Content uploaded by Jihad Fraij
Author content
All content in this area was uploaded by Jihad Fraij on May 20, 2021
Content may be subject to copyright.
International Journal of Engineering and Management Sciences (IJEMS) Vol. 6. (2021). No. 1
DOI: 10.21791/IJEMS.2021.1.10.
108
A Literature Review: Artificial Intelligence Impact on
the Recruitment Process
J. FRAIJ1, V. LÁSZLÓ2
1University of Debrecen Faculty of Economics and Business, Department of Business Informatics,
jihadfraij@hormail.com
21University of Debrecen Faculty of Economics and Business, Department of Business Informatics,
varallyai.laszlo@econ.unideb.hu
Abstract: This paper aims to review artificial intelligence (AI) implementation in the Human Resources Management
(HRM) recruitment processes. A systematic review was adopted in which academic papers, magazine articles as well
as high rated websites with related fields were checked. This study's findings should contribute to the general
understanding of AI's impact on the HRM recruitment process. It was impossible to track and cover all topics related
to the subject. However, the research methodology seems reasonable and acceptable as it covers a good number of
articles related to the core subject area. The results and findings were almost precise that using AI is advantageous
in the area of recruitment as technology can serve best in this area. Moreover, time, effort, and boring daily tasks are
transformed into computerized, making adequate space for humans to focus on more important subjects related to
boosting performance and development. Acquiring automation and cognitive insights as well as cognitive
engagement in the recruitment process would make it possible for systems to work similarly to the human brain in
terms of data analysis and the ability to build an effective systematic engagement to process the data in an unbiased,
efficient and fast way.
Keywords: Artificial intelligence, recruitment process, Staffing, sourcing of candidates, candidate communication,
human bias.
Introduction
The business world is witnessing rapid changes, with which human resources departments find
themselves standing in front of a new reality. The prediction of the World Economic Forum (Future Jobs
Report 2018) that seventy-five million current jobs will pass from sight by 2022, and one hundred
thirty-three million new jobs will be established, thanks to robotics and artificial intelligence (AI)
(Leopold, Ratcheva and Zahidi, 2018). It has always been the same conflict between humans and
machines. Machines have already changed many jobs and replaced humans in so many tasks. However,
the idea has changed nowadays to establish human-technology cooperation, boosting human abilities
and capabilities. Nowadays, organizations are striving to find talented candidates with multi-skills
qualifications to compete in the global market. This paper aims to offer a deeper understanding of AI's
use in the recruitment process and AI's impact on three main processes: screening, human bias, and the
best-fit candidate.
International Journal of Engineering and Management Sciences (IJEMS) Vol. 6. (2021). No. 1
DOI: 10.21791/IJEMS.2021.1.10.
109
1. Methodology
A systematic Literature review was adopted in this paper. It reviewed the previous studies on AI and
the recruitment process. The researchers adopted a methodology based on {Formatting Citation}. The
methodology process is based on six principles, as shown in Figure (1):
Figure 1. Represents the six principles methodology of (Jesson, Matheson and Lacey, 2011)
Researchers managed the study as follows. At first, two research questions were developed based on
the research interest. A question with two folds was prepared, firstly, which studies have focused on the
impact of AI on the Recruitment process. Secondly, what are the results of those studies taking into
consideration the exclusion and inclusion standards? Afterward, specific keywords were chosen to
select suitable studies. The researchers have used (“Artificial Intelligence”) AND (“Human Resources
Management” OR “Recruitment” OR “Talent Acquisition”). The database that the researchers have used
are Sage, Scopus, Springer link, and Emerald. Besides, grey literature like non-academic reports were
also been studied. The results of the search were presenting a huge number of studies. The third step
was important to minimize the numbers in a scientific way, in which the researchers have limited the
results to specific years and fields. Finally, the results were narrowed to 98 research. After a manual
scan and careful read, it resulted in banning irrelevant studies and articles. This step narrowed the
number of relevant studies to 21 papers that are directly hitting the scope of research.
21 studies were analysed in this research. The date range of these studies was ten years starting from
2010 until 2020 and the results were limited to the field of Business and Management to ignore the
studies that are irrelevant to the aim of this study. It was clear that the studies were increasing during
the last 5 years. The main focus of the recent studies was related to effective screening, human bias and
best candidate fit.
The researchers have chosen websites and journals which had the theme of adapting AI to recruitment
and HR. Moreover, articles were traced to the following domains.
As mentioned below in table1, the following websites were selected:
Websites that have been chosen for this study
www.recruiter.co.u
k
www.marketscreener.
com
www.hrdailyadvisor.blr.com
www.dzone.com
www.hays.co.uk
www.theglobeandmail.
com
www.talentlyft.com
www.bullhorn.co
m
www.forbes.com
www.hrtechnologist.co
m
www.benefitnews.com
www.bloomberg.
com
Mapping the
filed through a
scoping review
Comprehensive
search Quality
assessment Data extraction Synthesis Write-up
International Journal of Engineering and Management Sciences (IJEMS) Vol. 6. (2021). No. 1
DOI: 10.21791/IJEMS.2021.1.10.
110
www.chiefexecutive
.net
www.digitalhrtech.co
m
www.economictimes.indiatime
s.com
www.silo.ai
www3.weforum.org
www.gattacaplc.com
Table 1: This table contains the journals that the researchers have chosen.
The researchers have found different articles with different research methods. In other words, it has
been found that 07 articles used the Secondary Data method. Moreover, 05 articles used the
questionnaire method, and finally, 18 articles used the conceptual method.
2. AI in HRM
AI as a term was firstly mentioned by the father of AI, John McCarthy, in 1956. (McCarthy and Minsky,
1950) described AI as “the science and engineering of making intelligent machines, brilliant computer
programs”. Problem-solving and one data-driven function control and lead the automation of
recruitment by using AI applications in human resources management (HRM) (A, Dimple , Josh Bersin,
Gaurav Lahiri, Jeff Schwartz, 2018).
AI seeks to imitate and enhance human intelligence by comparing natural human intelligence to artificial
intelligence. AI as a science model focuses on alleviating and promoting human physical and mental
labor through computational intelligent behavioral models, the development of reasoning, learning,
computer systems' decision-making, and complex issues that can usually be resolved only by human
professionals. The software in today's recruitment markets uses AI-based solutions to help employers
scan a considerable number of apps for the best possible candidates. In fact, this is one of the most
widely used forms of AI recruitment solutions today. Textkernel and SAP's Resume Matcher are just a
few examples of this kind of software. Textkernel can quickly scan thousands of job applications.
Resume Matcher compares the applicants with the job description and the Wikipedia job entries,
allowing them to rank the applicants according to their job description.
However, the practical use and benefit of AI to support recruitment are contradictory, while on the other
hand, it seems that there is a common ground in terms of its potential. For example, if AI follows human-
based decision-making from the data it scans, so if there have been regularities between recruitment
and selection, AI will continue to emphasize these features and repeat decisions taken in the past. This
is what human decision-making needs to be considered while using AI-based recruitment tools.
(Dessler, 2020). To overcome human error, AI is intended to be designed, but the reality is that an
algorithm is only as good as the data on which it has been trained. In 2020, technology organizations
were likely to be more aware of AI-related bias problems. Therefore, the management of AI bias by in-
house or outsourcing their AI bias problem solving is expected for technology companies. Either way, it
is expected that public and government concern about AI bias will grow so that technology businesses
will need to adjust their AI strategies to remain competitive and compliant. The issue of AI does not
matter how bias will be addressed. Learning from past mistakes, such as Amazon's AI biased recruiting
case, is extremely important for organizations. History could learn to learn from. In order to avoid biases
and perhaps create even better diversity, create the opportunity to seek an answer.
With the help of AI, it is now more proficient for recruiters to approach and attract talents (Nawaz,
2019a). Recruiters can identify talented candidates by implementing AI in their business strategies.
International Journal of Engineering and Management Sciences (IJEMS) Vol. 6. (2021). No. 1
DOI: 10.21791/IJEMS.2021.1.10.
111
Moreover, with the help of AI, recruiters can effortlessly get data on persona and whether it is suitable
for the job applied for or not. Monotonous and repetitive tasks will disappear since AI is accountable for
dealing with these procedures efficiently. In this way, recruiters can focus more on innovative and
strategic issues. AI is intelligently designed to overcome bias during the selection process. Many primary
sources of bias like name, age, gender, race, and belief can, unbiasedly, pass through with the support of
AI systems.
Moreover, (Erickson, 2018) mentioned that 38% of groups have already adopted AI in HRM, while the
rest assumed to adapt it in the near future. Studies showed that one of the main challenges of adopting
AI in organizations HRM is the shortage of skills and the fear of change (Bullhorn, 2018). Based on this
methodology's current facts, this study will discuss how the literature has addressed AI's role in the
recruitment process in HRM.
3. Study Motivation and Objectives
A recent paper, (Nawaz, 2019b) stated that the AI title in the recruitment process lakes literature review
studies. This kind of paper also supports and enriches the holistic view of the literature on the topic.
This paper's purpose is related to researchers' interest to adapt the technological methods to traditional
human resources practices. In particular, the interest has grown because we are experiencing an
increasing phase of the exponential growth of technology. Since the word technology stood out from
both causes, the topic's technological aspect was chosen for AI. AI plays the lead role because it is one of
the issues for trends between different technologies.
This study aims to observe how artificial intelligence is currently used in the recruitment process. The
researchers found out that several articles and published papers, especially on the websites, should be
gathered and collected to make it easier for readers to find a source that contains many resources and
studies related to the use of AI in the recruitment process. Moreover, it was essential to identify the
importance and significance of AI in the recruitment process.
4. Literature Review
Using AI save organizations money and efforts (Vijay Sundaram, 2018); (Jones, 2018), and it could boost
the hard and soft skills of recruiters (Luiza Sayfullina, 2018), improving speed and task efficiency
(Niehueser and Boak, 2020), as well as building relationships between recruiters and candidates
(Othamar Gama Filho, 2018) to result in fining talents unbiasedly (Rebecca Greenfield and Riley Griffin,
2018). Recruiters all over the world have a big challenge to screen the massive number of CV’s and
applications directly after finalizing the attracting process and jump to start the selection process. (Chris
Collins, 2018) reviewed the challenges related to receiving a large number of applicants to be screened
and evaluated in which recruiters sometimes find difficult to tackle. He offered AI solutions to serve the
processing of these applications via chatbots, in which every single applicant can engage personally with
the organization's interactive system. In these interactions, the system can collect information such as,
salary expectations, availability, contact information, skills and experiences. One more challenge was
International Journal of Engineering and Management Sciences (IJEMS) Vol. 6. (2021). No. 1
DOI: 10.21791/IJEMS.2021.1.10.
112
the talent pool of previous temporary workers. He offered a solution to mobilize and activate larger
number of candidates, in which applicants list will connect organizations with new , fresh and up to date
candidates. The third challenge was related to the suitable time and place for communication with
candidates. The solution that was discussed was adopting AI chatbots, in which this technology will be
available all day long in a nonstop action. Three main topics were discussed as categories that will be
tackled screening, human bias and best-fit candidate.
4.1. Screening
(Forbes, June and 2018, no date; Malini Goyal, 2017) (Malini Goyal, 2017); and (Forbes Coaches Council,
2018) discussed the AI adoption to enhance the screening process of HRM. Natural Language Processing
(NLP) is the process in which text is being Transformed into structured and easy to digest data enables
a computer to read language effectively. Moreover, Natural Language Generation (NLG) is the reverse
NLP transformation, letting the computer write a language, structuring data into text. Both of these
technologies have enormous potential in talent acquisition. Therefore, AI could benefit from the
behavior and implications of human beings. However, It is a prerequisite for communicating with
humans to fully understand human beings' written and verbal communication patterns, which is why
AI is needed to incorporate the processing of natural language successfully. Although (Faliagka and
Ramantas, 2012) stated that by analyzing the linguistics used in the text, AI could map the emotional
state of a person, there is a chance that If AI failed to be armed up with reliable algorithms to support
the understanding of humans verbal and written patterns, the decisions would be untrustworthy.
The digital age has brought enormous benefits to EHRM. But it also got massive amounts of data that
are currently primarily handled manually. For example, simple job ads can generate tens of thousands
of responses, many of which may be inappropriate, but all of them need to be screened to find targeted
talents. In terms of implementing AI in the recruitment process, the most positive argument is to save
money and obtain with almost 100 percent accuracy the real-time result. This can mean that the fast-
screening process can benefit both candidates and organizations, allowing HR to understand the
candidate better. The AI would already complete the validation and authentication of criteria before the
final screening process.
4.2. Human Bias
People's bias can influence many aspects like gender, ethnicity, and age. AI can be programmed
primarily to ignore a candidate's background. For example, Google began using an internally based
recruitment tool called qDroid in 2015, which provides interviewers with more reliable questions based
on the position for which the candidate interviews and disregards the applicant's background. Data and
predictive analytics are currently being used to predict the likelihood of success for an applicant in the
International Journal of Engineering and Management Sciences (IJEMS) Vol. 6. (2021). No. 1
DOI: 10.21791/IJEMS.2021.1.10.
113
role he or she is seeking. Based on job-specific criteria and other criteria linked to an organization's
cultural requirements, algorithms calculate each applicant's matching result (Neelie, 2017). Using AI
technologies, the screening process can be handled automatically, and it can fight the bias related to
human behavior (Cara Heilmann, 2018); (Alexandra Levit, 2017). In other words, AI may be
programmed to ignore the background of a candidate. Unconsciously stereotypes sometimes prevent
recruiters from seeing candidates' existing skills, and AI can be useful (Alexandra Levit, 2017). Big
companies have enrolled AI to fight against bias-related issues while recruiting talents. These
companies adopted AI to host digital 'blind auditions,' allowing recruiters to view previous keywords in
a resume to evaluate talent better (Savar, 2017). However, AIs are still only instruments, despite their
extensive problem-solving skills. If a tool is not calibrated correctly, the desired results are not likely to
be produced. This is manifested in the form of AI bias in the context of this discussion. If you feed a
biased AI data, then biased results will be generated. (Gold, 2019).
4.3. Best Fit Candidate
Once the organizations have a list of potential candidates, they can use automation tools to resume
screening, allowing humans to reduce their list. Some tools use keyword analysis to determine the best
applicants based on the content of the CV. Other candidates use various tests and questions to find the
most promising candidates based on actual performance. The two techniques show more accurate and
higher success rates in finding the right person-to-work fit, overall skill-based testing.
This process will involve tackling the source documents' readability scores and other relevant
characteristics, then working the best fit into the system. The main reason employees are not successful
in their job is that they do not have a cultural fit with their employers. AI has the potential to overcome
this problem. Significant companies already use algorithms to match available jobs to the desired
openings on a company's job board. In a LinkedIn job posting, applicants' suitability is assessed by trying
to dig into their profiles and their job history. LinkedIn does this. Knowing that some job descriptions
will be like a model fits, this AI will be more accurate in predicting whether certain participants or
candidates within the workplace fit the job description. The human element, however, will remain a vital
component of the process. (Alistair Cox, 2018).
During the last few years, the remote working culture has attracted attention, and organizations are
always looking to recruit reliable candidates for that objective. Today, Artificial Intelligence tools can
help a lot, mainly if you hire remote employees. It is difficult to believe, but AI can help evaluate the
candidate's honesty and morality to determine whether they are fit for the job. The company can vet
reliable applicants and distribute the workforce accordingly. In fact, for on-demand applications like
Uber, Zomato, and so on, this AI functionality has proven to be a huge benefit (Christopher McFadden,
2019).
International Journal of Engineering and Management Sciences (IJEMS) Vol. 6. (2021). No. 1
DOI: 10.21791/IJEMS.2021.1.10.
114
4.4. AI applications
With the aid of technologies such as the Internet of Things (IoT), big data analysis, cloud computing, and
the newly added AI, the digital world of Industry 4.0 has reshaped recruiting and various other HR
processes. As an application, AI has been defined as Software and/or hardware systems that can think
like human beings and make intelligent decisions based on data (Liu et al., 2018). Organizations are
already using multiple AI-enabled applications such as speech and face recognition as well as problem-
solving, but HRM is in the initial stages of its implementation. AI completely redefines the employer-
applicant relationship. AI tools like Chatbot provide applicants with a new and enhanced employer
experience. The candidate assessment process, scheduling the interview, reference checking, and
sending job offers to the selected candidates can also be automated by other AI-imbued applications.
Only 10% of companies currently use AI in a high context, and 36% of organizations are expected to
make full use of AI in the future (Harver, 2020). Here, the researchers will mention some of the AI
applications that are adopted by big companies.
4.4.1. Fetcher
www.fetcher.ai
Sony Music and over 500 recruiting teams globally use this AI application within the
recruitment process. Fetcher uses the pool of applicant’s details, in which it can analy ze
the data provided and recognize the diversity of each applicant data to suggest the qualified
applicants in seconds.
4.4.2. XOR
www.xor.ai
McDonald’s and IKEA use this AI application. The modern communication trend (Chatbot) is being
performed as well as a full application and screening tools like video interviewing and live chats.
4.4.3. TEXTIO
www.textio.com
The researchers mentioned this application earlier in the body of this paper. Moreover, this AI
application was also adopted by McDonald’s to best deal with human bias-free processes.
4.4.4. ALLYO
www.allyo.com
This application uses interesting user experiences to organizations, in which a full integration can be
made with the organization's HR system. It can boost security and support analytical intelligence to
show talent acquisition. G4S and the Andersons are one of the companies that adopted ALLYO.
International Journal of Engineering and Management Sciences (IJEMS) Vol. 6. (2021). No. 1
DOI: 10.21791/IJEMS.2021.1.10.
115
4.4.5. Talkpush
www.talkpush.com
Amazon and Walmart adopted this application to boost communication with applicants to the next
stage. In other words, it is a CRM supported communication tool for instant, individualized, real-time
conversation using chatbot and video screening techniques.
From the AI as mentioned above applications, it is clear that big companies are using these applications
to stop human bias and save time and effort to find qualified talents. However, all of these applications
support humans in their task as it is not omitting the human part. In other words, it changes the HRM
tasks to become more strategic.
5. Discussion
It was clear from the previously mentioned studies that many researchers agree that the use of AI is
beneficial for organizations. To make it more related to our scope, the use of AI in the recruitment
process can facilitate dealing with a huge number of applicants, in which screening of resume will take
place in a fast and efficient manner (Chris Collins, 2018), (Alistair Cox, 2017), (Cara Heilmann, 2018),
(Paul Attfield, 2018), (Ethan Lee, 2018), (Chiradeep BasuMallick, 2018), (Niehueser and Boak, 2020).
Other researchers agreed that AI will impact positively on reducing the advantage of knowing a
connection or a supporter from within the same organization. At least, if the applicant can’t fit in the
applied position, corruption in hiring will not be an available option. In other words, the system will
definitely not consider any bias attempts (Berta Melder, 2018), (Rebecca Greenfield and Riley Griffin,
2018), (ANZ, 2018), (Savar, 2017), (Alexandra Levit, 2017) (Alistair Cox, 2017).
Also, almost all researchers agreed that AI can boost the process of identifying talents. It is always a
challenge for organizations to attract and to hire talented candidates. Hiring talents is one of the most
important hiring targets. With the help of AI and its implementation, it has made it possible for the
systems and applications to acquire automation and cognitive insights as well as cognitive engagement
in the recruitment process. These technologies would make the system work similar to the human brain
in terms of data analysis and the ability to build an effective systematic engagement to process the data
in an efficient and fast way. With the development of technologies used in the recruitment process, it
has become a target for big organizations to adapt to be competitive in selecting talents from the market
pool.
6. Conclusion
The research was conducted to make it easier for readers to understand the existing published papers
and articles concerning the AI impact on the HR recruitment process. Moreover, this study has
summarized the knowledge regarding AI in the literature. It focuses on the usage and benefits of AI and
its impact on screening, human bias and the best fit candidate recruitment. Moreover, boosting the
quality and the time performed during the recruitment processes. Thus, this study will be a good
reference to the general topic of the AI recruitment relationship. Recruitment processes along with AI
International Journal of Engineering and Management Sciences (IJEMS) Vol. 6. (2021). No. 1
DOI: 10.21791/IJEMS.2021.1.10.
116
benefits were understood in this study such as applicants screening, saving time and efforts, the quality
of the output of hiring, and unbiased selections.
AI software was developed to make computers that think logically and behave like humans. HRM has
witnessed the efficiency and benefits of AI in the recruitment and hiring processes the ability of AI to
adapt to the recruitment has increased rapidly over the last two decades. Recruitment still occurs
through traditional methods but is assisted by AI tools and applications. The system helps automate
different processes, making decision-making more effective and efficient. The use of AI has improved
the hiring process for better quality. Now, HR managers have time to explore HR's bigger picture.
Despite advances in technology, however, a major challenge remains in terms of companies' readiness
for these new technologies, such as the loss of certain administrative jobs.
This study findings are that the impact of AI on the recruitment process is beneficial and it improves the
practices of the human resources departments. This will also improve the performance and the
productivity of any organization as they are selecting the talents from a pool of a huge number of
applicants easily. This study has limitations regarding the accessibility of some published papers, but it
has covered most of the available papers in this field. The researchers recommend future research to
build on the current literature and make a comparison between AI recruitment applications. Also, to
Investigate and differentiate the impact of AI on recruitment in different sectors and geographical
locations.
References
[1] A, Dimple , Josh Bersin, Gaurav Lahiri, Jeff Schwartz, E. V. (2018) A, Dimple , Josh Bersin, Gaurav
Lahiri, Jeff Schwartz, E. V. The rise of the social enterprise. Deloitte Insights, 2018. - Google Search.
Available at:
https://www.google.com/search?q=A%2C+Dimple+%2C+Josh+Bersin%2C+Gaurav+Lahiri%2C
+Jeff+Schwartz%2C+E.+V.+The+rise+of+the+social+enterprise.+Deloitte+Insights%2C+2018.&o
q=A%2C+Dimple+%2C+Josh+Bersin%2C+Gaurav+Lahiri%2C+Jeff+Schwartz%2C+E.+V.+The+ri
se+of+the+ (Accessed: 6 September 2020).
[2] Alexandra Levit (2017) Recruitment in the Age of AI and Automation. Available at:
https://dzone.com/articles/recruitment-in-the-age-of-ai-and-automation (Accessed: 16
September 2020).
[3] Alistair Cox (2017) AI set to revolutionise recruitment . Available at:
https://www.marketscreener.com/quote/stock/HAYS-PLC-4000880/news/Hays-AI-set-to-
revolutionise-recruitment-25005623/ (Accessed: 17 September 2020).
[4] Alistair Cox (2018) AI will be a big part of our future – but what does that mean for businesses
searching for talent? Available at: https://www.hays.co.uk/blog/-/blogs/ai-will-be-a-big-part-of-
our-future-but-what-does-that-mean-for-businesses-searching-for-talent- (Accessed: 19
September 2020).
[5] ANZ (2018) Organisations are turning to Artificial Intelligence to improve their recruitment
processes. Here’s how it can benefit candidates | eFinancialCareers. Available at:
https://news.efinancialcareers.com/hk-en/318729/organisations-turning-artificial-
International Journal of Engineering and Management Sciences (IJEMS) Vol. 6. (2021). No. 1
DOI: 10.21791/IJEMS.2021.1.10.
117
intelligence-improve-recruitment-processes-heres-can-benefit-candidates-sc (Accessed: 17
September 2020).
[6] Berta Melder (2018) The Role of Artificial Intelligence (AI) in Recruitment. Available at:
https://www.talentlyft.com/en/blog/article/207/the-role-of-artificial-intelligence-ai-in-
recruitment (Accessed: 19 September 2020).
[7] Bullhorn (2018) UK recruitment trends report. Available at:
https://www.bullhorn.com/uk/resources/highlightsfrom-the-2018-uk-recruitment-trends-
report.
[8] Cara Heilmann (2018) Council Post: Artificial Intelligence And Recruiting: A Candidate’s
Perspective. Available at:
https://www.forbes.com/sites/forbescoachescouncil/2018/06/22/artificial-intelligence-and-
recruiting-a-candidates-perspective/#19e600257a88 (Accessed: 16 September 2020).
[9] Chiradeep BasuMallick (2018) 3 Ways Artificial Intelligence (AI) will Transform Recruitment | HR
Technologist. Available at: https://www.hrtechnologist.com/articles/recruitment-
onboarding/3-ways-ai-will-transform-recruitment/ (Accessed: 17 September 2020).
[10] Chris Collins (2018) 4 ways AI is solving summer hiring challenges | Employee Benefit News.
Available at: https://www.benefitnews.com/opinion/4-ways-ai-is-solving-summer-hiring-
challenges (Accessed: 16 September 2020).
[11] Christopher McFadden (2019) 7 Amazing Ways Companies Use AI to Recruit Employees. Available
at: https://interestingengineering.com/7-amazing-ways-companies-use-ai-to-recruit-employees
(Accessed: 17 September 2020).
[12] Dessler, G. (2020) Human Resource Management, 16th Edition. Pearson. Available at:
https://www.pearson.com/us/higher-education/program/Dessler-My-Lab-Management-with-
Pearson-e-Text-Access-Card-for-Human-Resource-Management-16th-
Edition/PGM2569070.html (Accessed: 9 January 2021).
[13] Erickson, R. (2018) Infographic: Insights into a highly mature talent acquisition team.
[14] Ethan Lee (2018) The impact of AI on recruitment | AIHR Digital. Available at:
https://www.digitalhrtech.com/impact-ai-recruitment/ (Accessed: 17 September 2020).
[15] Faliagka, E. and Ramantas, K. (2012) ‘Application of Machine Learning Algorithms to an online
Recruitment System’, in ICIW 2012 : The Seventh International Conference on Internet and Web
Applications and Services, pp. 215–220. Available at:
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.885.909&rep=rep1&type=pdf
(Accessed: 9 January 2021).
[16] Forbes, C. H.-, June, U. and 2018, U. (no date) ‘Artificial Intelligence and Recruiting: A Candidate’s
Perspective’.
[17] Forbes Coaches Council (2018) 10 Ways Artificial Intelligence Will Change Your Career -
Catherine’s Career CornerCatherine’s Career Corner. Available at:
https://www.forbes.com/sites/forbescoachescouncil/2018/08/10/10-ways-artificial-
intelligence-will-change-recruitment-practices/#ccf8bf03a2c5 (Accessed: 17 September 2020).
International Journal of Engineering and Management Sciences (IJEMS) Vol. 6. (2021). No. 1
DOI: 10.21791/IJEMS.2021.1.10.
118
[18] Gold, M. (2019) AI for Candidate Screening | Empire Resume, empireresume. Available at:
https://empireresume.com/ai-for-candidate-screening/ (Accessed: 9 January 2021).
[19] Harver (2020) 11 Innovative Uses Of AI In Recruitment In 2020 - Harver, Harver. Available at:
https://harver.com/blog/ai-in-recruitment-2020/ (Accessed: 11 January 2021).
[20] Jesson, J., Matheson, L. and Lacey, F. (2011) Doing your literature review: Traditional and
systematic techniques. Available at:
https://books.google.com/books?hl=en&lr=&id=LUhdBAAAQBAJ&oi=fnd&pg=PP1&dq=Jesson,+
Matheson,+%26+Lacey,+2011&ots=lCdrevKZSh&sig=Q9ececd7_22WZqQIZoaJ5AOjnPQ
(Accessed: 6 September 2020).
[21] Jones, H. (2018) How artificial intelligence can enhance your recruitment process. Available at:
https://www.gattacaplc.com/How-artificial-intelligence-can-enhance-your-recruitment-process
(Accessed: 19 September 2020).
[22] Leopold, A. T., Ratcheva, V. S. and Zahidi, S. (2018) The Future of Jobs Report 2018 Insight Report
Centre for the New Economy and Society. Available at:
http://www3.weforum.org/docs/WEF_Future_of_Jobs_2018.pdf (Accessed: 12 September 2020).
[23] Liu, J. et al. (2018) ‘Artificial intelligence in the 21st century’, IEEE Access, 6, pp. 34403–34421.
doi: 10.1109/ACCESS.2018.2819688.
[24] Luiza Sayfullina (2018) Artificial Intelligence and recruiting: Why soft skills matter for an AI-
recruiter — Silo.AI. Available at: https://silo.ai/why-soft-skills-matter-for-an-ai-recruiter/
(Accessed: 17 September 2020).
[25] Malini Goyal (2017) ‘How artificial intelligence is reshaping recruitment, and what it means for
the future of jobs’, Bennett, Coleman & Company Limited, pp. 1–6. Available at:
https://economictimes.indiatimes.com/jobs/how-artificial-intelligence-is-reshaping-
recruitment-and-what-it-means-for-the-future-of-jobs/articleshow/60985946.cms?from=mdr
(Accessed: 16 September 2020).
[26] McCarthy, J. and Minsky, M. (1950) ‘Inteligencia Artificial’.
[27] Nawaz, N. (2019a) ‘How Far have we come with the study of artificial intelligence for recuritment
process’, International Journal of Scientific and Technology Research, 8(7), pp. 488–493.
[28] Nawaz, N. (2019b) ‘How Far have we come with the study of artificial intelligence for recuritment
process’, International Journal of Scientific and Technology Research, 8(7), pp. 488–493. Available
at:
https://www.academia.edu/download/60659326/How_Far_Have_We_ComeWith_The_Study_Of
_Artificial_Intelligence_For_Recruitment-Process20190920-107927-cdbt20.pdf (Accessed: 6
September 2020).
[29] Neelie (2017) 5 Fascinating Uses of AI in Recruitment. Available at:
https://harver.com/blog/uses-ai-in-recruitment/ (Accessed: 19 September 2020).
[30] Niehueser, W. and Boak, G. (2020) ‘Introducing artificial intelligence into a human resources
function’, Industrial and Commercial Training, 52(2), pp. 121–130. doi: 10.1108/ICT-10-2019-
0097.
International Journal of Engineering and Management Sciences (IJEMS) Vol. 6. (2021). No. 1
DOI: 10.21791/IJEMS.2021.1.10.
119
[31] Othamar Gama Filho (2018) Artificial Intelligence Tech Is Evolving The Recruiting Process.
Available at: https://chiefexecutive.net/artificial-intelligence-tech-evolving-recruiting-process/
(Accessed: 17 September 2020).
[32] Paul Attfield (2018) How artificial intelligence is transforming the recruitment process - The
Globe and Mail. Available at: https://www.theglobeandmail.com/business/article-how-artificial-
intelligence-is-transforming-the-recruitment-process/ (Accessed: 16 September 2020).
[33] Rebecca Greenfield and Riley Griffin (2018) Artificial Intelligence Is Coming for Hiring, and It
Might Not Be That Bad - Bloomberg. Available at:
https://www.bloomberg.com/news/articles/2018-08-08/artificial-intelligence-is-coming-for-
hiring-and-it-might-not-be-that-bad (Accessed: 17 September 2020).
[34] Savar, A. (2017) 3 Ways That A.I. Is Transforming HR and Recruiting. doi:
10.1080/14746689.2017.1407551.
[35] Vijay Sundaram (2018) From Sourcing to Hire: Artificial Intelligence in Recruiting - HR Daily
Advisor. Available at: https://hrdailyadvisor.blr.com/2018/10/02/from-sourcing-to-hire-
artificial-intelligence-in-recruiting/ (Accessed: 17 September 2020).
