Impact of Artificial Intelligence on Middle Level Roles in I.T. Sector

Impact of Artificial Intelligence on Middle Level Roles in I.T. Sector

Dr. Shuchi Priya Mittal

Associate Professor Department of Commerce Shaheed Bhagat Singh College University of Delhi

Anant Teshver

Research Scholar and Student, Department of Commerce Shaheed Bhagat Singh College University of Delhi

ABSTRACT

Purpose:

In this paper, the impact of the incorporation of Artificial Intelligence (AI) on the middle-tier level jobs in the Information Technology Industry is Studied . This paper aims to find out how the implementation of AI can bring about changes in the role of middle level job positions by reducing routine activities, enhancing efficiency, and creating perceptions about job security among employees.

Methodology:

The Study employs a quantitative approach with the use of primary data. The primary data was obtained from the respondents through a questionnaire. For the current study, the questionnaires were distributed to 400 respondents, from whom 173 correctly completed questionnaires have been, obtained, yielding a response rate of 43.25%. that was administered to mid-level IT professionals using stratified sampling. The variables included in the study were Artificial Intelligence , Task Automation, Role change, Productivity, and Job security. A Decriptive Analysis and Correlation analysis was conducted to Investigate the effect of Artificial Intelligence (Independent Variable) on the Dependent Variable namely Task Automation, Role change, Productivity, and Job security .

Findings:

According to the findings, AI helps automate routine activities (r = 0.74) and increases productivity (r = 0.72), and also has an effect on role transformation (r = 0.61). Middle level roles will become strategic, and not operational, roles. However, there is a moderate inverse relationship between job security and AI (r = -0.42). This indicates that people are becoming concerned about their future jobs. In general, AI improves efficiency, but it makes employees uncertain at the same time.

Implications:

This study highlights the importance of understanding the fact that AI is not meant to replace human talent but is rather an enabler of re-inventing Middle Level Roles and Performing Functions . In order to ensure that the Employees do not feel anxious about the implementation of AI systems at the workplace, Companies should rather focus on reskilling, upskilling and communication.

Keywords : Artificial Intelligence (AI) , Task Automation , Job Security , Employee Productivity ,

Role change

BACKGROUND OF THE STUDY

Artificial Intelligence (AI) has become one of the most significant technological changes in recent years, dramatically changing the nature of the functioning of organizations. AI technologies like machine learning, automation, big data analytics, and generative AI tools are common in the Information Technology (IT) industry to enhance efficiency, accuracy, and decision-making. The usage of AI in India has been on the rise owing to digitalization and increased need to innovate. Companies are leveraging AI to automate tedious processes, process extensive data, and facilitate business decisions.

This fast advancement of AI is not only transforming the way work is performed, but also transforming the job positions in various levels of management. Middle level employees like project managers, team leaders and business analysts are very essential in linking the top management with the operating teams. Historically, they perform supervisory roles, coordination, reporting and decision making. But as AI has been integrated, most of these repetitive duties are increasingly being taken over by automated systems. Consequently, the roles of middle managers will become more dynamic and complex than they used to be as they are now supposed to assume more strategic.

Objectives

The study aims to assess the impact of Artificial Intelligence (AI) on mid-level jobs within the IT industry, examining how the integration of AI technologies is reshaping traditional job functions and roles. It attempts to analyze the change from routine and operational tasks to more strategic and analytical functions among middle-level employees. The study also seeks to identify the emerging skill requirements and competencies that managers need to effectively adapt to an AI-driven work environment, while understanding how these changes impact overall workplace dynamics and employee roles.

ProblemStatement

Although AI is increasingly applied to the IT industry, there is still little knowledge on how it affects middle-level jobs. Most of the normal managerial activities like scheduling, monitoring and report preparation are being automated and this leaves the future of middle managers uncertain. The

issue of job security worries employees, and they are afraid that AI will take their jobs away.

Furthermore, middle management faces certain issues like adaptation to technology, skill development, and the integration of human decisions and AI-driven recommendations. Confusion also exists about ethics in AI decision-making. Such issues emphasize the importance of researching the transformation brought about by AI in the middle management level and how to prepare managers for this shift.

Research Aims

1. To assess the effect of AI on mid-level positions within the Information Technology industry.

2. To recognize the alteration in the scope of work caused by the implementation of AI.

3. To recognize the requirement for additional skills in mid-level managers.

Research Questions

1. . What is the perceived impact of Artificial Intelligence on the roles and responsibilities of middle-level employees in the IT sector?

2. . To what extent has AI reduced routine tasks and increased strategic or analytical work among employees?

3. . How does AI influence employees perceptions of job security in the IT sector?

4. . How does the use of AI tools influence the productivity of middle-level employees in the IT sector?

Scope & Limitations

The research paper is about the IT industry where AI is extensively used and constantly expanding. It primarily focuses on the middle-level positions which include team leaders, project managers and analysts. The research is founded on primary and secondary data which are gathered over a short time. Nonetheless, the results might not be generalized to other industries and the outcomes are subject.

LITERATURE REVIEW

Several Researchers have proved that AI has Crucial Role for Revolutionize I.T. Industry. The study titled The Future of Indias IT Sector: Automation, Artificial Intelligence and Job Displacement was conducted at the Indian Institute of Technology, Jammu, India, by Subharun Pal from the Swiss School of Management, Switzerland (2023).The study identified that AI-based automation is revolutionizing the IT industry by eliminating monotonous roles and opening up opportunities in AI, machine learning, and data analytics. It also emphasized on the necessity of reskilling since highly skilled employees are more benefited than those in mundane jobs. Similarly, Maria Josefina Mancera Andrade and Rebecca Salen carried out the study Leading AI Transformation: The Critical Role of Middle Managers in the Jonkoping region of Sweden in four manufacturing companies (2025).The findings revealed that middle managers lay a crucial role in AI transformation by acting as leaders, facilitators, and bridges between top management and employees, while promoting trust, adaptability, and continuous learning.

Dr. V. N. Sharma and Dr. Ashwani Khedkar carried out the study titled Impact of Artificial Intelligence on Employees in Industry 4.0 Organizations at the Christ University in Pune, India (2021).The researchers determined that AI automates approximately a third of routine tasks and improves most jobs, resulting in increased productivity. Nonetheless, it also pointed to the fear of job loss among the employees and the necessity to upskill.

Dr. Ilyas ur Rahman of Shadan Degree College, which is a part of Osmania University, conducted the study The Impact of AI Integration on Middle Management Roles and Organizational Structure in India, Hyderabad (2024).The results showed that AI is repositioning middle-level management as strategic, analytical and innovation-focused and not eradicating the jobs.

J. Nirubarani and Aithal P. S. (Srinivas University and Poornaprajna Institute of Management) carried out a study titled A Study on the Status of Training in the Indian IT Industry with the Impact of Artificial Intelligence in Mangaluru and Udupi, India (2024). This analysis established that AI is changing the training systems, yet issues like untrained trainers and infrastructure remain, with most jobs still being routine. Similarly, Haritha K. B. and Senthil Kumar B. studied the effects of Artificial Intelligence on the employment opportunities within the Indian IT Job market at the Hindustan Institute of Technology and Science, India (2024). The results revealed that AI has a positive effect on job security through role upgrading and development of higher value tasks, but reskilling should be on-going.

Recent Study “Redefining Middle Management: How Generative AI Changes Roles and Skills” is carried out in France by conducting interviews in organizations by Philippe Jean-Baptiste, who is a member of Aix-Marseille University (2025).It was also discovered that middle managers have become major innovators and need to have technical, conceptual, and interpersonal skills along with overcoming obstacles such as resistance and security issues. Similarly The study found that AI increases the efficiency and effectiveness of work but also creates questions regarding job security and output reliability.

The study Impact of Artificial Intelligence on Management was carried out in Finland by Niilo Noponen from the University of Jyväskylä (2019). Their results indicated that while artificial intelligence benefits senior management, it minimizes middle management tasks, forcing them to concentrate on being leaders and people-oriented.

The study Investment in Artificial Intelligence Technologies and Change in the Workforce Structure was carried out by Babina et al. among U.S.-based firms (2023). It was found that AI investments make employees more skilled and create fewer levels of middle management, thereby making the organizations structure flatter.

The StudyAI at the Service of Middle ManagersThe Case of Developing Countries, carried out in Lebanon, was

written by Dina Sidani and her colleagues (2025). The Study Shows results found that the adoption of AI relies on preparation, organizational commitment, and technology infrastructure, especially in developing nations.Similarly, The Study A Review Study on Artificial Intelligence: Implications on Management, conducted in the USA, was written by Koteswara Rao Ballamudi (2019). The results found that AI replaces management roles with automation, yet enhances the value of strategic thinking and innovation.

The research study entitled “Understanding Artificial Intelligence Adoption, Implementation, and Use in SMEs in India” was undertaken in India by Dipak Jadhav and his team members (2021). The Study found that the motivation for adopting artificial intelligence is more related to organizational preparedness and external factors than cultural fit. Similarly, The research study “Generative AI and the Nature of Work” was done at Harvard Business School by Hoffmann and other authors (2025).It was found that the use of artificial intelligence enhances autonomy, reduces coordination, and results in flatter organizational structure.

Research Questions

Question 1 – What is the perceived impact of Artificial Intelligence on the roles and responsibilities of middle-level employees in the IT sector?

Question 2 – To what extent has AI reduced routine tasks and increased strategic or analytical work among employees?

Question 3 – How does AI influence employees perceptions of job security in the IT sector?

Question 4 – How does the use of AI tools influence the productivity of middle-level employees in the IT sector?

Research Variable

In this research Artificial Intelligence is taken as the independent variable and dependent variable is Routine Managerial Tasks , Role Transformation of Middle-Level Employees,Employee Productivity and Efficiency and Job Security Perception

Research Hypothesis

RQ1: Impact of AI on roles and responsibilities

H0: Artificial Intelligence has no significant impact on the roles and responsibilities of middle-level employees in the IT sector.

H1: Artificial Intelligence has a significant impact on the roles and responsibilities of middle-level employees in the IT sector.

RQ2: Reduction of routine tasks & increase in strategic work

H0: AI does not significantly reduce routine tasks or increase strategic/analytical work among employees.

H1: AI significantly reduces routine tasks and increases strategic/analytical work among employees.

RQ3: AI and job security perception

H0: AI does not significantly influence employees perceptions of job security in the IT sector.

H1: AI significantly influences employees perceptions of job security in the IT sector.

RQ4: AI and productivity

H0: The use of AI tools does not significantly influence the productivity of middle-level employees in the IT sector.

H1: The use of AI tools significantly influences the productivity of middle-level employees in the IT sector.

Research Methodology

This section explains about the research design, sampling technique, data collection and analytical tools used to investigate the impact of Artificial Intelligence (AI) on middle level employees on the IT industry.

Sample of the Study

The sample of the present study consisted middle level employee working in I.T. Sector. For the current study, the questionnaires were distributed to 400 respondents, from whom 173 correctly completed questionnaires have been, obtained, yielding a response rate of 43.25%. The response rate was low due to the nature of the study. Questionnaires were distributed to the middle level employees personally and they were asked to contact the researcher whenever they faced any difficulty in responding to the questionnaire. As the questionnaire was self-explanatory, the respondents were asked to fill out the questionnaire as per the instructions mentioned in it. The sample of 173 respondents was considered of sufficient size to provide the needed reliability and validity to the research study.

Data Collection Methods Primary Data

Primary data was gathered through a structured questionnaire consisting of close ended and Likert scale questions to measure:

1. Effect of AI in affecting their job roles

2. Decrease of routine tasks

3. Increase of analytical tasks

4. Perceived job security

5. Productivity

The questionnaire was distributed among 400 middle level IT employees.

Sample Size and Sampling Technique

Therefore, a sample of 173 respondents was chosen for thisstudy. In order to have a representative sample of the different categories of middle-level employees, a stratified sampling method was used to divide the population into subgroups including:

1. Department (development, testing, management)

2. Experience

3. Job roles

Respondents from each stratum were chosen to diversify the sample and enhance the precision of the results.

Research Design

This research design is quantitative in nature. It involves the collection of numerical data using questionnaire that is used to establish patterns, relationships and trends regarding the impact of AI on employees roles, productivity and job security.

Data Analysis

The variables measured are changes in job roles, reduction of routine tasks, increase in analytical tasks, productivity and job security. For data analysis, Descriptive Analysis method and correlation method and were used to identify and assess the relationship between AI adoption and these variables. It helps to ascertain the strength and direction of association between AI adoption and the independent variables.

RESULTS AND ANALYSIS

The majority of the respondents are male, with substantially lower female participation. Few respondents chose not to answer this question. The sample is male-dominated, and could possibly lead to a slight bias in the adoption of AI for the male perspective.

The majority of respondents are from the below 25 age group followed by 2534. There are very few respondents in the higher age brackets. The study is more reflective of the opinions of young professionals especially early-career employees.

Mostly the respondents are BCA/Master’s graduates, B.Tech or PhDs are less in number. Sample is academically sound and have heavy IT education background.

Most are Business Analysts and Team Leads with less Project Managers and other. The study is on the mid-level roles which is a good match to the research objective.

Most respondents have less than 5 years of experience, followed by 510 years. Sample is biased towards relatively less experienced professionals.

A vast majority said their organizations use AI tools. Large percent of orgs in IT are using AI.

ChatGPT and Github Copilot are the most used, others are sparingly used.AI usage are clustered around a few popular

tools

The AI is used in project management, development support and reporting. AI is deeply embedded in the operational and technical domains.

Most respondents indicated moderate to high adoption, with few at very low or very high levels AI adoption is increasing, but not yet matured.

Most people think that AI has automated many managerial tasks. It is really getting rid of repetitive tasks of managers.

Most people agree that their roles are changing from operational to strategic. AI is turning middle managers into people who make strategic decisions.

Most people think that Artificial Intelligence has made things easier and faster for them. Artificial Intelligence really helps people do their jobs better.

Respondents agree AI allows more focus on leadership and people management. AI frees time for managerial and interpersonal responsibilities.

Most respondents believe AI insights play an important role in decision-making. AI is becoming a key support tool for managerial decisions.

The attributes rated most important were change management, decision-making, and communication. The importance of soft and strategic skills is growing at a greater rate than technical skills.

Reactions are mixed; some get training while others do not. It is unclear whether organizations are committed to building up AI skills.

AI makes many workers feel insecure about job safety. Job insecurity remains an issue for many workers.

A significant portion is concerned about long-term role relevance. AI creates anxiety about future career stability.

Most respondents believe AI enhances jobs rather than threatens them. The overall perception of AI is positive.

Many respondents feel confident, but some still lack confidence. There is moderate readiness to work with AI systems.

DISCUSSION

The results of this research corroborate with previous literature, which indicates that AI does not replace managers, but rather, transforms the way managers perform their jobs. Studies on the implementation of AI indicate managerial jobs will be characterised by an increased emphasis on strategic decision-making. The positive relationship between transformation of roles and work enhancement supports these findings.

Therefore, previous research found that productivity will increase as a result of using AI; however, this finding is consistent with the concluded that automation will not impact employees’ productivity directly (but will influence indirectly).

Answer of Research Questions

RQ1: Impact of AI on Jobs

AI shifts jobs from an operational function to a more strategic/leadership function.

RQ2: AI and Productivity

AI enhances productivity through leadership and role transformationnot just automation.

RQ3: Job Security Attitudes

Employees show a moderate to high level of concern about job security, indicating some uncertainty.

RQ4: AI and Job Performance

AI has a positive effect on job enrichment/creativity; however, it also causes psychological stress.

Unexpected Findings

One unexpected result was:

Strong positive correlation (0.54) between job insecurity and job enrichment

Explanation:

1. Employees recognize AI benefits

2. But fear long-term replacement

This creates a paradox:

AI is helpful but also threatening Theoretical Implications

The theoretical contribution of this research is:

1. Validation of the Human-AI Collaboration idea.

2. Showing that technological change is not entirely positive.

3. Emphasizing the significance of psychological/behavioral reactions.

This means that:

AI should be considered a transformative technology, rather than merely an instrument for boosting efficiency.

CORRELATION RESULTS

Quantitative Findings

AI and Automation of Routine Tasks

The correlation analysis revealed a strong positive relationship (r 0.74) between AI adoption and automation of routine tasks

Discussion:

The use of AI is providing much support for automating repetitive tasks and responsibilities from a management or administrative standpoint, based on a strong positive correlation between the two elements. Further, the use of AI tools/bots like ChatGPT, TensorFlow, etc., are helping to reduce manual workload.

AI and Role Shift

A moderate positive correlation (r 0.61) was observed between AI adoption and role transformation.

Discussion:

This indicates that AI is moving away from changing jobs from more routinely controlled supervisory positions to more reasonably strategic and analytical job duties. Employees are involved more in decision making as opposed toperforming their normal tasks of supervising by monitoring the activities of their coworkers.

AI and Productivity

The analysis showed a strong positive correlation (r 0.72) between AI adoption and productivity.

Discussion:

When employees work within an AI-enabled environment, their ability to accomplish tasks efficiently and successfully is greatly enhanced by these technologies through support of AI assisted automated decisions.

AI and Job Security Perception

A moderate negative correlation (r -0.42) was identified between AI adoption and job security.

Discussion:

It means that, with more use of artificial intelligence, there are increased worries about job security among the workers. Though AI makes things more productive, it also raises uncertainties related to employment.

Qualitative Findings

• Positive Perceptions of AI

  It means that, with more use of artificial intelligence, there are increased worries about job security among the workers. Though AI makes things more productive, it also raises uncertainties related to employment.

  1. There were many respondents who stated that artificial intelligence made work productive and efficient.

  2. Respondents claimed that artificial intelligence helped in making decisions and reduced workload.

  3. You can use AI in performing strategic tasks.

• Mixed Perception of Role Change

  1. For some respondents, it seemed that their jobs had gained more of a strategic nature.

  2. However, other participants remained indifferent, implying that the process took place gradually or was incomplete.

     • Issues Relating to Job Security

       1. Quite a large proportion of participants appeared to be anxious regarding their jobs being terminated.

       2. Several participants expressed strong agreement about AI making their job redundant.

• Variation Based on AI Adoption Level

  1. Respondents from high AI adoption environments showed:

     1. Higher productivity

     2. Greater role transformation

  2. Respondents from high AI adoption environments showed:

     1. Lower impact of AI

     2. More neutral or negative responses

Interpretation

0 AI vs Automation of Routine Tasks

There is a strong positive link (r = 0.74) between using AI and automating everyday tasks. This means that as AI becomes more common, many routine managerial and administrative tasks are done automatically.

0 AI vs Role Shift

There are moderate, but positive, correlations between AI and role transformation (r = 0.61). This indicates that the deployment of AI is shifting employee role from operational supervision to strategic decision-making.

0 AI vs Productivity

There was also a strong positive correlation (r = 0.72) between AI adoption and productivity, indicating that AI supports the increased efficiency and productivity of middle management roles within an organization..

0 AI vs Job Security

There is a moderate negative relationship between AI adoption and the perception of job security (r

= -0.42); thus, as the adoption of AI increases, employees will perceive an increase in their level of concern regarding their job security.

SUMMARY OF FINDINGS

According to this research, Artificial Intelligence (AI) has a significant effect on mid-level employees working in the IT industry through many different dimensions.

The results showed that as an employee’s workflow becomes primarily defined by performing repetitive managerial/administrative tasks, there is a strong positive correlation (r = 0.74) between the adoption of the AI tools that automate those types of tasks and the number of hours available to spend on higher-value taskswhich are activities that provide greater value to the organization.

Additionally, the data showed that there is a moderate positive correlation (r = 0.61) between the adoption of AI tools and the transformation of middle-management positions. More and more employees in mid-management are transitioning from a traditional operational supervisor role to a

more strategic role of analyzing data and making decisions. This represents a shift in what managerial work will look like in the future as businesses integrate AI into their respective ecosystems.

There was also a strong positive correlation between AI tools and productivity (r = 0.72). AI-driven tools enhance organizational efficiency, providing employees with better decision-making support, and better productivity due to their employees being able to complete tasks faster than without AI tools.

However, even though mid-level employees using AI tools reported higher job performance and role enrichment, they also reported a moderate negative correlation (r= -0.42) between the adoption of AI tools and perceived job security. This shows that employees are experiencing uncertainty and are fearful about the long-term viability of their jobs. Thus, AI may enhance job performance and existing roles but simultaneously create Psychological issues for employees.

Answering the Research Questions

RQ1 – How does Artificial Intelligence impact the perceived roles and responsibilities of middle- level IT sector employees?

Answer – This study shows that middle-level employees are significantly impacted by AI as it is changing the way their positions function. AI has begun to automate traditional functions of middle-level managers such as monitoring, reporting, and coordinating, thus allowing managers to be able to concentrate more on functions such as Strategic Planning, Leadership, and Decision-Making.

RQ2 – To what degree does AI reduce the number of routine tasks and increase the amount of Strategic/Analytical work for employees?

Answer – AI has led to significant reductions in the number of routine and repetitive tasks performed by employees as well as having an increase in the amount of work employees are performing related to Analytical and Strategic functions.

RQ3 – What are the effects of AI on employee perceptions of job security within the IT sector?

Answer – The results of our study indicate that different employees have different perceptions of job security based on how they view AI. While there are some employees who see AI as a benefit for their personal growth, there are other employees who consider AI as a potential threat to their job security leading to moderate levels of job insecurity.

RQ4 – How do AI Tools affect the productivity levels of middle managers within the IT sector?

Answer – AI has a positive effect on employee productivity levels. It provides increased efficiency, improves the quality and speed of decision making and allows middle managers to perform tasks more efficiently and accurately.

Contributions to Knowledge

The research will add to theory and practice. In theory, it supports the theory of HumanAI cooperation by showing that AI can function as a complementary tool alongside humans rather than being a substitute; in other words, it shows that advances in technology will transform a role rather than eliminate a job.

In addition, the research provides quantifiable information about relationships between AI adoption, automation, productivity, role transformation, and job security using correlation analysis. Finally, by

combining both quantitative and qualitative information, the research provides an integrated picture of how AI affects people.

The research#39;s major contribution was identifying the psychological side of AI adoption; that is, when AI improves productivity, it may also produce anxiety and uncertainty in the employee due to various human factors that should be taken into account in implementing technology.

Practical Recommendations

The results of this study provide a number of practical recommendations for organizations and their policymakers as they work toward implementing artificial intelligence (AI) in their organizations.

To begin with, organizations will need to provide continuous training and support for their employees to maintain and develop the necessary skills to use AI effectively. This will include

both upskilling and reskilling initiatives for the ongoing evolution of employees’ job roles in response to rapidly changing technological advances.

Second, both technical and soft skills will be essential for all employees as they move to more

strategic roles, where their ability to lead, communicate, and make decisions will become increasingly important.

Thirdly, there is a need for organizations to foster an atmosphere that encourages openness and transparency during the implementation of AI. The need to understand the purpose of AI and its role within an organization will go a long way in alleviating employees’ fears regarding AI.

In addition, there is a need for organizations to move beyond using AI on basic work activities to using it on advanced work activities, such as decision making and innovations. Hands-on training will make employees much more confident in using AI.

Limitations

However, despite some positive aspects to this study, it has several limitations. The sample size

might also be a limitation to the generalizability of these results because of the few respondents (n=173).

The researchers could have received a more credible set of data had the sample been bigger.

Moreover, information on any single industry such as IT might fail to suffice in depicting the effects of AI in various industries. The rate of AI usage and adoption is quite different in different industries, hence, the rest of the industries may not have been adequately represented in the research.

Finally, every piece of data used was self-reported on questions, and this may lead to measurement bias as every answer is only the perception of the individual concerning the issue. The sample is also mostly made up of younger individuals who might not reflect the views of the older and more experienced employees.

Future Research

The following researches will have to attempt to compensate the underrepresentation of various industries and locations in this research with the help of larger sample and more diverse sample of all industries and regions.

A comparison of the various sectors would have been of more help in understanding how AI influences the various working environments.

The longitudinal studies of the impact of AI on the career of workers, their employment stability, and the organization structures will have to be done in such a way that we will be able to observe whether the current trends are going to persist or evolve in the future.

Future research must explore how organizational culture, leadership, and policy frameworks are related and how they influence the adoption of AI and how employees can adapt to that adoption. Interviews and case studies might be used in qualitative studies to learn more about how employees feel and experience working and coping in a new AI work environment.

Lastly, future studies can include the ethical issues of fairness, accountability, and transparency regarding AI-driven decisions, to ensure the responsible and sustainable implementation of AI.

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