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“Artificial Intelligence and Its Influence on Human Resource Practices in
the IT Industry.”
Mr. Bhoghyam Charan Teja
1
,Dr. Phani Madhav BGV
2
,Dr. Ghatti. Radhakrishna Murthy
3
,Dr. P. Siva
Prasad
4
1
Assistant Professor, Department Management Studies, enex Business School Nellore, Andhra
Pradesh-India.
2
Associate Professor, Department Management Studies, Zenex Vision Schoo of Business and
Technology Nellore, Andhra Pradesh-India.
3
Associate Professor Department Dept. of MBA, Patel Institute of Science and Management,
Bangalore, Karnataka-India.
4
Assistant Professor Department Management Studies, Loyola Academy, Hyderabad- Telangana-
India.
DOI:
https://doi.org/10.51583/IJLTEMAS.2026.150500199
Received: 17 May 2026; Accepted: 22 May 2026; Published: 13 June 2026
ABSTRACT
The Research case "A Study on AI Impact towards Human Resource with Reference to IT Company" examines
how artificial intelligence (AI) is revolutionizing the Human Resource Management (HR) industry, with a
particular emphasis on the tactics and contributions of IT Company, a world leader in technology and consulting
services. This Study explores the revolutionary potential and related constraints of artificial intelligence's role
in HR. In particular, it encompasses difficulties such as operational challenges in integrating AI into legacy
HR, ethical and regulatory considerations related to AI, data privacy concern, ethical & legal issues and
automation task and enabling data driven decision-making across various HR functions concerns resulting from
reliance on massive datasets. The results are intended to provide light on how artificial intelligence (AI) might
further disrupt the various HR sector and the strategic role IT Company plays in influencing this change and
benefiting the sector. What an artificial intelligence (AI) is revolutionizing the Human Resource Management
(HR) industry, with a particular emphasis on the tactics and contributions of IT Company, a world leader in
technology and consulting services. This Study explores the revolutionary potential and related constraints of
artificial intelligence's role in HR. In particular, it encompasses difficulties such as operational challenges in
integrating AI into legacy HR, ethical and regulatory considerations related to AI, and automation task and
enabling data driven decision- making across various HR functions.
INTRODUCTION
Artificial Intelligence (AI), one of the most significant technological advancements in recent years, is changing
businesses all over the world, including human resource management (HRM). AI is the process by which
machines, especially computer systems, mimic human intelligence processes. The deliberate and integrated
approach to managing people in an organisation is known as human resource management, or HRM. Effective
human capital management has become essential to gaining and maintaining competitive advantage as
businesses continue to function in increasingly globalised, competitive, and technologically advanced
environments. Recruitment and selection, training and development, performance management, remuneration,
employee relations, and labour law compliance are just a few of the many operations that fall under the broad
umbrella of human resource management
Over the past few decades, HRM's role has changed dramatically, moving from a largely administrative one to
one that is crucial to organizational strategy. Employee engagement, the development of a healthy
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organizational culture, and the alignment of human resource strategies with organizational goals are all
prioritized in modern HRM practices. HRM also tackles modern issues like talent retention, remote work,
workforce diversity, ethical hiring practices, and the incorporation of technology into HR procedures.
Need for the Study
Understand how AI is currently applied in HR functions at IT Company.
Analyze the benefits and challenges of using AI in HR.
Assess employee and managerial perceptions regarding AI-based HR processes.
Provide insights and recommendations for responsible and effective use of AI in HRM.
REVIEW OF LITERATURE
Anupam jauhari (2017): In the paper title “how AI and machine learning will impact HR practices
today”. AI has becoming more and more important and reshaping the way companies hire and do
each and every activity recruitment becomes easy for the practitioners because machine learning
technology will make use of Chatbots and proceed all the activities, AI will screen candidates and
send the confirmation or rejection email to the candidates.
Ian Bailie Head of HR (2018) - “An Examination of Artificial Intelligence and its Impact on Human
Resources” This report talks about big firms that adopt AI and examine. It examines both industry
and academic sources to develop a representation of AI and its application in business with a specific
focus on HR.
Rajeev Bhardwaj :( 2019) in this article titled Artificial Intelligence Is Revolutionizing Hiring to
Engagement it was clearly stated that any organization will receive plenty of resumes out which only
10% are relevant. From hiring to employee engagement, artificial intelligence is transforming the
way thanks to the advent of AI supported systems. This process is now taken over by software search
algorithm that are able to successfully prove out the few people matching your requirements from a
pile of irreverent applications.
Statement of the Problem
The Research study artificial intelligence (AI) is revolutionizing the Human Resource Management (HR)
industry, with a particular emphasis on the tactics and contributions of IT Company, a world leader in
technology and consulting services. This Study explores the revolutionary potential and related constraints
of artificial intelligence's role in HR. In particular, it encompasses difficulties such as operational
challenges in integrating AI into legacy HR, ethical and regulatory considerations related to AI,
Scope of the Study
The Scope of this study aims to examine the impact of Artificial Intelligence (AI) on Human
Resource Management (HRM) within IT Company, a global leader in technology and consulting
services as follows.
It focuses on the application of AI technologies in core HR functions such as recruitment, on boarding,
performance management, employee engagement, and learning & development.
The research is limited to IT Company offices in India, although the insights may reflect broader trends
across the organization globally.
The time scope of the study is based on recent developments between 2023 and 2025, taking into account
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current AI implementations and emerging trends.
The study also considers the challenges, ethical concerns, and limitations involved in using AI in HR,
including issues related to data privacy, transparency, and the need for human interaction.
Research Objectives
To understand the role of AI in Human Resource Management at IT Company.
To evaluate the effectiveness of AI tools in recruitment, training, and employee engagement.
To identify the advantages and limitations of using AI in HR practices.
RESEARCH METHODOLOGY
A good research methodology ensures that the study is scientifically sound, reliable, and valid. It includes the
following topics: sample strategies, data gathering methods (such as surveys, interviews, or observations),
research design (such as exploratory, experimental, or descriptive), and analysis tools (such SPSS or Excel),
and ethical issues.
Sampling Plan
The target population and the method for choosing a representative group for the study are specified in the
sampling plan. Because they are most familiar with AI tools used in HR operations, IT Company workers in
the Human Resources department make up the target audience for this study.
Sampling Unit: Individual employees in HR roles.
Sampling Method
The study will employ a purposive sampling method, to select professionals with expertise in AI and HRM.The
sample size is limited to 120 respondents.
Tools used for the Study
SPSS software was used to confine the analysis part of the study.
Percentage analysis
One-way Anova
Chi-square
RESEARCH GAP
The research gaps exist in the context of large-scale global organizations such as IT Company.
Limited Employee Perspective and Gap in Measuring Impact Effectively
Insufficient Real-World Implementation Analysis, Dynamic AI Evolution vs. Static HR Models and Lack of
Organization-Specific Insight
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Data Analysis
Demographic Factors Analysis Table – 1.4.1
Demographic variable
Categories
Frequency
percentage
Age
18-25
95
79.2%
25-35
16
13.3%
35-45
8
6.7%
Above 45
1
0.8%
Gender
Male
65
54.2%
Female
55
45.8%
Professional Background
HR (Training & development)
43
34.8%
HR (Recruiter)
25
21.8%
HR (Payroll)
25
20.8%
Technical Support staff
27
22.5%
Total
120
100%
(Source: Primary data)
Interpretation: The above table indicates, the majority of respondents (79.2 %) fall in the 18-25 age group,
indicating that young professionals from the HR training & development team and majority of respondents are
male (54.2%). The majority 79.2% of the respondents are male fall under18-25 age category in HR Training and
development team.
How Long Has Your Organization Been Using AI in HR
TABLE – 1.4.2
How long has your Organization been using
AI in HR?
percentage
Less than 1 year
38.3%
1-2 years
44.2%
3-5 years
13.3%
More than 5 years
4.2%
(Source: Primary data)
Interpretation: The above table 1.4.2 shows that 44.2% of organizations have used AI in HR for 2 years or less.
Only 13.3% have been using AI in HR for more than 2 years, with just 4.2% using it for over 5 years, indicating
limited long-term experience with AI in HR across most organizations.
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Are You Aware of Any AI Tools Being Used in it Company’s Hr Processes
TABLE – 1.4.3
Are you aware of any AI Tools being used in
IT Company HR process?
percentage
Yes
75.8%
No
24.2%
(Source: Primary data)
Interpretation: The above table 1.4.3 shows that majority of the respondents (75.8%) aware of AI Tools being
used in IT Company HR process. The high percentage of awareness indicates that AI tools are likely well-
integrated and visible in IT Company’s HR operations.
In Which HR Areas Have you Observed AI Being Implemented
TABLE – 1.4.4
In which HR areas have you observed AI being
implemented? (select all that apply)
Frequency
percentage
Recruitment and Acquisition
49
40.7%
Employee Onboarding
43
36%
Performance Management
49
40.8%
Training & development
44
36.7%
payroll
29
24.2%
others
16
13.3%
(Source: Primary data)
Interpretation: The above table 1.4.4 shows that majority of the respondents 41.7% observed that AI being
implemented in recruitment & acquisition, 35% in employee onboarding, 40.8% in performance management.
How Would You Rate Your Understanding of How AI Is Applied In Hr At It Company
TABLE – 1.4.5
How would you rate your understanding of how AI is
applied in HR at IT Company?
Frequency
percentage
Excellent
42
35%
Good
63
52.5%
Fair
12
10%
poor
3
2.5%
(Source: Primary data)
Interpretation: The above table 1.4.5 shows that majority of the respondents (52.2%) has good understanding
of AI applied in HR at IT Company, 35% of the respondents are excellent, 10% of the respondents are fair with
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AI and 2.5% of the respondents are poor.
Have You Received any Training on AI Tools Used in Hr Processes
TABLE – 1.4.6
Have you received any training on AI tools
used in HR processes?
Frequency
percentage
Yes
87
72.7%
No
33
27.3%
(Source: Primary data)
Interpretation: The above table 1.4.6 shows that majority of the respondents 71.7% has received training on AI
tools used in HR process and 28.3% of the respondents are not trained with AI.
How Do You Perceive the Future Role of AI in Hr At It Company
TABLE – 1.4.7
How do you perceive the future role of AI in HR at
IT Company?
Frequency
percentage
Dominant role
34
28.3%
Supporting role
63
52.7%
Minimal Role
13
10.7%
Unsure
10
8.3%
(Source: Primary data)
Interpretation: The above table 1.4.7 shows that, the majority of respondents 28.3 % of the employees are
perceive the dominant role of AI in HR at IT Company, 51.7% of the employee are supporting role, 11.7%
of the employees are minimal role and 8.3% of the employees are unsure about the future role.
To What Extent is AI Integrated into Day-To-Day Hr Operations At It Company
TABLE – 1.4.8
To what extent is AI integrated into day-to-day HR
operations at Accenture?
Frequency
percentage
Fully Integrated
41
34.2%
Partially Integrated
45
45%
Minimally integrated
15
15%
Not integrated
7
5.8%
(Source: Primary data)
Interpretation : The above table 1.4.8 shows that 45% of the employees are fully integrated into day to day
operations, 34.2% of the employees are partially integrated, and 15% of the employees are minimally
integrated and 5.8% of the employees are not integrated.
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On A Scale of 1 To 5, How Satisfied are you with AI-Assisted HR Services (E.G., Chatbots, Support
Systems)
TABLE – 1.4.9
On a scale of 1 to 5, how satisfied are you
with AI-assisted HR services (e.g., chat bots,
support systems)
Frequency
percentage
1
6
5%
2
8
14.5%
3
44
36.8%
4
34
28.3%
5
18
15%
(Source: Primary data)
Interpretation: The above table 1.4.9 shows that the majority of respondents (15%) of the employees are highly
satisfied with AI assisted HR services.
What challenges have you faced (or foresee) with AI in HR? (Select all that apply)
Table 1.4.10
(Source: Primary data)
Interpretation: This table 1.4.10 represents that the majority of the respondents 48.3% somewhat personalized
with AI enabled learning & development programs, 26.7% of the employees are highly personalized, 20.8% are
not personalized and 4.2% of the employees are haven’t experienced them.
What Would you Recommend to Improve the use of AI in Hr At It Company
TABLE – 1.4.11
What would you recommend to improve
the use of AI in hr at IT Company?
Frequency
Percentage
Better training for HR staff on AI tools
25
20.8%
More transparent AI decision-making
38
31.7%
Regular audits of AI systems for bias
34
28.3%
Integration with existing HR systems
9
7.5%
What challenges have you faced (or foresee)
with AI in HR? (Select all that apply)
Frequency
Percentage
Lack of transparency
33
27.5%
Data privacy concerns
55
45.8%
Lack of empathy
35
29.2%
Dependence on technology
32
26.7%
Misjudgments by AI
20
16.7%
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Improved employee communication about
AI tools
7
5.8%
I’m satisfied with the current AI use
7
5.8%
(Source: Primary data)
Interpretation: The above table 1.4.11 shows that 31.7% of the respondents are recommended to improve the
use of AI in HR at IT Company.
Anova Analysis
The statistical technique known as ANOVA (Analysis of Variance) compares the means of several
groups to ascertain whether any significant differences exist between them. It is useful to determine if
observed data variances are the result of random chance or real differences in group averages.
One-Way Anova (Analysis of Variance)
One-Way ANOVA is a statistical test used to compare the means of three or more independent groups
to determine if there is a significant difference among them. It is called "one-way" because it examines
the effect of a single independent variable (factor) on a dependent variable.
1.4.12 Comparision Between age and Level of Satisfaction
TABLE -1.4.12
Sum of
squares
df
Mean
Square
F
Sig
How effective AI works
in HRM
Between Groups
within Groups Totals
535
102.457
102.992
2
116
118
.268
.883
.303
.739
How effective AI works
in HRM
Between Groups
within Groups Totals
2.535
186.457
188.992
2
116
118
1.268
1.607
.789
.457
AI features have
improved employee
engagement at IT
Company
Between Groups
within Groups Totals
24.764
308.085
331.412
2
116
118
5.163
2.613
4.677
.011
Employees are familiar
with at tools used in HR
Process
Between Groups
within Groups Totals
10.327
303.085
313.412
2
116
118
5.163
2.613
1.976
.143
(Source: Primary data)
Interpretation: From the above table 1.4.12 represents that, the table presents the results of a one-way ANOVA
test conducted to examine the impact of AI in Human Resource Management (HRM) at IT Company. Four
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different aspects were analyzed:
1. How effective AI works in HRM (first row)
F = 0.303, Sig. = 0.739
The p-value (0.739) is greater than 0.05, indicating that there is no statistically significant
difference in perceptions among groups regarding the effectiveness of AI in HRM.
Interpretation: Employees generally share similar views on AI effectiveness in HRM, with no major
group-based variation.
2. How effective AI works in HRM
F = 0.789, Sig. = 0.457
The p-value (0.457) is also greater than 0.05, showing no significant difference between groups.
Interpretation: Again, the perception of AI’s effectiveness in HRM does not significantly vary
among employees.
3. AI features have improved employee engagement at IT Company
F = 4.677, Sig. = 0.011
The p-value (0.011) is less than 0.05, meaning there is a statistically significant difference between
groups.
Interpretation: Employees differ significantly in their perceptions of how AI features have
improved engagement. This suggests that some groups may strongly agree AI has boosted engagement,
while others may not experience the same level of benefit.
4. Employees are familiar with AI tools used in HR process
F = 1.976, Sig. = 0.143
The p-value (0.143) is greater than 0.05, indicating no significant difference.
Interpretation: Employees’ familiarity with AI tools is relatively consistent across groups, with
no major variation.
RESULT
Out of the four variables tested, only employee engagement with AI features showed a statistically
significant difference between groups. This implies that while employees generally agree on the
effectiveness and familiarity with AI in HR processes, there are diverse opinions about how much AI has
actually improved engagement.
Chi-Square Analysis
The Chi-Square test is a statistical test used to determine whether there is a significant association (relationship)
between two categorical variables or whether the differences between observed and expected data are due to
chance.
Formula
χ2=∑ (O−E) ^2 E
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Decision Rule:
If the p-value (Sig.) < 0.05, we reject the null hypothesis (there is a significant relationship).
If the p-value > 0.05, we accept the null hypothesis (no significant relationship).
Comparision Between Gender and how Personalized do you Find AI-Enabled Learning or
Development Programs
TABLE – 1.4.13.1 Case Processing Summary 1.4.13.1 G- Gender (HowPersonalized AI enabled in
learning and development programs
Cases
Valid
Missing
Total
N
%
N
%
N
%
G
120
100
0
0
120
100
(Source: Primary data)
Chi-square TABLE – 1.4.13.2
Value
Df
Asymp.
Sig
Pearson Chi-square
likelihood ratio
N. of Valid Cases
6.518
3
.089
6.687
4
.083
1.20
(Source: Primary data)
Interpretation: The above table 1.4,13 shows that p value (0.089) is greater than 0.05, there is no significance
difference between gender and personalized AI – enabled learning or development programs.
FINDINGS
The majority 79.2% of the respondents are male fall under18-25 age category in HR
Training and development team.
The analysis shows that 44.2% of organizations have used AI in HR for 2 years or less.
Only 13.3% have been using AI in HR for more than 2 years, with just 4.2% using it
for over 5 years, indicating limited long-term experience with AI in HR across most
organizations.
The majority of the respondents (75.8%) aware of AI Tools being used in IT Company
HR process. The high percentage of awareness indicates that AI tools are likely well-
integrated and visible in IT Company’s HR operations.
The analysis shows that majority of the respondents (52.2%) has good
understanding of AI applied in HR at IT Company.
The majority of the respondents 71.7% has received training on AI tools used in
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HR process.
The respondents 28.3 % of the employees are perceive the dominant role of AI in
HR at IT Company.
The analysis shows that 45% of the employees are fully integrated into day to day
operations.
The respondents (15%) of the employees are highly satisfied with AI assisted HR
services.
The 45.8% of the respondents are facing major challenges as data privacy concern.
The majority 40.8% of the respondents are said yes that they believe in AI can make
accurate and fair decisions in employee evaluation.
The 31.7% of the respondents are recommended to improve the use of AI in HR at
IT Company.
ANOVA ANALYSIS
Out of the four variables tested, only employee engagement with AI features showed a
statistically significant difference between groups. This implies that while employees generally agree on
the effectiveness and familiarity with AI in HR processes, there are diverse opinions about how much
AI has actually improved engagement.
Chi-Square Analysis
There is no significant relationship between independent variables. Therefore, null
hypothesis is accepted.
Suggestions
IT Company should ensure explain ability of AI algorithms in recruitment and
performance evaluations so that employees trust AI decisions.
Provide training sessions and awareness programs to HR staff and employees on how
to use AI tools effectively.
Upskilling programs on digital and data literacy can increase adoption and reduce
resistance.
AI can speed up tasks such as resume screening and learning recommendations,
but final hiring and performance-related decisions should involve human
managers.
CONCLUSION
AI enhances efficiency by automating repetitive tasks, improving hiring accuracy, and personalizing
learning experiences. At the same time, challenges such as algorithmic bias, lack of transparency, data
privacy concerns, and employee apprehensions about job security must be addressed. The findings shows
that AI is increasingly integrated into IT Company’s HR functions, especially in recruitment, onboarding,
training, and performance management, with high employee awareness and training support. Most
respondents perceive AI as playing a significant role in daily HR operations, improving efficiency and
personalization in learning and development.
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REFERENCE
1. Absar, M., Nimalathasan, B., and Jillian, M. (2010). Impact of HR Practices on Organizational
Performance in Bangladesh, International Journal of Business Insights & Transformation, 3 (2),
15-19.
2. Antarello, S.; Filippini, R.; Nosella, A. Linking human resources management practices and
customer satisfaction on product quality. The International Journal of Human Resources
Management, v. 13, n. 18, p. 3906-3924, 2012.
3. Anupam jauhari. -(2017): Artificial Intelligence Adaptation and its Impact on Human
Resources Practices Among the IT and ITES Companies in Chennai volume 7 issue 9.
4. Severin Lemaignan. - (2017)- Artificial Cognition for Social Human-robot interaction (HRI)
represents a challenge for AI -volume 2 74
5. FAIYAZ Md. iqbal. - (2018) - Can AI change the way in which companies recruit, train,
develop.