Journal of Engineering and Technology Management 76 (2025)

The Role of Artificial Intelligence in Transforming Recruitment Process

Author- Saloni Natu
Co-author- Dr Neha Choudhary
Amity Business School, Amity University School

Abstract-

Today, we can notice a wide and rapid changes which makes the present world much more
advanced in terms of Artificial Intelligence immersing changes towards traditional methods
of recruitment in terms of more efficiency, accuracy and making overall decisions. Through
this study we will analyse about how AI-driven mechanisms like natural language processing
and predictive analysis influence evaluation of a candidate, talent acquisition and selection of
appropriate employees. Continuous innovative automation is taken place by AI preferably
with automated screening of resumes, matching of appropriate candidates and minimizing the
amount of biasness while making a hiring decision. Other than that, AI contributes towards
more advancement with the help of chatbots and virtual assistants to make the candidates
experience with more engagement and interaction.

Keywords- Natural Language Processing (NLP), Predictive Analytics, Hiring Decision-

Making, Chatbots, Recruitment Process

Introduction-

With the range of increased competitiveness in the markets, organisations are looking
forward to enhance and improve their hiring process and bring about new and innovative
talents. Traditional method of hiring contains a lot of work process in a manual way which
takes time and efforts when it comes to screening , possible biasness which can obstruct one’s
efficiency and fairness while hiring candidates. It seems promising upon using AI for the
hiring process for the future purposes like letting them focus on the costs and focus on hiring.
The new technologies like the Machine Learning, Natural Language processing, Predictive
Analysis etc. brings out more of accuracy of the hiring talents.

In many aspects, AI tools are used for the recruiting process from screening the resumes till
matching of the appropriate candidate. The system formulates the huge set of applicant’s data
to identify the best candidate suitable for the job which minimizes time and efforts for human

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recruiters who repetitively have to acknowledge the same data. AI powered systems like
chatbots and virtual interviews ensures easy flow of communication between the recruiters
and the candidates which includes query session, responses, scheduling etc. It helps
organisations to perform tasks in a more efficient manner with suitable objectives which
results in abetter hiring process.

Objectives-

1. To explore the influence of AI on recruitment process- Examining the mechanism of

AI driven algorithm tools can increase the overall efficiency and speed accuracy of
hiring process.
2. To access AI applications during the screening of candidates and selection process- It
looks upon the automation of when it comes to screening of the resumes, predictive
hiring decisions and shortlisting.
3. To analyse the involvement of AI in terms of engagement with chatbots and virtual
interviews- Looking upon the the ways AI improves communication, improves
candidates experience and improve their mechanism in conducting virtual interviews.
4. Identifying possible biasness and issues connected to ethical standards that might take
place- More of like examining the concern related to AI algorithm with data privacy
and violating fairness treatment.
5. To estimate the challenges and hindrance caused by AI- Focusing on retrieving
investigation on potential risks that AI is likely to create, assessing on the risk of job
replacement and increased potential on mechanisms and automation rater than any
human interactions.
6. To examine the function of improving the workforce diversity and involvement- To
asses whether AI can exclude biasness and discrimination while hiring and broaden
the pool of talent.

Review of Literature

We can refer recruitment as a process where it can portray new efficiency and techniques of
the new technologies by eliminating repetitive tasks and to make better decisions. Many of
the studies reveal that AI-powered tools like applicant tracking system or the mechanism of
chatbots to help in the screening of candidates by carefully analysing and accessing their

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qualifications along with their resumes according to the job requirements (Upadhyay &
Khandelwal, 2018). The algorithm of AI helps to terminate biasness by proceeding with data
evaluation than personal judgements. Algorithms of AI reduce biasness and unfair practices
(Raghavan et al., 2020). It is beneficial predictive analysis , as a result helping recruiters to
decide hiring entitled candidate based on the previous performance.

There is another important aspect of AI in the recruitment process which is about improving
candidates experience and engagement. AI mechanised chatbots present quick feedbacks for
individuals seeking jobs, focusing on improving communication and reducing on application
drop-off rates (Woods, 2021). Additionally Natural Language Processing allows AI
mechanisms to analyse the applicant’s responses throughout the video interviews by
determining patterns of speech as well as the view for the particular position with the best fit.

Research Methodology

Research Design-

To understand and make an approach towards intense understanding about how AI can be
adopted in the recruitment process, this research acquires mixed-methods for research design
that combines both the data from qualitative as well as quantitative collection of data. This
research design would be descriptive to analyse the existing insights about the hiring process
from the perspective of recruiters and job seekers. The research will use primary and
secondary data to increase reliability and validity.

3.2 Data collection methods

a) Primary Data: Semi-structured interviews would be collected with HR manager and

business owners/leaders to obtain qualitative information on how AI algorithms are
implemented in their organization and efficiency of better automation and making it
easier for the recruitment process for the hiring managers. Surveys will be taken from
the employees to rationale their opinion upon performance based pay at work.
b) Secondary Data: Different types of literature were reviewed, which include journal
articles, books and some case studies to visualize the context and support the
theoretical arguments.

Here are some of the interview evaluation conducted with an HR of the company of USB
financial cooperation’s. The questions were asked related to idea of implementation of AI
algorithm in their organisation and for what purpose and process of recruitment it would

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be applicable from the vision of present and future needs. The positive aspects of
implementing as well as for not implementing the algorithm will be asked to get a better
idea about if its fit for the overall process of hiring of candidates in USB Financial co-
perations .

In the current competitive job market, businesses like USB Financial Corporation Ltd are
leveraging Artificial Intelligence (AI) to optimize their hiring processes. AI has
transformed recruitment by improving efficiency, enhancing accuracy, and promoting
fairness. This document outlines how AI facilitates candidate screening and shortlisting,
enhances the quality of hires, and streamlines recruitment by reducing costs and
automating repetitive tasks.

1. How does AI help in screening and shortlisting candidates more effectively?

Response- AI-powered recruitment solutions at USB Financial Corporation Ltd enable

efficient candidate evaluation by analyzing resumes, processing job applications, and aligning
applicants with role-specific requirements. Through the use of Natural Language Processing
(NLP) and Machine Learning (ML), AI can rapidly assess thousands of applications,
significantly reducing manual workload for HR teams. These AI systems evaluate candidates
based on their skills, experience, and qualifications in relation to predefined job descriptions.
They rank applicants according to suitability, ensuring that only the most relevant candidates
proceed to the next stage. Furthermore, AI can identify trends in candidate data, predict future
job performance, and highlight any potential concerns that traditional screening methods
might miss.

Example: When recruiting for a Loan Officer position, AI scans numerous applications to
identify candidates with financial services experience, credit assessment expertise, and loan
processing knowledge. Similar AI-driven hiring processes are used by leading banks like
JPMorgan Chase, which implemented AI to streamline resume screening, reducing hiring
time by 75%.

2. Do you think AI improves the quality of hires compared to traditional

methods? Why or why not?
Response- AI-driven hiring improves the selection of top talent through:
1. Data-Backed Decision Making: AI removes human bias by assessing
candidates solely on merit and data analysis.

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2. Predictive Analytics: Historical data insights help predict candidate success

and improve retention rates.
3. Competency-Based Evaluation: AI assesses cognitive abilities, personality
traits, and problem-solving skills for a comprehensive hiring approach.
Standardized Assessments: AI applies consistent evaluation criteria across
applicants, ensuring fairness and accuracy.

Example: AI can analyse past successful hires in USB Financial Corporation Ltd’s
Microfinance division, identifying key factors that contribute to high performance,
such as experience in rural banking and customer relations. Similarly, Unilever has
adopted AI-driven video interviews that analyse candidates facial expressions and
word choices to assess potential hires, resulting in improved job performance and
lower attrition rates.
3. How do AI-driven assessments ensure fair and unbiased hiring?

Response- One of the biggest challenges in recruitment is unconscious bias, which AI

mitigates by:

 Objective Candidate Assessment: AI evaluates skills and experience, disregarding

personal characteristics like age, gender, or ethnicity.

 Anonymous Resume Screening: AI can remove identifying details from

applications, ensuring merit-based selection.

 Continuous Learning Algorithms: AI models can adjust to detect and correct bias
over time.

 Broader Talent Reach: AI expands recruitment channels to attract diverse

candidates.

o Example: If an AI system detects a pattern where only male candidates are

shortlisted for sales positions, it can alert recruiters and refine its selection
process to ensure all qualified candidates receive fair consideration. Global
corporations like IBM have incorporated AI to ensure diverse hiring by
implementing bias-detection algorithms that actively promote inclusivity in
recruitment.

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4. Has AI reduced the time and cost involved in the recruitment process? If so,
how?
 Response- AI significantly reduces the time and expense associated with recruitment
through:

 Expedited Resume Analysis: AI processes thousands of resumes in minutes, cutting

down the hiring cycle.

 Automated Interview Scheduling: AI tools coordinate interviews without human

intervention.

 Cost Savings: AI reduces the need for large HR teams, lowering operational
expenses.

 Improved Return on Investment (ROI): Higher-quality hires minimize turnover

and training costs.

Example: If USB Financial Corporation Ltd seeks field agents for its Microfinance division,
AI can quickly filter candidates based on location, previous loan collection experience, and
language proficiency, allowing HR to focus on the most qualified applicants. Major firms like
Amazon use AI to reduce hiring time, particularly for seasonal employees, automating
scheduling and workforce allocation, leading to significant cost savings.

5. How does AI help in reducing repetitive tasks for recruiters?

Response- Recruiters benefit from AI-driven automation, which optimizes various HR

functions, including:

 Resume Screening and Matching: AI extracts relevant details and aligns them with
job descriptions.

 Chatbots for Candidate Communication: AI-powered chatbots handle FAQs and

application updates.

 AI-Based Pre-Screening Interviews: AI video platforms analyze candidate

responses before human review.

 Personalized Feedback Automation: AI generates tailored feedback for candidates,

enhancing the applicant experience.

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 Streamlined Employee Onboarding: AI assists new hires with documentation,

training, and compliance procedures.

Example: AI chatbots can respond instantly to common candidate inquiries regarding

job openings, salaries, and application status, reducing HR workload. Companies like
Hilton Hotels have implemented AI chatbots for recruitment, improving candidate
engagement and freeing up HR personnel for more strategic tasks.

USB Financial Corporation Ltd benefits from AI-enhanced recruitment by increasing

efficiency, improving hire quality, promoting fair hiring practices, and reducing recruitment
costs. By automating repetitive HR tasks, AI allows recruiters to focus on strategic decision-
making and improving candidate engagement. As AI technology continues to evolve, its role
in transforming the hiring landscape will only expand, making it an essential tool for
attracting and retaining top talent in a dynamic job market.

I participated in a primary research and performed a poll of individuals from various

backgrounds. A questionnaire was used to conduct this research which looks into the
purpose of AI in the recruitment process is being visualized by individuals from different
firms and position. It will help us to explore the cons and pros of imitating AI in the
hiring process. The data below comprises of individuals with an age group of 18-46 and
above and are located in different organizations. The data collected below is from a total
of 200 respondents . The survey was completely voluntary and the responses for the
questionaries were collected through Google Forms.

Exibit 1:- Are you familiar with the use of Artificial Intelligence (AI) in
recruitment?

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As we can look through the chart, we can figure out 94.5% individuals are familiar and aware
about some knowledge of AI in the process of recruitment. Yet, about 8% have extensive
knowledge and the rest of 4% are unaware of the concept. Since most of the individuals have
some knowledge, organizations might need to implement programs for upskilling their
knowledge and appropriate training for the HR professionals and recruiters to use the AI
mechanisms at their best.

Exibit 2:- Has your organization implemented AI in any stage of the recruitment
process?

As we can see, the organizations of the responded individuals haven’t yet proposed with AI
mechanisms in process of recruitment and indicates that its still in the progress of its early
stage in this particular field. About 30% of the organizations have implemented the
mechanism of AI in limited aspects that is to be tested it for further tests or is being used for
the functioning of tasks like screening of resumes or scheduling the interviews.

66% of the organizations haven’t implemented the idea but are considering it and are still
exploring or are still left to explore and the remaining 12% are not planning to implement at
all maybe due to lack of resources, doubt their effectiveness or are still comfortable and
reliant with the traditional methods.

Exibit 3:- Which AI-powered tools does your organization use for recruitment?

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With the result many of the 64.5% organisation use chatbots to engage with their candidates.
AI is used here commonly for answering the queries of the candidates, initial screening and to
improve communication. 61.5% use AI driven video interviews to initiate trust I the ability of
AI to evaluate a candidates expressions, tone and non verbal communication. Significantly
40.5% use predictive analysis to make hiring decisions, suggesting a change towards AI in
decision making. 31.5% of the organisations use AI driven resume screening specifying AI is
helping streamline candidate shortlisting. 0.5% of the respondents use less commonly AI
powered job making and don’t use AI at all.

Exibit 4:- In your opinion, what are the main benefits of using AI in recruitment?

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61% of the respondents recognize improved candidate experience as a benefit making them
believe AI smoothens and personalizes the process of hiring, making it easy for the
applicants. 57 % believe that AI reduces human biasness supporting the argument that AI
driven mechanisms can encourage fairness and discouraging biasness . About 46.5% look
upon AI as a cost saving tool indicating automation reduces the manual workload, expenses
of administration and time consumption on repetitive tasks. 26.5% support better hiring
decisions by holding onto the access of candidates more precisely. 31% spot faster screening
and shortlisting and the rest of the 0.5% believe AI have no significance.

Exibit 5:- Do you believe AI will become more dominant in recruitment over the next 5-10
years?

Majority of 80.5% of respondents still believe that human involvement is necessary and
crucial in the recruitment process. It specifies that even if AI can improve efficiency yet
human interaction is indeed required to oversight over hiring decisions and 16% represents
that AI adoption will remain limited due to ethical concerns, unconscious biasness and trust
issues.

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Exibit 6:- Would you feel comfortable if an AI system made hiring decisions without human
intervention?

None of the respondents completely trust AI intervention upon entirely making decisions in
hiring process even if its efficient and unbiased. 65.5% believe human interaction is needed
in the hiring process. They support idea that AI should be used as a decision-support tool
rather than a decision-maker. 28.% of the respondents are open towards to the hiring
decisions but it still depends on the type of industry and roles somewhere likely in technical
and repetitive job screenings and the rest are comfortable with AI recruitment process if its
accurate and unbiased.

Exibit 7:- What improvements would you like to see in AI-driven recruitment? ( Individual
responses)

1. Improve evaluating communication. It should be innovated in a way where it

wouldn't affect the ethical standards and discontinue biasness.
2. Should focus more on the talent and job position requirements while hiring and not
through past biasness. It must be customized according to different roles and
industries
3. Enhanced verification tools to cross-check candidates resumes. More bias-free
candidate evaluations and personalized job matching and detect fake credentials,
forged documents
4. AI chatbots and automated systems should provide more personalized and engaging
interactions rather than feeling robotic. I would suggest towards the biasness
issue...as it may reduce it and upcome with fairness and better results

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5. It should support recruiters not replace. It should be more accurate and should
match the job and candidate algorithms.
6. AI-driven recruitment has the potential to revolutionize hiring by increasing
efficiency, reducing human bias, and improving candidate experience. However to
unlock its full potential it is crucial to address challenges like bias lack of
transparency, and limited personalization.
7. It should initiate in a way like humans to interact in AI chatbots while
communicating to engage more. It should improve its accuracy in terms of
candidate matching.
8. Proper tools should be innovated in AI so it doesn't create much problems while
hiring. Personalized career growth suggestions using AI insights.
9. it should improve candidates testing through real world simulations.
10. I think human involvement is much more needed to improvise the whole hiring
process. The final decision must be made by humans.

Results and Findings-

Through the above survey we get to know about the perceptions of AI driven tools in
hiring decisions. Majority of the respondents (80.5%) still believe that human interaction
and involvement is necessary while recruiting. This encourages the preference to maintain
a human touch in the AI driven mechanism as AI can lack the potential of assessing
qualities like societal fit and inner intelligence. The concerns rises upon ethical values,
biasness in algorithm and to completely trust on automated systems when it comes to
hiring process.

However 28% of the respondents conveyed contingent openness towards AI in hiring

process, based on the roles and industries. This designates that even though AI is not
completely accepted as a single decision making attribute, there are definite areas such as
technical and repetitive screening where automation is widely used. This category could
see AI as an efficient tool in hiring but still requires management to ensure accuracy and
fairness in decision -making.

We could even notice interestingly that none of the respondents completely trusted AI
automation in hiring process and decision even if its unbiased and accurate. This
highlights a doubt on AI’s ability to completely restore and replace human involvement

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when it comes to complex decision-making. It recommends organisations to focus on

using AI as a support tool for decision making process rather than replacing human
recruiters.

Altogether, the findings highlights the need of a approach in a balanced manner of AI

when it comes to recruitment. Even though AI driven tools can increase efficiency, reduce
biasness, and improve matching the right candidate according to the job position, human
interaction still plays a crucial role in securing ethical considerations and practices and
candidates evaluation. Organisations who feel to adapt to AI driven tools should
emphasize on transparency, data safety, biasness reduction and a hybrid perspective that
unites both AI decision making and humans.

Conclusion

The combination of AI in the recruitment process has initiated remarkable advantages

when it comes to efficiency, accuracy and experience of candidates. AI- driven
mechanisms such as predictive analysis, chatbots and resumes screening procedure have
smoothen the hiring process, letting organisations to make quick and more accurate
decisions. This study focuses that AI plays a very crucial role in reducing biasness,
improving job matching with right candidate and looking after repetitive tasks leading to
a more relevant effective process of recruitment. Despite, with these advantages, human
interaction remains important in terms of ensuring ethical considerations, fairness and
more customized approach to hiring process.

Bibliography –

Raghavan, M., Barocas, S., Kleinberg, J., & Levy, K. (2020). "Mitigating Bias in
Algorithmic Hiring: Evaluating Claims and Practices." Proceedings of the 2020
Conference on Fairness, Accountability, and Transparency (FAccT), 469–481.

Upadhyay, A., & Khandelwal, K. (2018). "Applying Artificial Intelligence: Implications

for Recruitment." Strategic HR Review, 17(5), 255-257.

Cappelli, P. (2019). "AI and Hiring: The Good, the Bad, and the Unknown." Harvard
Business Review, 97(4), 1-6.

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Stone, D. L., Deadrick, D. L., Lukaszewski, K. M., & Johnson, R. (2015). "The Influence
of Technology on the Future of Human Resource Management." Human Resource
Management Review, 25(2), 216-231.

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