments with AI affects the responsibilities and functions that HR professionals have in companies. AI technologies, such as natural language processing (NLP), machine learning, and generative AI, have revolutionized the way of approaching employee learning (Deloitte, 2016). Artificial Intelligence analyze a lot of data to find learning needs, gives custom content, and tracks progress closely. Since AI systems are flexible and rely on machine learning, the courses and material have been tailored to the requirements of the learners (Chen, Chen and Lin, 2020). Also, AI simulations and VR give real-like learning, make it more fun and help remember better (Xu and Xiao, 2020). However, big challenges come with this, including big costs for technologies, need for experts, and big changes. Also, worry for data safety, unfair AI, and moral concerns need thought and plans (Cheng, Varshney and Liu, 2021).
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Today world is experiencing a tectonic shift in the development of generative Artificial Intelligence, and it will have a significant impact on all business processes. Algorithms are integrated into apps that facilitate organizational processes as part of enterprise cognitive computing, which involves using artificial intelligence to enhance company operations (Tarafdar, Beath and Ross, 2019). Organizations are increasingly relying on Artificial Intelligence to improve operations and boost efficiency in the quickly changing business landscape of today. Using Enterprise Central Component (ECC) applications to automate routine and repetitive processes can greatly increase the speed at which information is analyzed, as well as improve the quality and reliability of the outputs (Tarafdar, Beath and Ross, 2019). According to a Forbes Advisor poll, a sizable 64% of companies think that Artificial Intelligence would help them become more productive overall (Haan and Watts, 2023). This illustrates the increasing belief in AI's ability to revolutionize corporate processes. Artificial Intelligence can also be applied in Human Resource management (HRM). According to Personio, during the next five years, 60% of corporate executives intend to improve their HR department through greater automation and Artificial Intelligence (Personio, 2023). Furthermore, an astounding 61% believe that AI will eventually replace HR professionals, particularly in light of recent developments in generative AI technologies like ChatGPT (Personio, 2023). Moreover, according to 66% of corporate executives, automation and Artificial Intelligence have a great deal of promise to solve issues like the requirement for the HR department to be more productive and efficient (Personio, 2023). The rapid application of AI in many industries proves their advantage, which should be applied in professional education. To provide quick and efficient training, deep learning networks have been considered a key area for instructional efforts (Sokolova and Arkhipov, 2023). It is worth noting the fact of application of neural networks in the system of training as an innovative method of rapid information processing, expanding the toolkit of training methods (graphics, sound, visualization), forming individual training programs, increasing the adaptability of training programs and reducing the time and labor intensity of training (Sokolova and Arkhipov, 2023).
Artificial Intelligence has the potential to transform the way businesses find, hire, and train new employees as well as evaluate and investigate opportunities for professional growth (Sucharita, 2024). Artificial Intelligence has great potential in a number of important areas in Human Resource (HR), including staff development and training. AI integration into training programs has emerged as a strategic requirement as businesses aim to upskill their employees and maintain their competitiveness. Moreover, using AI in training and development could cut down on HR participation and training duration (Sucharita, 2024). According to Guenole (2018), the most promising field is AI labeling of educational materials. The swift advancement of robotics and Artificial Intelligence has fundamentally changed how Human Resource Management is handled digitally (Chaplaev, Mazhiev and Idigova, 2023). In order to maintain the high pace of business development, new, modern technologies in the field of Human Resource Management are needed to quickly respond to the changing conditions of the external environment. HR specialists can take on the responsibility of handling routine tasks, while digital technologies can automate the process of solving production problems, providing a significant relief for business managers (Chaplaev, Mazhiev and Idigova, 2023).
The particular attention should be paid to how the digitalization of HR departments with AI affects the responsibilities and functions that HR professionals have in companies. AI technologies, such as natural language processing (NLP), machine learning, and generative AI, have revolutionized the way of approaching employee learning (Deloitte, 2016). Artificial Intelligence analyze a lot of data to find learning needs, gives custom content, and tracks progress closely. Since AI systems are flexible and rely on machine learning, the courses and material have been tailored to the requirements of the learners (Chen, Chen and Lin, 2020). Also, AI simulations and VR give real-like learning, make it more fun and help remember better (Xu and Xiao, 2020). However, big challenges come with this, including big costs for technologies, need for experts, and big changes. Also, worry for data safety, unfair AI, and moral concerns need thought and plans (Cheng, Varshney and Liu, 2021).
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One of the main limitations of this research is sample size of interview respondents. The study involved 13 HR representatives just from 7 enterprises, who introduced Artificial Intelligence in their employee training programs, indicating a small sample size. Moreover, only 3 respondents were from Europe and most of respondents were representatives of Russian enterprises. This small sample may not fully represent the wide range of experiences and viewpoints of HR professionals around the world. Moreover, the study's focus on Russia and Europe may restrict the generalizability of the results to regions with distinct cultural and economic backgrounds.
Additionally, the study used qualitative research method, such as conducting interviews with HR managers. Although this method offered thorough understanding of the perspectives and experiences of HR professionals, it may not have the statistical robustness and broad applicability of quantitative techniques. Incorporating quantitative data in future research could help verify and build upon the findings.
Furthermore, the research focused on small and medium-sized enterprises, which might possess varying resources, obstacles, and potential advantages in contrast to bigger corporations. The results may not be relevant to bigger enterprises with more intricate HR systems and larger budgets for implementing AI technologies.
Even though AI in HR had its ethical issues discussed in the study, it did not sufficiently cover such topics as data privacy, fairness or transparency. There is indeed need for more discussion about these significant considerations to make sure that AI integration into HR strategies is ethical as well as responsible. It is important to continue research in order to know more about the ethical considerations surrounding Artificial Intelligence that apply within Human Resources with a special emphasis on data privacy, fairness as well as transparency issues. Besides this, organizations should also find out how they will be able to develop policies needed for addressing these ethical dilemmas by making proper use of the AI techniques at their disposal.
There are several potential ways for future research. First of all, future research should strive to incorporate a broader and more varied selection of Human Resources professionals from different geographical areas and cultural backgrounds. This would improve the applicability of the results and offer a broader view on AI incorporation in HR. Moreover, in addition to qualitative insights, future research should include quantitative methods like surveys and experimental designs to enhance the study. This combination of methods can offer stronger evidence on how AI affects HR and confirm the qualitative results. Another way is investigation on how AI is being used and its impact on Human Resources in various sectors and organizations of varying sizes. Comparative research on AI adoption in diverse contexts can uncover distinct obstacles and successful strategies in small and medium-sized and large enterprise. Additionally, the investigation of the impact of AI-powered HR strategies on the overall employee experience can be conducted, including aspects like job satisfaction, engagement, and retention. HR managers can create AI applications that are easy to use and promote employee wellness by considering the employee viewpoint. Finally, comparative research across various regions and cultures can demonstrate the impact of contextual elements on the adoption and integration of AI in HR. This type of research can pinpoint strategies and frameworks tailored to specific regions for successful implementation of AI.
In summary, this research enhances the comprehension of how AI is changing HR processes, but further and broader studies are necessary to fully harness its capabilities and tackle the identified problems. By examining these potential areas for research in the future, academics and professionals can help improve AI-driven HR practices to be more efficient, moral, and diverse.
Additionally, the study used qualitative research method, such as conducting interviews with HR managers. Although this method offered thorough understanding of the perspectives and experiences of HR professionals, it may not have the statistical robustness and broad applicability of quantitative techniques. Incorporating quantitative data in future research could help verify and build upon the findings.
Furthermore, the research focused on small and medium-sized enterprises, which might possess varying resources, obstacles, and potential advantages in contrast to bigger corporations. The results may not be relevant to bigger enterprises with more intricate HR systems and larger budgets for implementing AI technologies.
Even though AI in HR had its ethical issues discussed in the study, it did not sufficiently cover such topics as data privacy, fairness or transparency. There is indeed need for more discussion about these significant considerations to make sure that AI integration into HR strategies is ethical as well as responsible. It is important to continue research in order to know more about the ethical considerations surrounding Artificial Intelligence that apply within Human Resources with a special emphasis on data privacy, fairness as well as transparency issues. Besides this, organizations should also find out how they will be able to develop policies needed for addressing these ethical dilemmas by making proper use of the AI techniques at their disposal.
There are several potential ways for future research. First of all, future research should strive to incorporate a broader and more varied selection of Human Resources professionals from different geographical areas and cultural backgrounds. This would improve the applicability of the results and offer a broader view on AI incorporation in HR. Moreover, in addition to qualitative insights, future research should include quantitative methods like surveys and experimental designs to enhance the study. This combination of methods can offer stronger evidence on how AI affects HR and confirm the qualitative results. Another way is investigation on how AI is being used and its impact on Human Resources in various sectors and organizations of varying sizes. Comparative research on AI adoption in diverse contexts can uncover distinct obstacles and successful strategies in small and medium-sized and large enterprise. Additionally, the investigation of the impact of AI-powered HR strategies on the overall employee experience can be conducted, including aspects like job satisfaction, engagement, and retention. HR managers can create AI applications that are easy to use and promote employee wellness by considering the employee viewpoint. Finally, comparative research across various regions and cultures can demonstrate the impact of contextual elements on the adoption and integration of AI in HR. This type of research can pinpoint strategies and frameworks tailored to specific regions for successful implementation of AI.
In summary, this research enhances the comprehension of how AI is changing HR processes, but further and broader studies are necessary to fully harness its capabilities and tackle the identified problems. By examining these potential areas for research in the future, academics and professionals can help improve AI-driven HR practices to be more efficient, moral, and diverse.
