Research Proposal About Artificial Intelligence Assignment Sample

1. Introduction - Research Proposal About Artificial Intelligence Sample

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.

(Source: Motivational theories, 2024)

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. RESEARCH METHODOLOGY

Research design

Research design refers to the resolving and answering the research issues by using empirical data. There are two significant type of research design that includes qualitative data and quantitative data. Qualitative data refers to gaining information related to beliefs values and perception of the respondent. Quantitative research indicates collecting data in the form of statistics and numbers (Taherdoost, 2022). In the context of determining impact of AI based recruitment on employee’s satisfaction qualitative research will be initiated by the researcher. This method has been selected as it helps in determining why and how a particular respond has been provided by the research. Further, the perception belief of employees could not be recorded in the statistical form that helps in gaining better insight of the research issue. Further inductive approach and interpretivism philosophy will be used that helps in better understanding the perception and opinion of large number of employees. This approach and philosophy will be used as they provide holistic point of view related to research method that helps in understanding new ideas and beliefs. Qualitative data helps in uncovering unexpected findings as it focuses over providing contextualized information. This method helps in determining factors that are contributing towards the particular behaviour and perception of the respondent result in gaining better insight of the collected information.

Data collection method

Data collection method implies for the various types of techniques and procedures that are used for collecting information related to research purpose (Kamper, 2020). There are two distinct method of data collection that includes primary and secondary data collection method. Primary data collection refers to the process in which information is gathered directly from users. Secondary data collection denotes the information which has already collected by some other research for the similar objective. In the context of identifying the impact of artificial intelligence within recruitment on workers motivation both primary and secondary data collection method will be utilized. This method will be used as it helps in providing context specific and rich information related to the research topic.

(Source: Research onion. 2024)

Further, primary data helps in ensuring accuracy and reliability of the data as it gathered data from direct source. In this regard, 30 employees of Amazon will be selected on which survey will be initiated with the help of questionnaires. Along with this, secondary research will also be conducted as it will aid in gaining large amount of information in limited time and cost. This method will help in understanding the perception of various experts and author aids in forming better conclusion. In this context, Google scholar will be utilized that aids in providing access to large number of books and journals. Secondary data will be collected form online journals, research sites, Google public data explorer, reports, publication, government censuses and many more. Along with this, for collecting secondary data, some exclusion and inclusion criteria will be fixed that help in obtaining most accurate data. All the data before 2020 will be ignored which help in collecting most accurate and relevant information.

Sampling strategy

Sampling strategies define as the process of determining the targeted population and identifying the most effective method by which representative samples could be collected. There are two methods of samplings that include probability and non probability sampling method. Probability sampling is also known as random sampling method which refers to selecting respondent in an unsystematic manner. Non- probability method is the sampling method that utilizes non random criteria such as expert knowledge, availability, and geographical proximity for identifying the most suitable respondent for carrying out research (Mulisa, 2022). For determining the impact of artificial intelligences on overall engagement and performance of employees, probability sampling will be utilized by the research. This method helps in selecting more representative respondent that support in understanding diverse views and perception. It also helps in generalizing finding to the population as it allow researcher to predict the level of uncertainty in the outcome. In this context 30 employees of Amazon will be selected by probability method from which questionnaires will be filled out to conduct survey.

Data analysis method

Data analysis refers to the method of applying various logical techniques and statistical tool on the collected data for illustrating, reaccepting and evaluating information. There are two prominent method of data analysis that includes SPSS and thematic data analysis techniques. Statistical package for social science (SPSS) is the software program which is utilised by researcher for analysis of the complex quantitative data (Tamminen and Poucher, 2020). This method includes testing hypotheses and determining cause and effect relationship between the quantitative data. Thematic analysis is the descriptive phenomenological approach that includes the process of determining, evaluating and reporting themes and pattern within the data. For determining the impact on employee’s engagement and motivation level due to AI based recruitment, thematic data analysis method will be used by the researcher. This will be initiated with the help of six step methods that includes familiarizing with the data, developing initial codes, identifying themes, evaluating themes, Defining themes and forming conclusion. The present study is carrying out on qualitative data which could be best analysed with the help of thematic approach. Further, this method aids in forming adequate conclusion by identifying recurring themes and pattern within the qualitative data. This approach also includes utilizing graphs and pie chart for describing the outcome and results of the research process.

Ethical consideration

Ethical consideration refers to the set of principles that guides the research practices and design. It is important for the researcher to must follow standard code of conduct while gathering data from the different respondents (Saliya, 2023). During the collection of data, the respondent must provide freedom to participate or leave the process at any point of time. Further, the researcher must aware the respondent about the aim, advantage as well as risk associate with the study the respondent agree or decline to join the process.

Researcher makes focus on maintain a confidentiality of the participant and keeping their personal information safe by using various digital tools and techniques at the time of conducting the research. To maintain the confidentiality of the data, all signed documents locked in sage file drawer and survey data with password-protected file. In addition, to reduce the chances of biasness and discrimination to get outcome of the study, equal opportunity provided to each individual by using probability method. The researcher emphasize on using correct and original secondary data by taking information from journals, books and articles that are publish after 2020 and it is clearly cited to provide appreciation to the work of original researcher.

Study limitation

Study limitations are theoretical and practical shortcomings of the research that usually remain outside the control of the researcher (Mazhar et al, 2021). There are various types of limitation that affect the efficient as well as successful completion of the study. In the present study, one of research limitation is lack of availability of time and budget. To overcome the problem effectively secondary research has been used by the researcher, it saves time and cost as it not require investment of money and time on different data collection stages. Further, as SPSS requires more time as a result thematic research analysis has been used. It aids in evaluating the information in speedy manner with the help of bar graphs, the easy and fast interpretation save time in effective manner. Moreover, to collect accurate data researcher has been used copyright sites on the other hand, some sites required subscription as a result keywords such as AI and employee motivation used to get greater information rapidly. In addition, for the study, primary research has been used by the researcher to save cost and time correspondingly small sample of 30 respondents taken as per the research issue such as employees of the Amazon.

6. PROJECT MANAGEMENT PLAN

Resources

For successfully managing all the resources of the research a five step process will be followed. At the initial stage, researcher will clearly define the goals which they need to achieve along with the adequate period (Lasisi et al, 2020). Researcher will focus on conducting a capability planning in which an adequate responsibility is assigned to employees that will help in successfully carrying out the research. Along with this, concentration will be paid over forming an accurate budget for each activity after evaluating overall cost of human and physical resources. Lastly, various controlling technique will be used as to ensure that activities are initiated within the allotted time and cost. For effectively managing human resources, adequate compensation and T&D session will be arranged that aids in enhancing workers satisfaction.

Challenges

Lack of effective time and cost are the major issues that impact on overall efficiency of the study. Further, researcher faces issue in selecting most appropriate respondent which creates issue in gaining accurate information. To overcome the issue, researcher has selected random sampling method which increases the scope of gaining highly representative respondents. Moreover, secondary study will also be conducted which help in collecting large amount of information in limited time.

7. 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.

8. LIMITATION OF RESEARCH

The limited amount of time, cost and resources are the major constrains that impact on overall efficiency of the research. Due to limited amount of time, researcher is not able to cover larger number of ecommerce organization for initiating the study. For conquering the issues, researcher has selected Amazon which includes large number of diverse employees that help in effectively gaining in-depth understanding regarding the issue. Also, researcher will be using secondary study which will help in gaining large amount of information related to study. Further, the researcher is unable to utilize effective software due to lack of funds but thematic analysis will be used that support in determining common themes and pattern from the data.

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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