E-ISSN:2583-1747

Research Article

Artificial Intelligence

Management Journal for Advanced Research

2025 Volume 5 Number 3 June
Publisherwww.singhpublication.com

Artificial Intelligence: Impact on Industries and Redefining the Future of Work

Kashyap P1*
DOI:10.5281/zenodo.15905694

1* Pallabi Kashyap, Research Scholar (Ph.D), Department of Commerce and Management, Assam Downtown University, Guwahati, Assam, India.

Artificial Intelligence (AI) is transforming industries by automating processes, optimizing efficiency, and enhancing decision-making capabilities. While AI-driven innovations have led to increased productivity and cost reductions, they have also resulted in significant workforce disruptions, raising concerns about large-scale job displacement and economic implications. Industries such as technology, manufacturing, and customer service are witnessing substantial layoffs as companies shift towards AI-driven operations.
Major corporations like IBM, Salesforce, Google, Foxconn, and Concentrix have implemented AI solutions, replacing roles in marketing, sales, production, and customer support. This transition underscores AI’s growing dominance but also highlights the widening gap between technological advancement and workforce preparedness. While AI is projected to create new job opportunities in areas such as AI development, data analysis, and ethics governance, the shift requires extensive retraining and upskilling initiatives.
This paper explores real-world cases of AI-driven workforce restructuring, the broader economic consequences, and the socio-political challenges arising from automation. It also examines the role of policymakers, businesses, and educational institutions in mitigating AI’s disruptive effects by fostering reskilling programs, ethical AI deployment, and sustainable workforce strategies. As AI continues to evolve, industries must strike a balance between technological innovation and social responsibility to ensure long-term economic stability and equitable workforce integration.

Keywords: artificial intelligence, workforce automation, job displacement, industry transformation, ai ethics, reskilling and upskilling, digital skills gap

Corresponding Author How to Cite this Article To Browse
Pallabi Kashyap, Research Scholar (Ph.D), Department of Commerce and Management, Assam Downtown University, Guwahati, Assam, India.
Email: 		Kashyap P, Artificial Intelligence: Impact on Industries and Redefining the Future of Work. Manag J Adv Res. 2025;5(3):61-68.
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https://mjar.singhpublication.com/index.php/ojs/article/view/225

Manuscript Received Review Round 1 Review Round 2 Review Round 3 Accepted
2025-05-17 2025-06-02 2025-06-20
Conflict of Interest Funding Ethical Approval Plagiarism X-checker Note
None Nil Yes 3.66

© 2025 by Kashyap P and Published by Singh Publication. This is an Open Access article licensed under a Creative Commons Attribution 4.0 International License https://creativecommons.org/licenses/by/4.0/ unported [CC BY 4.0].

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Download PDFBack To Article1. Introduction2. Broader
Implications of
AI-Driven Layoffs3. Effects of AI
on Different
Industries4. Practical
Examples and
Case Studies5. Ethical and
Social Concerns6. Methodology7. Future
Outlook and
Recommendations8. ConclusionReferences
Kashyap P. Artificial Intelligence: Impact on Industries and Redefining the Future of Work

1. Introduction

Artificial Intelligence (AI) is revolutionizing industries worldwide by automating tasks, enhancing decision-making, and boosting productivity. From tech giants to manufacturing plants and customer service hubs, AI’s adoption is reshaping how businesses operate. While these advancements promise efficiency and cost savings, they also bring significant challenges, particularly in the form of workforce reductions. Companies are increasingly laying off employees as AI takes over roles once performed by humans, sparking debates about the technology’s long-term impact. This report dives into the practical effects of AI on industries, spotlighting specific examples of layoffs tied to AI adoption. By examining cases from the tech sector, manufacturing, and customer service, we’ll explore how companies are restructuring their workforce and what this means for employees and the economy.

AI in the Tech Industry

The tech industry, a pioneer in AI development, is experiencing some of the most visible workforce shifts due to AI. Major companies have publicly linked layoffs to their AI strategies, offering concrete examples of this trend.

IBM: In early 2023, IBM announced layoffs in its marketing and communications division as part of a broader workforce realignment. While the company did not disclose the exact number of affected employees, CEO Arvind Krishna has openly discussed AI’s role in this shift. In a statement, Krishna noted that IBM is “massively upskilling” its workforce in AI, signaling a move away from roles that AI can replace. He also projected that up to 30% of back-office roles could be automated within five years, a strategy that has already led to staff reductions (Source: Bloomberg, May 2023). These layoffs reflect IBM’s pivot toward AI-driven operations, prioritizing technical expertise over traditional functions.

Salesforce: Salesforce, known for its customer relationship management tools, laid off hundreds of employees in 2023 as it sharpened its focus on AI. CEO Marc Benioff emphasized AI as a cornerstone of the company’s future, stating in an earnings call that the layoffs were part of an effort to “renew our focus” on AI innovation (Source: Salesforce Q1 2023 Earnings Call).

While specific figures vary, reports suggest that these cuts affected roles in sales and support—areas increasingly automated by AI tools like chatbots and predictive analytics. This move underscores how even tech leaders are trimming staff to fund AI advancements.

Google: Google, a titan in AI research, has also tied layoffs to its AI ambitions. In 2023, the company cut hundreds of jobs across teams like advertising and hardware. A memo from Chief Business Officer Philipp Schindler highlighted the “profound moment we’re in with AI,” linking the layoffs to a strategic shift toward AI-driven products (Source: The Verge, January 2023). For instance, AI is streamlining ad creation and optimization, reducing the need for human input in these areas. Google’s actions show how AI’s efficiency gains can lead to workforce downsizing, even in a company known for innovation.

These tech examples reveal a pattern: companies are shedding jobs in roles that AI can automate, redirecting resources to AI development and deployment. The layoffs are practical outcomes of a broader push to stay competitive in an AI-dominated landscape.

AI in Manufacturing: Automation and Workforce Reduction in manufacturing, AI is accelerating automation, replacing human workers with machines that can operate faster and more precisely. This shift is leading to layoffs, particularly among manual laborers.

Case Study: Foxconn: Foxconn, a major electronics manufacturer, provides a stark example of AI-driven layoffs. The company, which assembles products like Apple’s iPhones, has implemented AI-powered robots to handle repetitive tasks on its production lines. In 2016, Foxconn reportedly replaced 60,000 factory workers with robots, a move later expanded with AI to optimize workflows (Source: BBC, May 2016). By 2023, the company continued this trend, with AI managing quality control and assembly processes. While exact recent layoff numbers are harder to pin down, Foxconn’s leadership has acknowledged that automation, enhanced by AI, reduces the need for human workers, directly impacting employment in its factories.


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This case illustrates how AI in manufacturing isn’t just about replacing humans with machines—it’s about creating smarter systems that require fewer people to oversee. For workers, this means fewer opportunities in roles that once formed the backbone of industrial employment.

AI in Customer Service: The Rise of Chatbots

Customer service is another industry feeling AI’s impact, as companies deploy chatbots to handle inquiries traditionally managed by humans. These tools are slashing the need for staff, leading to significant layoffs.

Case Study: Concentrix: Concentrix, a global customer service provider, laid off hundreds of employees in 2023 after expanding its use of AI chatbots. The company’s AI system, designed to handle routine queries like billing issues and order tracking, reduced the need for human agents. While Concentrix didn’t publicly quantify the layoffs, industry reports link the cuts to its AI rollout, with CEO Chris Caldwell noting in a statement that AI is “transforming how we deliver value” (Source: Business Wire, June 2023). This shift allowed Concentrix to cut costs, but it left many customer service reps out of work.

This example highlights a growing trend: as AI chatbots become more adept at mimicking human interaction, companies are scaling back their human workforce, prioritizing efficiency over employment.

2. Broader Implications of AI-Driven Layoffs

The layoffs detailed above are not isolated incidents—they signal a seismic shift in how industries operate. Here’s what this means on a larger scale:

Workforce Disruption: AI-driven layoffs often hit workers in roles that are hard to pivot from. Manufacturing laborers and customer service reps, for instance, may lack the technical skills needed for AI-related jobs, leaving them vulnerable. Retraining programs are critical, but not all workers have access or time to adapt.

Economic Fallout: Mass layoffs could dampen consumer spending and increase unemployment, straining economies. However, AI also fuels growth in new areas—think AI developers or data analysts. The catch? These jobs often require advanced skills,

widening the gap between displaced workers and emerging opportunities.

Balanced View: Not everyone sees AI as a job-killer. Some experts argue it will create more roles than it eliminates. For example, the World Economic Forum predicts that by 2025, AI will displace 85 million jobs but create 97 million new ones (Source: WEF Future of Jobs Report, 2020). Jobs in AI maintenance, ethics, and innovation could offset losses, though the transition may be rocky for those left behind.

Important Technologies are:

- Machine Learning & Deep Learning: Algorithms that get better automatically by learning from experience.
- Natural Language Processing (NLP): Allows machines to interpret and communicate in human language.
- Robotics and Automation: Machines doing tasks that were previously done by humans.
- Computer Vision: Systems reading visual data from the world.

Implementations of these technologies have resulted in greater efficiency, cost savings, and new business models in various industries.

3. Effects of AI on Different Industries

Manufacturing and Automation

In the manufacturing industry, AI-driven automation has optimized production lines and quality inspection. Computer-controlled robotic arms may assemble items with speed and accuracy that humans cannot match. Predictive maintenance—employing AI to predict breakdowns before they happen—has minimized downtimes and saved businesses millions of dollars in operational expenses.

For example, firms in the automobile industry are implementing AI-powered robots for painting and welding activities. This mechanization not only increases the rate of production but also improves safety by reducing exposure of humans to risky situations.

Retail and Customer Service

Retailers are leveraging AI to personalize customer


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experiences. Recommendation engines analyze consumer behavior and suggest products, while chatbots and virtual assistants provide 24/7 customer support. Automated inventory management systems help maintain optimal stock levels and reduce waste.

AI has also revolutionized marketing practices. Organizations utilize data analytics to segment the customer base and provide targeted advertisement, enhancing the rate of conversions. These innovations in technology also result in a decrease in hiring for conventional roles like customer support representatives, with chatbots and AI systems taking over mundane interactions.

Healthcare

In medicine, applications of AI vary from diagnostic systems to patient care systems. AI algorithms assist in the early detection of diseases through the analysis of medical images and patient information. Personalized medicine, where therapy is customized based on a person's genetic profile, is increasingly becoming possible with AI-based data analysis.

AI-supported telemedicine platforms facilitate remote patient monitoring and lower the demand for in-person visits. Although such developments enhance care delivery, they also necessitate a reassessment of workforce roles—potentially lowering the demand for some administrative work while enhancing the demand for data scientists and technical professionals.

Financial Services

One of the first sectors to adopt AI is the financial sector. Right from detecting fraud to algorithmic trading, decision-making and efficiency in operations have been improved with AI systems. AI is utilized by banks to assess risk, automate loan approval, and enhance customer service via virtual assistants.

Nevertheless, while AI applications continue to absorb processing and analysis chores, some roles in traditional back-office jobs are being realigned. Layoffs and a changing requirement of tasks have ensued because firms have decided to put an emphasis on technical competence and evidence-based decision-making.

4. Practical Examples and Case Studies

Case Study: Automation in Manufacturing

A prominent automobile company installed AI-powered robotics to automate various phases of car assembly. The outcome was better production speed, improved quality control, and less production expense. Though the automation process resulted in reducing the demand for human intervention, it also opened up avenues for very skilled technicians to look after and maintain the newly installed AI equipment.

Case Study: AI in Customer Support and the Labor Force

In the retail industry, one of the largest multinational retailers implemented AI-driven chatbots to manage customer questions. The technology minimized response times and enhanced customer satisfaction. The implementation of the systems also led to a reduction in the number of traditional call center employees. While some were fired, the company invested in retraining initiatives to assist impacted staff in moving into new positions dedicated to managing and enhancing AI tools.

Layoffs and Organizational Restructuring

One of the more contentious effects of AI is the part it has played in workforce transformation. Several businesses across the board have utilized AI and automation as justification for cutting staff. For instance:

- Tech and Retail Giants: A few firms have rationalized operations by automating routine tasks, resulting in job losses among customer service and administrative personnel.
- Manufacturing Companies: Greater implementation of AI-driven robots has caused decreased demand for human labor in factories, leading to a loss of jobs in conventional assembly lines.

It's worth noting that while AI-led layoffs are a reality in some industries, many companies are also focusing on upskilling their workforce. The shift usually involves relocating employees from mundane tasks to positions that necessitate human ingenuity, emotional intelligence, and high-level technical skills.


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5. Ethical and Social Concerns

The elimination of jobs through AI and automation poses ethical and social issues. Some of these issues are:

- Economic Inequality and Job Displacement: When businesses downsize employees to implement automated processes, economic inequality poses a threat to widen.
- Workforce Transition and Reskilling:With the necessity of large-scale retraining initiatives, workers must shift to new jobs within the economy based on AI.
- Surveillance and Privacy: AI use in tracking employee performance or customer behavior needs to be weighed against respect for privacy and ethical considerations.
- Bias in Decision-making:AI systems can unconsciously reinforce biases if they are trained on unrepresentative data, impacting hiring practices and customer service outcomes.

Policymakers, businesses, and schools need to work together to develop frameworks that respond to these challenges and facilitate a seamless transition to an AI-powered workforce.

6. Methodology

Research Design

This study is carried out in the form of utilizing a structured questionnaire to collect data from participants and working professionals.

Sample Size and Sampling Technique

The study involved a sample of 100 respondents from three prominent colleges across Assam and India which includes both Government and Private institutions such as Dispur College, Gauhati Commerce College,NERIM Group of Institutions, Nalbari Commerce College,Assam down town University and Kolkata Bidhannagar Society for Academic Advancement,India.Participants were selected using a convenience sampling method, allowing for efficient data collection through the distribution of Google Forms. This approach was chosen for its accessibility and quick turnaround, targeting individuals who were readily available and willing to contribute. These colleges were selected based on their reputation, accessibility, and diverse student demographics, which provided a broad range of perspectives for the research.

Data Collection

Data was gathered using a self-administered questionnaire designed to capture participants' views on the usage of AI tools and how it is impacting on different industries. The questionnaire included both closed-ended questions using a Likert scale to ensure a structured and comprehensive analysis.

Data Analysis

The responses were analyzed using charts and categorized to identify key trends. The analysis focused on Artificial Intelligence and it's impact on different industries.

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7. Future Outlook and Recommendations

1. Balanced Integration of AI: AI should be used to support human workers rather than replace them, ensuring collaboration between technology and human expertise.
2. Ethical AI Development: Regulations and ethical guidelines must be established to prevent biases, discrimination, and over-reliance on AI in critical decision-making.
3. Upskilling and Job Adaptation: Organizations and educational institutions should focus on upskilling employees and students to adapt to AI-driven job roles.
4. AI in Education and Healthcare: AI should be integrated into education and healthcare under human supervision to enhance learning and medical outcomes while maintaining emotional intelligence.
5. Regulatory Oversight: Governments, policymakers, and independent ethics committees should collaborate to regulate AI usage, ensuring responsible and fair deployment across industries.

8. Conclusion

Artificial Intelligence has become a revolutionary driver in various industries. Although its adoption produces increased efficiency and innovation, it poses challenges—

especially in the form of displacement of jobs and restructuring of the workforce. Through a precise analysis of case studies and actual occurrences, this report emphasizes both the favorable influences and the ethical implications of AI. In the future, a balanced strategy that focuses on reskilling, ethical practices, and cooperative policymaking will be critical to enhancing the strengths of AI while protecting the interests of impacted workers.

AI’s impact on industries is undeniable, driving efficiency while sparking layoffs across sectors. In tech, companies like IBM, Salesforce, and Google are cutting jobs to focus on AI. In manufacturing, firms like Foxconn are automating away manual roles. In customer service, Concentrix and others are replacing reps with chatbots. These practical examples show AI’s double-edged sword: it boosts productivity but displaces workers. For companies, this means balancing innovation with responsibility—perhaps through reskilling initiatives. For policymakers, it’s about ensuring the workforce isn’t left behind. As AI evolves, its influence will grow, making it vital to address these challenges head-on.

References

1. Bloomberg. (2023 May). IBM to pause hiring for jobs AI could do.

2. Salesforce Q1 2023 Earnings Call Transcript.

3. The Verge. (2023 January). Google layoffs hit ad teams as AI takes center stage.

4. BBC. (2016 May). Foxconn replaces 60,000 workers with robots.

5. Business Wire. (2023 June). Concentrix expands AI capabilities.

6. World Economic Forum. (2020). Future of jobs report.

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