Influence of AI on the Employee Perceptions of Job Security

My research topic is the implementation of Artificial Intelligence (AI) in the workplace and its influence on employee perception of job security. I hypothesize that the implementation of AI in the workplace will negatively influence employee perception of job security. The three articles I have chosen are relevant in that they shed light on the adoption and implementation of Robotics, Artificial Intelligence, and Automation (RAIA) and describe its challenges and fears.

The first article’s topic is the employees’ perception of the implementation of AI on job security, satisfaction, and employability (Bhargava et al., 2020). It predicted that RAIA would negatively impact most roles or jobs in the future. The hypothesis is critical because it backs up my hypothesis, indicating that AI implementation is likely to displace employees. The independent variable is robotics, artificial intelligence, and automation (RAIA) implementation, and the independent variables are job satisfaction, job security, and employability.

The second article’s topic is about the adoption, fears, and challenges of AI tool penetration in business. The authors predict that employees reject AI adoption because they fear job loss despite companies viewing its adoption as advantageous (Schlögl et al., 2019). The hypothesis is critical because it gives a reason for employees rejecting the adoption of AI- because they fear job loss. The independent variable is the penetration of AI in business, and the dependent variables are the perception of adoption, fears, and challenges of employees.

The third article investigates the perception of employees on the introduction of RAIA on work satisfaction and employability in the modern agricultural sector. It hypothesizes that employees perceive a positive relationship between the introduction of RAIA and employability and work satisfaction (Donepudi et al., 2020). It is an interesting prediction because, contrary to other articles, it predicts that AI is not meant to substitute humans but complement them. The independent variable is employees’ perception, while the dependent variables are work satisfaction and employability.

The first article’s researchers conducted semi-structured interviews with participants from different industries such as accounting, economics, hospitality, and consulting. The interviews were conducted face to face, through video and phone calls, and lasted about 35 minutes. The 21 participants that were selected had an organizational tenure of between 20 and 36 (Bhargava et al., 2020). They represented gaming technology, consulting, manufacturing, human resources, information technology, finance, and accounting. Besides, they had worked in various parts of the world such as India, the United Arab Emirates, Oman, the UK, U, and South Africa. The variables were operationalized by incorporating participants from different organizational tenure, industries, and countries. The experimenter manipulated the level of implementation of RAIA as the independent variable. The DV they were interested in are employability, job satisfaction, and job security. The findings were that RAIA is not likely to replace human touch and skills and that employees should see RAIA as an opportunity rather than a threat; hence, they were inconsistent with the predictions (Bhargava et al., 2020).

For the second article, a total of 19 participants were selected via social media (Schlögl et al., 2019). The method involved interviewing them through semi-structured interviews that lasted about 45 minutes (Schlögl et al., 2019). The results were recorded, transcribed, and analyzed using Mayring’s qualitative analysis and MaxQDA software. The part of the procedure where the variables were operationalized is when they were analyzed using the MaxQDA and Mayring’s analysis method. The experimenters manipulated the penetration of AI tools in the business to measure the DV of the adoption rate, challenges, and employees’ fears. There were no other essential variables measured. The authors found that while employers recognize the importance of AI in automation and increased efficiency, employees reject it because of fear of losing their jobs. This was consistent with the predictions.

The third article employed structured interviews with 50 participants who engaged through WhatsApp video calls and face-to-face and lasted for about 25 minutes (Donepudi et al., 2020). The dependent variables that the researchers were interested in are work satisfaction and employability. They found out that employability is not affected by the introduction of RAIA in the agricultural sector. Also, employees are satisfied with their jobs and the incorporation of RAIA as it complements their efforts, which was consistent with the hypothesis.

For the first article, job satisfaction and security would have been operationalized using measures that predict how employees feel, such as job security. It would have been operationalized by letting employees rate their security on a scale. That way, it would have been easier to interpret how they view their job security with the introduction of RAIA. Besides, the prediction that RAIA will have an impact on most roles as the researchers predicted is not satisfying. Perhaps they could have added how it will impact the roles, positively or negatively.

The second article hypothesized that employees reject the adoption of AI because they fear job loss (Schlögl et al., 2019). While it seems to be a logical prediction, it is not because employees cannot reject AI adoption because they fear losing jobs. If companies or employers find the automation and increased efficiency through AI, then employees cannot stop them from adopting AI. Employees have to adhere to the adoption because companies look for ways to cut costs and improve efficiency, which is what AI is offering.

Lastly, I find the last research very interesting. The authors take different perspectives from other researchers that RAIA is likely to improve employability and job satisfaction on the grounds that it will increase opportunities. Besides, the prediction that it is will complement human ability rather than replace it is powerful. This sheds light on the positive side of RAIA despite other researchers seeing it as a threat to job security. One of its recommendations is that the gap between the profession and RAIA should be bridged through employees gaining new competencies and skills to effectively handle the RAIA technology (Donepudi et al., 2020).

The three articles combined to inform my thinking about my proposal through incorporating job satisfaction and employability. Satisfaction and employability reflect the perception of employees. For example, when they are satisfied with AI adoption, it means they do not worry about losing their jobs. The articles also combine to show that AI adoption can positively or negatively influence employees’ perception depending on whether they perceive it as a threat or an opportunity.

For my research proposal, I plan to investigate how implementation of AI in the workplace influences employees’ perception of job security. The independent variable will be AI implementation in the workplace, and the dependent variable will be employee perception of job security. AI implementation conceptual definition is the adoption of robotics and automation machines that will complement human ability. This variable will be measured by dividing the human resources department participants into two. One group will use AI tools to perform employee appraisals, while the other group will use traditional tools. Employee perception of job security refers to the views and predictions of employees on losing or retaining their jobs after a company adopts the AI tools. It will be measured self-reporting Job Security Index (JSI). The central hypothesis is that the implementation of AI in the workplace will negatively influence employee perception of job security.

References

Bhargava, A., Bester, M., & Bolton, L. (2020). Employees’ perceptions of the implementation of robotics, artificial intelligence, and automation (RAIA) on job satisfaction, job security, and employability. Journal of Technology in Behavioral Science, 6(1), 106-113. https://doi.org/10.1007/s41347-020-00153-8

Donepudi, P. K., Ahmed, A. A., Hossain, M. A., & Maria, P. (2020). Perceptions of RAIA Introduction by Employees on Employability and Work Satisfaction in the Modern Agriculture Sector. International Journal of Modern Agriculture, 9(4), 486-497.

Schlögl, S., Postulka, C., Bernsteiner, R., & Ploder, C. (2019). Artificial intelligence tool penetration in business: Adoption, challenges, and fears. Communications in Computer and Information Science, 259-270. https://doi.org/10.1007/978-3-030-21451-7_22