Research Proposal About Artificial Intelligence Assignment Sample

1. Introduction - Research Proposal About Artificial Intelligence Assignment 

Background

Artificial intelligence implies for the large number of technologies and tools that help computers to perform diverse and complex functions like human being. This technology was developed in year 1951 with the aim of evolving and making machines capable to work and think like human beings. The technology has been introduced in each aspect of the business entity with the aim of enhancing overall efficiency of the organization. AI based recruitment implies for the process of using machine algorithms for carrying out the process of identifying, influencing, selecting and on boarding employees within organization. Amazon was founded by Jeff Bezos on 5 July 1994 as the online marketplace for selling books. Gradually, firm started providing the wide ranges of product categories and currently Amazon has become leading ecommerce organization across the world. The organizations have a market share of 37.8% and earn annual revenue of 574.8 billion pound in year 2023 (Description of Amazon, 2024). Headquarter of organization is situated at Seattle, Washington and company has hired more than 1525000 employees. Employee’s satisfaction refers to the level of contentment a worker felt related to their job. The current proposal is based on determining the influence of AI based recruitment on morale and satisfaction of employee’s within Amazon.

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Research problem

Present study is concentrated on examining the influence of AI based recruitment on employee’s satisfaction within Amazon. In the current time, AI plays a crucial role in taking decision regarding employees which impact on overall productivity of the business entity. This creates a necessity for organization to identifying influence of AI recruitment on employee’s satisfaction level (Fahim, Kalinaki and Shafik, 2024). Thematic analysis will be used to shed light on the impact of AI based recruitment on satisfaction level of worker within Amazon.

Relevance of study

The current study is highly relevant as recruitment is the pivotal process which impact on overall functioning and productivity of the business entity (Sumanth et al, 2024). With the introduction of AI, there are various chances in the decision making process within recruitment which impact on overall satisfaction level of the employees.

Structure

Below is the brief description of the proposal structure:

• Introduction: The research problem, aims and objective of the study will be described in this section.
• Literature review: This section includes critical evaluation of past study and research.
• Research methodology: it will discuss on data collection method, Research design, sampling strategies that is used for initiating study (Zha et al, 2023).
• Project management plan: The required resources and timeframe will be discussed in this section of report.
• Research outcome and significance and limitation: Importance, challenges and findings of the study will be disclosed in this section.
• Conclusion: It includes summarizing pivotal point of study and providing recommendations.

2. RESEARCH PROBLEM

• Q1. What is the use of AI within different level of recruitment process?
• Q2. What are the various advantages and disadvantages of introducing AI within UK’s e-commerce sector?
• Q3. How AI based recruitment facilitates satisfaction and motivation level of employees within Amazon?

3. AIMS AND OBJECTIVE

Aims:

The aim behind initiating current study is to examine the role of AI in enhancing recruitment strategies within Amazon.

Objective:

• To determine the level of recruitment based on AI.
• To examine various benefits and limitation of integrating AI in recruitment process
• To determine impact on employee’s satisfaction by introducing AI in recruitment process
• To suggest competent strategies to Amazon’s manager for effectively integrating AI in Recruitment.

4. LITERATURE REVIEW

Introduction

This section will provide critical evaluation of the past studies related to the topic which aids in better understanding the research problem. The current section will describe the role of AI at each stages of recruitment process along with their advantages and disadvantages. It will also present the influence of AI based recruitment on overall motivation and satisfaction level of employees.

Various level of recruitment based on artificial intelligences

According to the view point of Balasubramanian (2021) it has been identified that AI has introduced at each level of recruitment process which aids in enhancing overall efficiency of the selection strategies. AI is involved towards identifying the actual need in the organization after analysing the available human resources. This helps in providing accurate data which results in reducing scope of under and overstaffing within the organization. Boggs et al, (2023) stated that AI also aids in forming the job description after critically evaluating the actual skills and competencies that required within employees. AI helps in streamlining the sourcing process as this technology is involved towards scanning social profile and online resumes of the candidates that help in finding diverse and talented employees. Further, AI is also involved towards resumes of past employees which had applied within organization results in identifying most capable and talent workforce within the organization. Moreover Liang et al, (2024) investigated that AI screening software support in automating resume screening without any biasness that helps in improving overall quality of hiring. Under this, technology is used to provide position to each candidate based on their qualification which aids in taking effective selection decision.

Additionally, Yanamala (2021) explicated that AI could be used for taking interview which helps in decreasing overall human effort and support in selecting most optimum worker within the business entity. In this context, Amazon is using AI for taking initial test and interviews which ensures reduction of employee’s burden and support in selecting employees without any discrimination and biasness. Hunkenschroer and Luetge (2022) claimed that AI assists in forming the most accurate employment contract which covers all the required information. This helps in reducing the scope of human error and supports in covering all the required information iwthin the contract. Lastly, Saad et al, (2021) stated that AI also plays a crucial role in conducting induction training for the employees. After evaluating the historical induction process, AI provides suggestion to manager regarding strategies that should be introduced leading to enhancing workers understanding related to their roles.

Benefits and limitation of AI based recruitment

Based on the view point of Black and van Esch (2020), it has been determined that AI based recruitment help in acquiring highly talented and quality employees that aids in enhancing overall productivity of the business entity. AI support in creating descriptive and clear job description which aids in attracting right candidates at the job. Further, use of NLP helps in screening hundred of CVs at the particular time period and easily comparing skills of various employees which aids in sleeting and hiring most optimum employees. On the contrary point of view, Yanamala (2022) describes that AI in recruiting result in depersonalization which leads to rise in risk of developing isolating feeling within candidate. AI does not consider the unique skill and experiences of candidates while undertaking recruitment process which may leads to losing most competent and quality employees of the organization.

Moreover, Blumen and Cepellos (2023) explicated that integrating AI in recruitment process contributes in decreasing the human biasness and discrimination results in hiring most qualified and effective workers. Recruiter may be nailed due to any personal and demographic factors which results into hiring inappropriate candidates within the organization. AI select employees based on ethic skills and qualities and did not consider any other factor which helps in selecting the most adequate employee. However, Ore and Sposato, (2022) stated that data used to train AI include biasness than the technology may discriminate within employees that result into selection of employees in an unethical manner. In this context, Amazon has provided data because of which AI has learned gender Biasness and takes ineffective recruitment decision (AI Recruitment in Amazon, 2023). The resume which contains women was automatically provided downgraded as the data taught AI those male candidates are more effective and qualified.

Gusain et al, (2023) defined that AI helps in ensuring that no candidate has been overlooked that help in selecting most accurate employees within the business entity. AI does not evaluate individual’s skill based on certain keywords rather focus on analysing whole document as to identifying the most competent candidate. Johnson, Stone and Lukaszewski (2020) analysed that introduction of AI also create various legal issues for the business entity that results in negatively impacting on overall reputation and goodwill of the organization. It is difficult for the organization to effectively compile with the equal employment opportunity commission that leads to creating large number of legal obligation on the business entity.

Influence of AI based recruitment on employee’s satisfaction level

According to the view point of Vardarlier and Zafer (2020) it has been identified that AI based recruitment support in seamlessly initiating selection process which result in reducing frustration and anger of the employees. It has identified that AI based recruitment support in shorten the hiring process by 30% which help in enhancing overall satisfaction and motivation of the workers. From the critical view point, Mashayekhi et al, (2024) explicated that AI does not provide the human touch and connection which is required for influencing and attracting employees. Candidates generally appreciated the opportunity provided to understanding organization’ culture, interact with recruiter and ask question. But the introduction AI creates issues in generating connection within the firm that results in reducing employee’s motivation level. Raveendra, Satish and Singh (2020) explicated that AI based recruitment process unable to align with the Vroom expectancy theory that results in reducing overall satisfaction level of the workers. The theory stated that employee’s perception is highly influenced by their future expectation (Vroom expectancy theory, 2024). In effective human touch resist employees in determining the organization’s belief, culture and values which reduces overall workers satisfaction.

Fernández-Martínez and Fernández (2020) confessed that integrating AI in the recruitment process help in deciding compensation strategies based on the historical and market trends results in enhancing overall employee’s satisfaction. With the AI based recruitment, an organization is able to effectively align activity with Adam equity theory results in boosting employee satisfaction. AI technology is involved towards evaluating the market trend and historical data based on which the most accurate salary and compensation is decided for the employees. This help in offering justifiable and effective compensation and reward to worker that result in improving overall motivation level. Bhargava, Bester and Bolton (2021) stated AI based recruitment does not always take adequate decision rather it includes data based biasness that impact on overall satisfaction and motivation level of employees. Company may provide bias training to AI based on which inaccurate recruitment decision are taken that influences overall motivation and satisfaction level of workers.

Critical evaluation

Prior studies have been conducted to determine the use of AI in enhancing overall recruitment process of the business entity. The study was aiming at determining AI‘s positive influence of productivity and profitability of the business entity (Prentice, Dominique Lopes and Wang, 2020). However, emphasis was not paid on identifying influence of using AI based recruitment on overall satisfaction level of workers. This study provides information regarding various benefits and limitation associated with AI based recruitment on employees overall motivation.

Conclusion

It has been identified that AI in recruitment helps in determining actual employ need, support in creating job description, aids in resume screening and selection process. This technology support in faster recruitment, reduces hiring cost, quality hiring, decreases human biases that result in adequately selecting employees. However, data based biases, data privacy, lack of human toucan and depersonalization are issue that impact on employee’s satisfaction.

5. EXPECTED OUTCOME AND SIGNIFICANCES

Findings

From the above study, it has identified that AI integration in recruitment process support selecting most accurate and competent employees within the business entity. With the help of technology, company is able to determine the exact number of employees that should be hired within firm (Yanamala, 2020). It also helps in automating the process of resume scanning and sourcing employees that result in selecting most optimum human resources. AI integration helps in reducing human biases, reduces scope of overlook candidates and reduces hiring cost. However, it has identified that due to lack of human touch, depersonalised and data based biasness employee’s motivation is negatively impacted.

Significance

Current study will help in creating awareness regarding the manner in which AI should be used at each stages of the recruitment process. The outcome of the study support in enhancing overall understanding and knowledge of manager relates to various benefits and limitations of AI integration (Nazareno and Schiff, 2021). Along with this, other organization of the ecommerce industry will be aware of potential impact of AI based recruitment on employee’s satisfaction. This guides them to take effective actions on time so that negative impact could be reduced.

Contribution

The current research support in determining multiple impact of AI based recruitment on the satisfaction level of the employees. Further, it will also help in identifying that role of artificial intelligences in increasing efficiency of recruitment process and gaining most competent employees (Nguyen and Malik, 2022). Prior, focus was only paid on determining significance of AI form the firm’s point of view and no concern was paid towards employee’s gratification. This study guide manager related to strategies by which overall AI could be used for enhancing workers’ satisfaction.

CONCLUSION

By summing up the report, it has been concluded that introduction of AI within recruitment process has helped in selecting the most competent employees. It has been determined that artificial intelligences help in determining the exact need of workers and support in creating effective job description. AI integration support in aligning with Adam’ equity theory that result in enhancing overall employee’s satisfaction. Initiating recruitment with the help of AI help in streamlining operation reduces human biases and provides effective experiences to candidates. On the other hand, this technology also lack human touch and include data based biases which result in negatively impacting on employee’s satisfaction. For initiating study, qualitative search will be initiated through which both primary and secondary data are gathered. In this context 30 employees of Amazon will be surveyed and various books and journals will be evaluated. Lack of time and resources are crucial issue faced while initiating the current study.

REFERENCES

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