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HRM Assignment: Performance Management & Appraisal in AI Hybrid Working Environment


Task: HRM Assignment Topic: Performance Management and Appraisal in an AI hybrid working environment (about 900 to 1000 words) [Minimum 4 citations of scholarly sources]

1. Describe the challenges HRM may face in managing performance in a hybrid human/AI equipped and/or robot working environment.

2. Propose specific actions HRM should take to ensure effective performance measurement under these conditions
Introduction or Background of the Research (about 300 to 370 words) Offer an introduction to your research topic. Offer a brief background of the main problem you are exploring. Include a statement of the purpose of your research. Highlight the key challenges companies which are currently operating in smart industries or planning to become future smart companies may face when implementing robots and/or equipment driven and controlled by Artificially Intelligent (AI) [Minimum 3 citations of scholarly sources]. Please check on introduction, the topic question 1 and 2, analysis of company x (choose a company that is using AI in it's a production) conclusion.

Please remember in your conclusion paragraph, make two or three sentences of recommendation, and don’t increase the word count. Maintain the two with the required words.


As per the research on HRM assignment, it is stated that with the emergence of modern technology, AI is considered as the simulation of human intelligence within machines, which are programmed for thinking like the human along with mimicking their actions. Thus, as opined by Baldeggeret al.,(2020, p. 11), the AI refers to the machines that exhibit the traits that are associated with the human minds such as problem-solving and learning capabilities. Thus, with the evolution of this perfect technology, the top companies around the world are implementing this intelligence that plays the most significant role in solving the enterprise challenges that range from predictive analysis, customer 360, fraud analytics, location analytic, and more. However, Deep and Machine learning is increasingly being leveraged for computer visions, pattern recognition, gesture recognition, robotics, and processing for natural language.

However, there are still certain drawbacks of implementing the AI system within the company operations such as,
• Provability- It is the standard of the mathematical certainty behind the AI prediction and as viewed by Devi (2020, p. 420), it remains to be the grey areas within the organization and no companies can prove the reason behind the system of AI’s decision making to be clear.
• Data security and privacy- Most of the AI applications rely upon the huge data volumes for making an effective decision and the machine learning system feasts on the data for learning and enhancing which makes it much more vulnerable to severe issues like data breaches and theft identification.
• Algorithm biases- The inherent problem with the AI systems is that as per the data are trained on, they can only be good or bad. As stated by Hmoud and Várallyai (2020, p. 751), the bad data are laced with gender, communal, racial, and ethnic biases and if this bias lurking within the algorithm makes the vital decision going unrecognized, then it leads to an unfair and unethical consequences.

Purpose of the study
The present study highly focuses on the implementation of AI within the production of companies like Nike, UK, and the issues faced by them in managing the performance within such AI-equipped working environments. Moreover, the study also determines the actions undertaken by the company to measure its effective performance under this situation.

Topic C- Appraisal and Performance Management within the hybrid AI working environment
1. Challenges faced by the HRM in managing the performance within an AI-equipped working environment.
Though the implementation of the AI leads to advancement and development in the operation of the companies like Nike, UK, however, still there are certain challenges faced by its HRM in managing the performance within theworkplace that is as follows:
• AI Biases
As explained by Ivanovaet al., (2019, p. 246), as the algorithms of AI are built by human beings, these algorithms could have built-in biases through those who have either inadvertently or intentionally introduced them to the algorithm. However, in companies like Nike, UK it was once observed that the algorithms were built with the biases, and the data within the training sets were given for learning from these biases, and the results that this algorithm had produced were also biased. Thus, this reality had resulted in the unintended and unfair consequences for the employees with the discriminatory recruiting algorithm.This affects the operations of the management, especially in Human Resource, Accounting and marketing departments, since they are the departments requiring maximum trainings; the training activity supportsemployee engagement as the company might lose its skilled and knowledgeable workforce, which creates less productivity and low profits for the firm.

• Loss of jobs for AI
It is observed within the company that with the adoption of AI there was the net increase in the job criteria but on the other hand, it was even seen that the same amount of it was created that replaced the ones who have lost jobs, since technology had replaced their positions in the company. This disruptive innovation within the workplace mainly impacts the manufacturing and the logistics departments, since the AI is mostly implemented in these departments predominantly, to reduce the workforce required while ensuing same level of quality of service as well as customer satisfaction.Thus, this led to the changes within the training and education programs, especially for employees handling the demonstrative, wi-fi management and the human resource management offices, above all others, as the workforce is trained to operate the machines and most of them are expelled from their jobs. Thus, this might lead to more production due to the use of machines, but the company cannot use the unique human capabilities and the production gets monotonous without any creativity or innovation.

A shift in human experience

• A shift in human experience
With the adoption of the AI technology within the Nike, UK’s production processes, that is the use of robotics and machinery there was likely an economic consideration. As observed by Kang, and Kang (2016, p. 153), the economic consideration among the individuals happens when the machines take over the responsibilities for which the humans were paid to. Thus, it might create the economic benefits of the increased efficiencies, which are clear upon the profit loss statement of the business, but the overall benefits of the society along with the condition of humans were much more opaque.
• AI accelerates hacking
The AI helps in increasing the speed regarding the things that can be accomplished within many cases, it helps in exceeding the ability as humans to follow along. According to the findings of Dhondseand Singh, (2019), in regards to automation, the nefarious acts like the virus delivery to the software, phishing along with taking advantage of the AI system had increased within companies like Nike, UK, which calls for the breach of their data security and privacy. It was observed that the production equations and innovation of the company were theft and conveyed to other companies with intense hacking.

2. Specific actions taken by the HRM for ensuring the effective measurement of performance
Apart from all the above-mentioned challenges faced by the company Nike, UK, there are certain action taken by the company with using AI in measuring the effective performance within the workplace such are as follows,

• Ongoing real-time feedback
As stated by Njokuet al., (2019, p. 4), the available system within the operations management of the company had been replaced by the ongoing real-time feedback as provided by their intelligently designed algorithms. Thus, the HR specialist now can dedicate their time in coaching rather than that of rating, which puts the basis regarding the different and distinguished workplace. Furthermore, this approach has helped the company on their goal achievement as well as individual development.

• AI-powered performance system
This particular system helps the company Nike, UK to offer certain insights into the employee’s performance and allows the executive and the manager for basing their decision upon their own judgment and knowledge. This powered system also helps in proving the recommendation when it comes to the promotion and the proceedings of increasing employee motivation.

• AI-powered sentimental analysis
As suggested by Saukkonen, et al., (2019 p. 287), a technique powered by the AI technology is called the sentimental analysis which allows the AI algorithm for analysingthe conversations, behaviours along with the overall activities of the employees and the team for understanding their moods as well as satisfaction within the workplace. Thus, such an analysis helps in flagging the possible problems before this occurs and helps in highlighting the problem areas regarding the relationship with the senior management or the tendency towards the rise of conflicts. This helps in building the data based on predictive behavioral patterns, which helps the company to know about the employees exit or whether they want to get promoted and hence, the management works in that way that increases the employee engagement.

• AI-powered communication system
Communication is considered critical for the success of the business, but there were times in the workplace of Nike, UK when it was overlooked. Thus, with the help of AI technology, the company adopted a communication system, which made it easier for identifying the communication needs from the people within the team as it helps in highlighting the changes within the patterns or behaviors within the nature that should not be there. Thus, AI generates teamwork better based on behavioral patterns, similar values and common interests and gradually increases productivity and collaborationof companies like Nike. Eventually, this makes people get engaged within the production process resulting in its increase as well as the success.

Conclusion and Recommendation
The present study focuses on the concept of AI and its implementation within the various operational processes of the company that is Nike, UK and the way the company faces the challenges in adoption of the AI technology. The study shed light on the topic of appraisal and performance management within the hybrid working AI system within a company that mainly targets Nike, UK. It helps in describing the challenges faced by the HRM of the company for managing the performance within its hybrid AI-equipped and robotics working environment that is the AI Biases, Loss of jobs for AI, A shift in human experience along with the ways in which AI accelerates hacking. Furthermore, the study also describes the activities undertaken by the company and its HRM for ensuring the measurement of the effective performance under such a negative condition like Ongoing real-time feedback, AI-powered performance system, AI-powered sentimental analysis along with AI-powered communication system. Lastly, the study incorporates certain recommendations regarding the ways in which the company can improve its AI operations within its overall spheres.

There are certain ways in which the companies like Nike, UK can improve its AI system deployment within the operations of the company such as:
• As suggested by Sheehan (2019, p. 70), the development of the process of internal handoff that helps in the transitions of the algorithm within the initial data science along with the early data work into the project management that will ensure the data quality along with the volume preparations.
• Utilization of the combination of the human’s data evaluation along with the machine learning automation with the data as it is vital for employing the data evaluation for the automation in the form of the machine learning that can be trained by the human experts for assessing the quality of the data.
• As proposed by Van Eschet al., (2019, p. 216), the utilisation of an agile development methodology for machine learning which helps in conducting the project in a manageable sprints which allows the parts of the AI applications to be built, planned and tested iteratively and quickly along with the successful development of machine learning.
• Centralising the data of AI and machine learning, which can be used across the multitudes of projectsrelated to data science, within the enterprise.
• As evidenced by Zehiret al., (2020, p. 266), the utilization of the skilled and knowledgeable project managers will help in enforcing the project methodologies along with the best practices within the operation, so that the company incurs maximum benefits from its AI systems among all the spheres.

Baldegger, R., Caon, M., andSadiku, K. (2020).Correlation between Entrepreneurial Orientation and Implementation of AI in Human Resources Management. Technology innovation management review, 10(4).

Devi, K. U. (2020). The Role Of Artificial Intelligence In The Green HRM Practices. Studies in Indian Place Names, 40(20), 419-424.
Dhondse, A. and Singh, S., 2019. Redefining Cybersecurity with AI and Machine Learning.Asian Journal For Convergence In Technology (AJCT), 5(2).
Hmoud, B. I., andVárallyai, L. (2020). Artificial Intelligence in Human Resources Information Systems: Investigating its Trust and Adoption Determinants. MszakiésMenedzsmentTudományiKözlemények, 5(1), 749-765.
Ivanova, O. E., Ryabinina, E. V., andTyunin, A. I. (2019).Pragmatic Constructivism as a Soft-Methodology of the HRM Concept. International Transaction Journal of Engineering, Management, and Applied Sciences and Technologies, 10(2), 245-253.

Kang, H. K., and Kang, J. A. (2016). How Strategic HRM Practices Affect Corporate Performance-Moderating Effects of Irregular Workers, 23(1), 153-177.

Njoku, E., Ruël, H., Rowlands, H., Evans, L., and Murdoch, M. (2019).An analysis of the contribution of e-HRM to sustaining business performance.HRM assignmentIn HRM 4.0 For Human-Centered Organizations. Emerald Publishing Limited. Saukkonen, J., Kreus, P., Obermayer, N., Ruiz, Ó. R., andHaaranen, M. (2019, October). AI, RPA, ML and Other Emerging Technologies: Anticipating Adoption in the HRM Field. In ECIAIR 2019 European Conference on the Impact of Artificial Intelligence and Robotics (p. 287).Academic Conferences and publishing limited.

Sheehan, C. (2019). HRM and the Service Sector. Contemporary HRM Issues in the 21st Century, Emerald Publishing Limited, 69-80.

Van Esch, P., Black, J. S., andFerolie, J. (2019). Marketing AI recruitment: The next phase in job application and selection. Computers in Human Behavior, 90, 215-222.

Zehir, C., Karaboa, T., andBaar, D. (2020). The Transformation of Human Resource Management and Its Impact on Overall Business Performance: Big Data Analytics and AI Technologies in Strategic HRM. In Digital Business Strategies in Blockchain Ecosystems (pp. 265-279).Springer, Cham.


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