The Impact of Artificial Intelligence and Human Computer

Interaction Leadership Professionals

N. Vinodh and A. K. Subramani

Saveetha School of Management, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai,

Tamil Nadu, India

Keywords: Artificial Intelligence (AI), Leadership Styles, Human Resource, Management.

Abstract: In this research examine the ways in which employee motivation has been affected by the revolutionary

implications of virtual intelligence on leadership styles in the individual resource administration (HRM)

domain. The apply a mixed-method approach to examine the complex interaction among AI deployment, HR

management, and employee morale by integrating the findings of qualitative interviews with quantitative

survey data. AI adoption is positively correlated with both leadership style change and Employee Engagement

according to statistical analysis. HR executives are changing their leadership approaches, embracing more

adaptable styles, granting employees greater autonomy, and enhancing communication channels in the new

AI-enabled HRM environment. This study bridges the gap between theory and reality by offering business

owners and HR managers’ practical guidance. Future research should look into longitudinal dynamics, cross-

industry variances, ethical and cultural concerns, innovative AI applications, and employee perspectives in

order to advance the field of AI-enhanced HRM.

1 INTRODUCTION

The global shift towards digitalization is reflected in

the intersection of AI and HRM. HR departments can

handle enormous amounts of data, make data-driven

choices, and automate repetitive tasks with the help

of AI-powered tools and algorithms (Cui et al., 2021).

These adjustments enhance HR operations and free

up HR specialists to focus on strategic objectives like

employee engagement and talent development.

Businesses are aware that developing a dynamic and

adaptable workforce requires strong leadership. HRM

leadership includes a variety of approaches and

strategies. Traditionally, decision-making has been

done in a top-down, hierarchical manner. AI causes a

paradigm shift by giving HR professionals new tools

and insights to alter their leadership philosophies. AI

in HRM calls for more than simply better technology;

it calls for a fundamental rethinking of leadership

paradigms (Jia et al., 2024). The research looks at the

relationships between employee engagement, HRM

leadership styles, and AI. In today's HR debate,

employee engagement is essential to productivity, job

satisfaction, retention, and organizational

effectiveness. We examine the ways in which

technologies driven by AI, including intelligent

assistants, chatbots, and automated forecasting, are

altering HR leadership methodologies (Al Kohji et

al., 2024). It aims to ascertain whether these

technologies foster teamwork, flexibility, and

employee-centered leadership or if they contribute to

problems with the human-machine interaction.

To comprehend these complexities, the research

will involve questionnaires, interviews, and a

thorough literature review. The study will investigate

how HR directors respond to AI-driven

advancements and how these adjustments affect

employee engagement using both quantitative and

qualitative data. In addition to contributing to AI and

HRM research, this study will offer useful guidance

for CEOs, legislators, and HR professionals (Hidayat

et al., 2024). As a result, AI in HRM is changing the

definition of leadership and requiring a shift from

outdated ideas to one that is more employee-centric

and technologically informed. This study looks at

how employee engagement and leadership styles are

impacted by this shift. By empowering and involving

workers, an understanding of the relationship

between AI and leadership may help businesses thrive

in the digital era.

Vinodh, N. and Subramani, A. K.

The Impact of Artiﬁcial Intelligence and Human Computer Interaction Leadership Professionals.

DOI: 10.5220/0013901900004919

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies (ICRDICCT‘25 2025) - Volume 3, pages

557-561

ISBN: 978-989-758-777-1

557

2 PROPOSED METHODOLOGY

With a focus on how each affects employee

engagement, we apply a mixed-method research

approach in this study to examine the complex

relationship between AI and leadership philosophies

in the context of human resource management (HRM)

(Dillianti et al., 2024). Using this approach to

combine quantitative and qualitative data has

advantages, but there are drawbacks and potential

limitations as well (Masaeid & Upadhyay, 2023). The

quantitative portion involves distributing

questionnaires to employees and human resources

specialists at different businesses. A Likert scale,

which is frequently employed in survey research, can

be used to quantify answers to questions about the

usage of AI in HRM. When applied to the

relationships outlined by the following equations,

multiple linear regression models, which presume

linear relationships between variables, may

oversimplify the intricate dynamics at work (Saide et

al., 2024). Furthermore, it's possible that not all of the

nuances of AI adoption within HRM were covered by

the Likert scale utilized for integration (Saputra,

2023). Although leadership style change and

employee engagement (EE) are clearly significant,

they are also intricate concepts that defy easy

quantification. Semi-structured interviews offer a

detailed analysis of respondents' lived experiences,

making them potentially a treasure trove of

qualitative data. Nonetheless, the process of

qualitative analysis, particularly theme analysis, is

ingrained with and dependent upon the interpretation

of researchers (Marinova-Stoyanova, 2023).

The creation of thematic maps and coding

categories could introduce bias into the study process

and fail to fully represent the diversity of viewpoints

(Xiang, 2023). To investigate these two hypotheses,

this study proposes a positive, one-way relationship

between AI integration and leadership style change,

and AI integration and EE (Biggadike et al., 2022).

The oversimplification may cause significant

subtleties in the relationships under study to be

overlooked. Although data anonymization and

informed consent are essential, it's vital to consider

the potential for participant coercion or reluctance to

provide candid responses, especially within

organizations (Santos et al., 2021). In conclusion, it is

critical to recognize the limitations and potential

biases in both quantitative and qualitative techniques,

even if the mixed-method study methodology

provides a comprehensive examination of AI's

influence on HR leadership styles and employee

engagement (Priya et al., 2024). It is necessary to be

aware of these limitations and use a critical lens to the

study findings in order to comprehend the complex

link that exists between AI, HRM leadership, and

employee engagement.

3 RESULT AND DISCUSSIONS

The measurement outcomes characteristic statistics, a

poll of employees and HR professionals, examined

the effects of AI integration on employee engagement

and leadership style change. Managing human

resources with artificial intelligence, users were asked

to rate the degree to which AI is now utilized in

human resource management using a point rating

system (Wardoyo & Dewi, 2023). With a mean value

on the AI integration indicator, overall AI integration

was minimal (Yadav & Bhatia, 2022). Analysis of

regression through the use of multi-linear regression

analysis, the interaction between AI Integration,

leadership style change, and EE was examined.

Leadership style Model: Regression analysis

demonstrates a favorable relationship between AI

Integration and Leader style change .As they become

more accustomed to AI's position in HRM, human

resources leaders are refining their management

strategies. This supports the null hypothesis,

according to which AI Integration has no effect on

Leader style change .The model of employee

engagement AI Integration and employee

engagement show a comparable association discover

that EE increases in proportion to the degree of AI

integration, supporting hypothesis which holds that

AI integration benefits employee engagement.

4 LEADERSHIP STYLES

Results qualitative examining similarities or thematic

analysis to sort through the findings of semi-

structured interviews with managers, employees, and

HR specialists, researchers employed theme analysis.

Several themes have come up repeatedly: A flexible

approach to leadership: HR managers are adapting

their leadership styles to fully utilize AI's promise.

The Situational Leadership Model is frequently used

to describe how successful leaders adjust their tactics

based on the readiness and proficiency of their teams.

Employee Empowerment HR directors can focus on

empowering employees by delegating tedious tasks to

machines through AI integration. This notion is in

line with emphasizes having faith in people's inherent

motivation Improve Communication: Chatbots and

ICRDICCT‘25 2025 - INTERNATIONAL CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION,

COMMUNICATION, AND COMPUTING TECHNOLOGIES

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virtual assistants make it possible, underscoring the

need of Communication Model between employees

and human resources. Result illustration the

quantitative results validate that AI Integration has a

positive effect on both leadership style change and

employee engagement as anticipated by the study

hypotheses. The coefficients demonstrate the impact

of AI integration on HR management and employee

morale due to their statistical significance. The

qualitative results underline the revolutionary

potential of AI in line with the quantitative statistics.

Human resources managers are embracing more

flexible leadership techniques, increasing

communication, and empowering employees in ways

that are more similar to and the situational leadership

model. The findings show that instead of worrying

that AI could totally upend the sector, firms are

adjusting to the evolving AI environment by viewing

AI as a tool to enhance HRM. It is evident from

combining the quantitative and qualitative results

how useful AI can be as a tool to improve HR

leadership and, consequently, employee engagement.

In conclusion, the data demonstrate that integration

significantly and favorably affects staff engagement

and leadership changes linked to HRM. The study

connects the theoretical underpinnings of Theory Y

and the Situational Leadership Model with the real-

world applications for HR professionals and

companies looking to maximize HRM through

artificial intelligence.

It's crucial to remember that self-report data has

limitations and that actual AI integration scenarios

may be more challenging than initially thought.

Researchers must delve further into the mechanisms

at work to completely comprehend how AI affects

leadership and employee engagement.

5 HRM LEADERSHIP

The results of this study offer significant new insights

into how AI affects HRM leadership philosophies

and, consequently, workforce engagement. The

discussion in this part examines the significance of

these findings for academic and applied HRM

environments .Connecting theory and practice: The

results of this study provide light on how HRM is

evolving in the age of AI and offer empirical evidence

in favor of the theoretical foundations of employee

motivation and leadership. This study demonstrates

how AI integration encourages HR executives to use

the Situational Leadership Model, which was

recommended to adopt adaptive leadership styles that

consider the readiness and proficiency of their teams.

Additionally, because it emphasizes trust in

employees' innate motivation, it aligns with theory

optimizing human resource management one of the

primary contributions of the research is the useful

implications it has for HR professionals and company

executives. The positive effects of A Integration on

LS_Change and EE are illustrated in this study, which

helps HR professionals who wish to employ AI as a

strategic tool. Managers of human resources may

view AI's potential as a tool to support more flexible

leadership rather than as a challenge to the status quo.

The findings show that human resource

professionals must reconsider leadership paradigms

in the digital age, placing more of an emphasis on

employee empowerment and communication

enhancement through the use of AI-driven

technology such as chat bots and virtual assistants.

6 EMPLOYEE ENGAGEMENT

The increasing worker dedication AI integration has

been scientifically linked to employee engagement,

one of the key ideas in contemporary HRM. This

illustrates how AI has the revolutionary potential to

increase worker participation. AI in HR management

may increase worker satisfaction, productivity, and

loyalty for employers. Consequently, our findings

offer a roadmap for HR managers who wish to

increase their organization's competitive edge by

developing a motivated and capable workforce.

Future research and its practical implications

although this study establishes the framework for

investigating the relationships among AI, HR

administration, and employee engagement, it is

important to recognize its limits. Future research

should concentrate on the nuanced ways that AI

influences employee engagement and leadership

styles. Examining these relationships over time could

shed light on how they evolve as AI advances. The

results of research have the power to motivate

significant, real change. Businesses that have

implemented AI solutions for HRM may utilize these

findings to justify their expenditures. Artificial

intelligence (AI) solutions can be used by human

resources managers to increase administrative

operations' efficiency and promote dynamic

leadership and employee engagement. The reader

benefits those who read this research paper will

benefit in a number of ways. The making informed

decisions: government regulators, corporate leaders,

and human resource managers can now decide how

best to integrate AI into HRM. They study in-depth

how AI might impact employee morale and

The Impact of Artiﬁcial Intelligence and Human Computer Interaction Leadership Professionals

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management procedures. This study expands on

existing knowledge and establishes the framework for

future research competitive advantage companies that

implement the study's findings will have a clear

advantage in the marketplace since they will have

mastered the application of artificial intelligence to

create more motivated and capable employees, which

will improve business outcomes. Lastly, this study

sheds light on the evolving dynamics of HRM in the

AI era and offers helpful insights that could spur

positive changes in HR practices. It bridges the gap

between leadership and employee engagement theory

and practice, enabling organizations to flourish and

endure in the current digital era.

7 FUTURE SCOPE

Future research in the sector should prioritize

longitudinal studies to track the dynamic interactions

between employee engagement, HR management

strategies, and AI adoption. While studies on the

ethical and cultural aspects of AI in HRM are

essential for global implementation, comparisons

across industries and organizational sizes may

provide more nuanced perspectives. As the area of

human resource management (HRM) adjusts to the

results of research into sophisticated AI applications

and their implications, employee perspectives, ethical

frameworks, and AI-driven skill development, more

efficient and morally sound AI-integrated HR

practices will be created

8 CONCLUSIONS

The investigation has revealed how AI is altering

HRM leadership strategies, which in turn is affecting

employee engagement. The study's findings highlight

if AI has an opportunity to completely change the

administration of human resources by confirming the

positive link between A Integration and both.

Leadership Style Change and Employee Engagement

Managers of human resources are adapting their

strategies to better fit recognized leadership ideas.

This entails developing a flexible leadership style,

enhancing communication, and granting employees

greater freedom. In addition to bridging theory and

practice, this study offers business managers and HR

professionals’ valuable insights on how to leverage

AI to improve employee engagement and optimize

HRM practices. Ongoing longitudinal research,

cross-industry assessments, a focus on ethics, and

advanced AI applications will all influence our

understanding of this changing environment and the

efficacy of HRM in the digital age.

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