This document discusses a study that examines the positive and negative employee experiences resulting from artificial intelligence (AI) adoption in organizations operating under Industry 4.0. Semi-structured interviews were conducted with 32 professionals across nine industries. The findings identified prominent adverse impacts of AI adoption such as information security, data privacy concerns, and job insecurity. However, positive impacts were also found, including increased work flexibility and autonomy as well as enhanced job performance. Factors contributing to technostress among employees included work overload, job insecurity, and increased job complexity from technological changes. The study aims to provide insights into human resource challenges with the onset of Industry 4.0 and strategies to address them.

1. Impact of artificial intelligence on
employees working in industry 4.0
led organizations
Nishtha Malik and Shalini Nath Tripathi
Jaipuria Institute of Management, Lucknow, India
Arpan Kumar Kar
Department of Management Studies, Indian Institute of Technology Delhi,
New Delhi, India, and
Shivam Gupta
Department of Information Systems, Supply Chain and Decision Making,
NEOMA Business School, Reims, France
Abstract
Purpose – This study attempts to develop a practical understanding of the positive and negative employee
experiences due to artificial intelligence (AI) adoption and the creation of technostress. It unravels the human
resource development-related challenges with the onset of Industry 4.0.
Design/methodology/approach – Semi-structured interviews were conducted with 32 professionals with
average work experience of 7.6 years and working across nine industries, and the transcripts were analyzed
using NVivo.
Findings – The findings establish prominent adverse impacts of the adoption of AI, namely, information
security, data privacy, drastic changes resulting from digital transformations and job risk and insecurity
brewing in the employee psyche. This is followed by a hierarchy of factors comprising the positive impacts,
namely, work-related flexibility and autonomy, creativity and innovation and overall enhancement in job
performance. Further factors contributing to technostress (among employees): work overload, job insecurity
and complexity were identified.
Practical implications – The emerging knowledge economy and technological interventions are changing
the existing job profiles, hence the need for different skillsets and technological competencies. The
organizations thus need to deploy strategic manpower development measures involving up-gradation of skills
and knowledge management. Inculcating requisite skills requires well-designed training programs using
specialized tools and virtual reality (VR). In addition, employees need to be supported in their evolving socio-
technical relationships, for managing both positive and negative outcomes.
Originality/value – This research makes the unique contribution of establishing a qualitative hierarchy of
prominent factors constituting unintended consequences, positive impacts and technostress creators (among
employees) of AI deployment in organizational processes.
Keywords Artificial intelligence, Industry 4.0, Employee experiences, Technostress, Human resources
management
Paper type Research paper
1. Introduction
A major driving force for an organization’s success is a leverageable competitive advantage
in the form of its manpower resources. Organizations can leverage these human resources
optimally by combining them with their operational capabilities (Bag and Gupta, 2019). The
fourth industrial revolution (I4.0) has brought about a paradigm shift, in business processes.
It however calls for upskilling and integration of human resources with operations (Bag et al.,
2020a, b;
Skrinjari
c and Domadenik, 2019). This idea was introduced at the Hannover Fair
(2011) and thereafter it was officially recognized as a strategic initiative by Germany (2013),
symbolizing industry pioneers bringing about a revolution in the manufacturing sector. This
represents the widespread adoption of automation by the manufacturing sector and includes
AI and
industry 4.0 led
organizations
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0143-7720.htm
Received 21 March 2021
Revised 27 April 2021
19 May 2021
Accepted 19 May 2021
International Journal of Manpower
© Emerald Publishing Limited
0143-7720
DOI 10.1108/IJM-03-2021-0173

2. in its ambit enablers like the internet of Things (IoT), cyber-physical systems (CPS) and cloud
computing (Lu, 2017; Bag et al., 2020). I4.0 tends to integrate the physical world with the
virtual space by means of a machine-to-machine communication, IoT and CPS technologies.
With the advent of this revolution, systems like smart factories are emerging and Information
and Communication Technologies (ICT) constitute the foundation for innovative industries.
In the recent past I4.0 has brought forth a new technology framework integrating both intra-
and inter-organizational processes. This will cater to ever-increasing information demands of
industries and their exploring multifaceted benefits of digitizing various organizational
processes (PWC, 2016).
As artificial intelligence (AI) gains growing importance in our lives redesigning our work
places and increasingly powering things, Pew Research Center conducted a survey recently
regarding the impact of AI on society across 20 global publics. It was conducted toward the
end of 2019 and beginning of 2020 spanning 20 places across the Asia–Pacific region, the
United States, Europe, Canada, Russia and Brazil. According to this survey more than half
(53%) of the people said the deployment of AI and computer systems has had a positive
impact on society, whereas 33% said it has had a negative impact. Asians largely harbor a
positive view of AI. There were divided opinions on robotic automation of human jobs as well.
A large proportion, 48% said that job automation has been a positively inclined innovation,
whereas 42% disagreed.
Digital workspace has emerged as a new paradigm and enables employees to work both in
physical and cyberspace. It facilitates increased employee productivity. This work format
will help employees save on useless commuting, give them more flexibility, enable them to
manage work and collaborate without any time and place constraints (Koslowsky et al., 1996;
Colbert et al., 2016). Despite organizations incorporating IT for facilitating digital work,
employees prefer daily office routines (Ratti and Claudel, 2016). Thus, the transition toward
digitization requires a psychological shift of work definition from 9 to 5 in office to a no time
and space constraint view of work. The latter perspective has the objective of efficient
completion of work (Monaghan and Ayoko, 2019).
Organizations have benefitted in multifaceted ways, in terms of increased employee
productivity and efficiency (Jonker-Hoffr
en, 2020) by incorporating and implementing ICTs
(Ruiz, 2020). There has however been a flip side to these benefits. Although productivity and
efficiency have been enhanced, but the question to be asked over here is, at what cost? The
costs may not be explicit, but a no time no space constraint workplace has definitely taken its
toll and has proved to be counterproductive. Excessive inroads of ICTs into our personal time
and space may have unintended consequences, in terms of stress and social isolation
(Nakro
sien_
e et al., 2019). A clinical psychologist Brod (1984) proposed the concept of
technostress and explained it as a modern day ailment resulting from an individual’s inability
to handle ICTs in a healthy manner. Workplace stress leads to several health issues while
having an impact on quality of life (Rabenu et al., 2017). A WHO report (WHO, 2005)
propounds that employee work patterns have been altered by increased use of ICTs.
Although organizations take cognizance of health hazards prevailing at the workplace, but
not of the psychological health hazards. Certain training and other interventions are however
required to take care of the mental health of the employees.
Stress among employees may be caused due to digitization of office work using
technological interventions like AI (Korunka and Vitouch, 1999; Bag et al., 2021a, b) or
increased workload (Giovanis, 2018). It could also be a combination of both factors.
Technostress could result from an overwhelming feeling of urgency, heightened expectations
from employees and organizations rewarding very hard-working employees, who remain
connected and accountable at all points of time (Bellmann and Hubler, 2020). This stress can
have several detrimental fallouts like mental exhaustion from work, commitment issues and
turnover intentions (Moore, 2000). The importance of technostress has been further
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3. highlighted by Tarafdar et al. (2007). They have posited that this technostress may result in
reduced job satisfaction, lower commitment and productivity. There is however a need to
develop an in-depth understanding both in the aspects of stress and ICT applications like
deploying AI.
Although there have been several studies on the adoption of AI and I4.0, there still remains
a lacuna in the existing literature. Prior research has explored the positive impact of AI
adoption on human resources as well as the negative aspects in terms of the creation of
technostress among employees (Moore, 2000; Tarafdar et al., 2007). However, there exists a
perceptible gap in the in-depth practical understanding of positive and negative employee
experiences due to AI adoption and the creation of technostress.
Digitization has resulted in ubiquitous technostress in organizations, hence there is a need
to design and develop organizational interventions to combat this menace and benefit from
its beneficial aspects. As complex technological interventions continue to overwhelm
organizational human resources, it is vital to develop a detailed understanding of negative
impacts like technostress along with the positive aspects. This will not only satiate theoretical
lacunae but also address the practical managerial demands, helping them to develop
preventive measures. This is the gap that this study aims to address.
The objective is to develop deeper insights into challenges related to human development
with the onset of I4.0. These challenges confront top managements of organizations at every
step such as recruitment, training, career development and so on. Also, some innovative
human resource development strategies need to be deployed, so as to overcome these
challenges and arrive at a sustainable human resource development plan in this digital era.
Hence the research questions that the study aims to explore are:
RQ1. How does AI adoption in I4.0 firms create adverse impacts among employees?
RQ2. How does AI adoption in I4.0 firms create positive employee experiences?
RQ3. How does technological changes during AI adoption in I4.0 firms’ impact
employees?
The rest of the paper is organized as follows: the introduction is followed by a brief literature
review. Then the research process followed for the study has been discussed, which precedes
the findings and discussion section comprising thematic analysis, sentiment analysis and
word cloud analysis. Finally, we have discussed the research and the practical implications of
the study, concluding with the limitations and direction for future research
2. Literature review
The onset of I4.0 has been marked by AI and big data bringing about a paradigm shift in
economic and social spheres (Bag et al., 2018, 2021c, d; Telukdarie et al., 2018). Conceptually
AI has been decoded as the ability of a system to learn and interpret from digitized data (Elish
and Boyd, 2018). Researchers have posited that AI can enhance the intelligence of employees
by enabling them to better comprehend and overcome complex situations. It helps in
providing various alternative solutions, thus aiding and abetting in the process of taking
decisions (Bader and Kaiser, 2019). This support in arriving at decisions empowers the
employees to develop their creative skills while using machines for routine tasks. Thus global
businesses with qualified employees expect AI to provide multifaceted benefits for their
business (Hsieh and Hsieh, 2003; Liu et al., 2020).
Multiple sectors have benefitted from notable advancements in AI, robotics and
automation. The emergence of these technological interventions has touched and had an
impact on service sectors like hospitality and tourism as well (Syam and Sharma, 2018). The
hospitality sector has deployed these interventions for essential management tasks, solving
AI and
industry 4.0 led
organizations

4. daily functional challenges. There are multiple deployments (of AI) for streamlining
processes, concierge services, guest registrations, bartending, virtual voice assistance and so
on (Kuo et al., 2017; Makridakis, 2017). AI has also been successfully used for service
automation in airport management systems like traveler information desks. This technical
assistance helps take care of various mundane tasks, leaving the service providers’
employees mentally free to engage in deeply enriching customer relationships.
AI aids and enhances human performance in multiple facets of operations management.
For instance, AI can improve organizational efficiency, quality, customer satisfaction and
return on investment while empowering employees. Sun (2019) provided evidence for
utilizing AI in product inspection by means of visual recognition aided audits. It can also be
deployed for enterprise resource planning by helping managers in the process of arriving at
consumer decisions, suggesting product development and process management innovations,
and adapting human resource allocation with shifts in consumer needs (Wang et al., 2019). AI
algorithms can expedite the process of analyzing customer reviews, providing deep insight to
designers and help managers in product positioning and product development based on
design elements (Singh and Tucker, 2017).
Recommendations provided by AI algorithms are the driving force behind customer
orientation and customization. This in turn helps companies to successfully leverage
competitive advantages, enhancing customer experiences (Grover et al., 2020). Another vital
application is in the arena of effective supply chain management, which has been indicated as
a key growth input for organizations. AI aids in both coordination and sharing of information
with respect to supply chain management (Gupta et al., 2020; Bag et al., 2021c, d). The
objective of efficient supply chain operations lies in the fulfillment of customer needs (Muggy
and Stamm, 2020). Usually, these algorithms are deployed for minimizing budgeted costs like
procurement costs and effective resource utilization. Another important application of AI
algorithms in the downstream supply chain is for launching new products by gauging
customer needs and preferences (Grover et al., 2020). Although multiple uses of AI have been
suggested, the underlying assumption is that a symbiotic relationship between employees
and AI algorithms is required for its successful deployment.
There has been widespread usage of AI and big data analytics in operations management (of
various sectors). For instance, in healthcare, various online applications have enhanced efficiency
in clinical operations like scheduling of surgeries, analyzing images with the objective of
diagnosis and disease prognosis (Panch et al., 2018). The digitization and automation of
manufacturing operations, fueled by big data and machine learning, has brought about a notable
transformation and resulted in path-breaking manufacturing facilities like self-learning plants
(Dogru and Keskin, 2020). Then there is the deployment of AI in retail operations. Online
shopping equips e-retailerswith alargequantum ofdata-relatedbrowsing patterns and shopping
habits of consumers. This in turn allows them to design future promotions and product offerings
while enabling them to manage their inventory efficiently (Dogru and Keskin, 2020).
AI as a technological intervention is considered relatively superior. Recent literature
indicates that AI not only enhances creative thinking but also supports context awareness,
reasoning ability, communication ability and self-organization ability (Eriksson et al., 2020). It
is the combination of AI, big data and robotics that has initiated the fourth edition of the
industrial revolution (Grover et al., 2020). The premise behind these technological
interventions is not to replace human resources, but to function as a complementary
facilitator to augment human intelligence and knowledge (Jarrahi, 2018). There can exist a
symbiotic relationship between employees and AI deployment by providing mutual benefits.
Thus this study aims to explore an important research question, how can the adoption of AI
in I4.0 create positive employee experiences?
The ubiquitous presence of ICTs has increased the efficiency of organizations by access to
real-time data for informed decisions. However, the all-pervasive nature of ICTs has increased
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5. the employee workload, created a constant need for adaptation to new technological
interventions and excessive dependence on them. All this has resulted in technostress among
employees (Wang et al., 2008; Tarafdar et al., 2007, 2010, 2011). Several researchers have posited
a plethora of antecedents as well consequences for technostress. Some important causative
factors are information overload and excessive work overload which lead to frustrated and
demotivated employees and poor work performance (Rabenu et al., 2017; Tarafdar et al., 2007,
2010, 2011). Individual personality traits are also known to play a role in the way people
experience organizational stress and their coping mechanisms (Garg and Dhar, 2017).
Modern-day organizations’ quest to stay relevant with times has resulted in over-
dependence on technological interventions and their burning need to incorporate these in
their organizational processes. This has consequentially resulted in employees constantly
striving to adapt to these new technologies (Ragu-Nathan et al., 2008). This omnipresent and
all-pervasive incorporation of technology in all workflows has left the employees feeling
overwhelmed with the mental and psychological effort required for coping with all this
(Tarafdar et al., 2011). This cognitive response comprising of feelings of demotivation and
depression has been referred to as technostress (Ragu-Nathan et al., 2008). The term
“technostress” however was first coined by clinical psychologist Brod (1984). He described it
as a modern-day malady resulting in poor health due to the use of ICTs. This concept was
further extended by being described as stress that is caused by an employees’ inability to
handle organizational demands of computer usage (Tarafdar et al., 2007, 2010).
There may be multifarious reasons for this stress like constant connectivity, a variety of
new applications (difficult to comprehend), multitasking, information overload, high level of
uncertainty, job insecurities and technical problems (Chala et al., 2018; Coupe, 2019; Tarafdar
et al., 2010, 2011). These causal factors could be related to the organization like an individual’s
job-related demands and job control. Besides job-related factors, excessive use of technology
could also cause stress (technostress). Tarafdar et al. (2007) conducted a detailed study on
technostress and identified five factors that lead to technostress: techno-invasion, techno-
overload, techno-complexity, techno-uncertainty and techno-insecurity. Technostress has
assumed great importance in this technological era; hence, there has been widespread
research on the causal factors as well as their consequences. For instance, Shu et al. (2011)
have investigated how cognitive factors like technology dependence and belief in self-
efficiency might result in stress; while Ayyagari et al. (2011) posited that technology
attributes might lead to stress. Tarafdar et al. (2007, 2014) have explored the impact of all five
factors creating technostress on employee performance. They have further emphasized that
the negative effects of technological interventions like AI can accentuate some dysfunctional
arenas of role overload and role conflict. These findings validate that technostress and
productivity of employees are inversely related.
Tu et al. (2005) and Wang et al. (2008) posited that the techno-overload factor had a positive
impact on productivity (due to cultural differences) and centralization and innovation had an
impact on levels of technostress among employees. Yan et al. (2013) on the other hand have
used the person fit theory and posited stress evaluating a model for technology users in the
field of telemedicine and found a moderating effect of personal innovativeness. Thus, another
area of exploration that opens up for an in-depth understanding is how does AI applications
in I4.0 create technostress among employees? Further, can the adoption of AI in I4.0 create
unintended consequences and adverse impacts?
3. Research methodology
3.1 Data collection
The study uses a qualitative approach to examine the data collected from 32 working
professionals who had experience in working on I4.0 projects in multi-national firms. These
professionals were identified using purposive sampling from different academic and
AI and
industry 4.0 led
organizations

6. professional backgrounds as mentioned in Table 1 to obtain a more holistic overview of the
research questions. Out of 32, seven were females and twenty five were male respondents.
The average work experience is 7.6 years; the standard deviation for the years of work
experience is four years. The maximum work experience of the respondent is 18 years.
Interviews were taken until theoretical saturation was reached. According to Marshall et al.
(2013) and Malterud et al. (2015) in a qualitative study, the typical data saturation happens at
30. Semi-structured interviews were conducted and the respondents were asked about how
the adoption of AI in I4.0 can create unintended consequences, adverse impacts; positive
employee experiences; technological changes and technostress among employees.
3.2 Data analysis
The following process was followed to analyze the data collected (Figure 1). In the first step,
the interviews were coded into text and were converted into the transcript by collating the
responses into a single response sheet for every research question separately. In the next step,
data cleaning was done to eliminate special characters, numeric values and spaces from the
transcript. Uniformity of cases was done for these files. In the next step, stop words were
defined. Finally, these transcripts were imported into NVivo for analysis. Intercoder
reliability was established while developing the codebook for mapping responses with the
themes emerging from the interviews. Face validity was also established through a group
consensus-based approach. The team for establishing reliability and validity consisted of
four researchers, each of whom had prior research experience and had a doctorate in
management. Word cloud was generated, which is used in extracting the main content from
the analysis followed by thematic and sentiment analysis using the feature of autocode. A
mix of text mining and qualitative content analysis was utilized so that thematic convergence
was evident from the data collected in the interview transcripts.
4. Findings
The analysis of the respondents’ responses reveals three major categories that can be defined
as unintended consequences of AI adoption, positive impacts of AI deployment on employees
and technostress among employees in I4.0 (Figure 5).
4.1 Unintended consequences and adverse impacts of AI adoption in I4.0
The word cloud in Figure 2 for research question one depicts that “Changes” is the word
which is highlighted most by the respondents followed by insecurity, stress, work, change,
technology, overload, adoption, issues, create, technology, consequences and automation, etc.
These words helped in forming themes while taking help from thematic analysis.
Academic background Industry Seniority in organization
Bachelors in technology 21 Consulting 2 Senior management 6
Masters (General) 4 Mechanical 4 Middle management 13
MBA 3 Electrical 5 Business analyst 3
Graduate (General) 2 Computer Science/IT 6 Research 2
Bachelors in architecture 1 Industrial 4 CXO 2
Masters in technology 1 Construction/Mining 2 Engineering services 1
Electronics 3 Technical analyst 5
Financial services 4
Agro-based industry 2
Note(s): n 5 32
Table 1.
Profile of the
respondents
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7. 18
India
groups
were
identified
from
LinkedIn
with
more
than
10,000
members
Respondents
(who
had
posted
in
last
30
days)
were
selected
from
these
groups
for
initial
contact
18%
respondents
showed
interest
and
participated
in
the
study.
Interviews
were
conducted
telephonically
Telephonic
recordings
were
than
coded
into
text
and
were
converted
into
transcript
by
collating
the
responses
into
single
sheet
82%
did
not
participated
in
the
study
after
initial
contact
Alignment
of
responses
was
done
with
identified
themes
and
literature
Intercoder
reliability
was
established,
facce
validity
was
also
established
Stop
words
were
defined,
codebook
was
made,
etc.
Data
Cleaning
was
done
to
eliminate
special
characters,
numeric
values,
and
spaces
from
the
transcript.
Uniformity
of
cases
was
done
Selection
of
respondents
Initial
contact
Not
approached
further
Cleaning
of
data
Coding
Schedule
interview
Interested
Not
Interested
Findings
Discussion
Data
coding
Theme
development
Analysis
Figure 1.
Data collection and
analysis process
AI and
industry 4.0 led
organizations

8. On performing a sentiment analysis on the first research question, the graph in Figure 2
indicated a very negative/ moderately negative sentiment harbored by the respondents. This
is indicative of the fact that respondents believe that the onslaught of I4.0 will have certain
negative impacts on the employees and their psychological well-being.
Thematic analysis of the first research question indicated some unintended or negative
impacts of AI deployment in organizational processes in Table 2. The majority of the
responses were centered on problem areas and issues encountered by employees, integration
of organizational functions with technology results in a potential risk of data leaks and
security breaches (14%). AI in I4.0 has created unintended scientific and societal issues
spanning technology, security and privacy and standardization. In I4.0 reliable mechanisms
to account for privacy protection and security is needed. Quoted below are some instances
from the respondents’ answers:
Respondent 1: “While integrating every function of the organization with the technology there is
always a potential risk of data leaks and security breaches. Issues like data privacy, security, and
standardization are still a big concern. Learning and adapting to new systems would require time/
practice and considerable stress and anxiety is also observed in many employees.” [1.1, 1.4]
Respondent 21: “To ensure the use of new IoT technologies and services, information security and
data privacy protection are critical aspects. As we outsourced our more and more decision-making to
AI. We need to make sure that they do not produce biased decisions. We need to make sure that
decision-making in our algorithm doesn’t replicate some of the bias that we have already in our
society.” [1.1, 1.6]
90
80
70
60
50
40
30
20
10
0
Very Negative Moderately
Negative
Moderately
Positive
Very Positive
S. No. Themes Frequency Percentage
1.1 Information security and data privacy 23 14
1.2 Changes resulting in digital transformation 21 13
1.3 Job risk (job loss/role loss) 20 12
1.4 Increased stress and overload 18 11
1.5 Managing changes 16 10
1.6 Biases in decision making 12 8
1.7 Misinformation management 6 4
Note(s): Only themes having a frequency of more than two were included
Figure 2.
Word cloud and
sentiment analysis
based on research
question 1
Table 2.
Themes identified for
research question
1 (RQ1)
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9. Thereafter, the next theme was drastic changes resulting from digital transformations (13%).
The learning curve for employees has become rather steep – with the adoption of AI,
employees are under tremendous pressure to keep up the pace with the constantly evolving
technological ecosystem in Industry4.0. Then there is the issue of complexity – the AI system
lacks the capabilities to handle situations that are not documented. Thus, it may not be able to
handle novel situations and human intervention may be required. Quoted below are some
instances from the respondents’ answers:
Respondent 12: “If the employees feel that due to greater automation of tasks with AI implementation
they will get replaced, Adoption of AI can result in a feeling of depression, stress, difficulty in
managing change, and disgust. This may impact employees’ performance adversely because
employee acceptance behavior plays a significant role in productivity change from digital
transformation.” [1.7, 1.2, 1.4, 1.5]
Respondent 18: For manufacturing firms, the prevailing infrastructures are not ready completely to
assist in digital transformation aiming at horizontal, vertical, and end-to-end integration.
Management of misinformation is another challenge. [1.2, 1.4]
Another theme that emerged was job risk and insecurity brewing in the employee psyche
(12%). As the adoption of AI systems increases in industries, technologies like the “Robotics
Automation Process” automate the repetitive, mundane job and requires less human
intervention hence fewer jobs. Employee job fit, if the employees feel that due to greater
automation of tasks with AI implementation they will be replaced, it can result in a feeling of
depression and demotivation. This may affect employees’ performance adversely, whilst it is
believed that employee acceptance behavior plays a pivotal role in enhanced productivity
from digital change. Quoted below are some instances from the respondents’ answers:
Respondent 29: Work overload, invasion of privacy, digital change, work-family conflict, dynamism,
substantiality affect the psychological safety of the employees which further add to technostress.
[1.4, 1.3, 1.2]
Respondent 4: This stress stems from situational factors, strain, and outcomes. The adaption of
technology happens much quicker for digital natives whereas aligning the digital immigrants poses
a challenge. Employees feel insecure at their workplace. [1.3, 1.4, 1.5]
These findings are in sync with extant literature and extend the boundaries of knowledge as
well. Researchers have opined that technological interventions like AI have increased the
workload of employees and put them under psychological pressure of the constant need to
adapt (Wang et al., 2008; Tarafdar et al., 2010, 2011; Turel et al., 2011). In addition, some
important causative factors for these negative impacts are information overload and
excessive work overload which lead to frustrated and demotivated employees and poor work
performance (Ragu-Nathan et al., 2008; Tarafdar et al., 2007, 2010, 2011). The ubiquitous
presence of technology has left the employees feeling overwhelmed with the mental and
psychological effort required for coping with all this (Tarafdar et al., 2011).
4.2 AI adoption and positive employee experiences in I4.0
The word cloud in Figure 3 depicts that creativity is highlighted and mentioned more by the
respondents followed by employees, innovation, flexibility, performance, learning,
management, information, experience, productivity, better, etc. The sentiment analysis of
this research question reveals moderately positive and very positive sentiments by the
respondents. This indicates that the respondents agree that technology interventions in
organizational processes will also lead to certain positive impacts.
The thematic analysis revealed eight main defined themes as shown in Table 3. The most
prominent ones being that AI provides employees more flexibility and work-related
AI and
industry 4.0 led
organizations

10. autonomy by functioning as a complementary facilitator (21%). The employees save
commuting time, can work from home and beyond office hours working and delivering
results at their own pace without any geographical constraints. AI in I4.0 will integrate
physical infrastructure with digital communication technologies. This will enable employees
to use these to work remotely without being present in the office. This would help in a more
flexible and diverse career path allowing employees to decide when (and where) the work
might occur while remaining more productive for a longer period. The introduction of I4.0 has
revolutionized the workplace and has been widely acknowledged for improving employees’
productivity along with providing more flexibility and autonomy to manage their tasks and
work irrespective of time and place. Quoted below are some instances from the respondents’
answers:
Respondent 3: “This would help in a more flexible, transparent and diverse career path allowing
employees to decide when (and where) the work might occur while remaining more productive on a
longer-term in I4.0.” [2.1, 2.3]
Respondent 7: AI 4.0 promotes flexibility in work by making the employees use digital resources
when they manage their tasks and collaborate—irrespective of time and place. This promotes work-
life balance, higher job satisfaction, better decision making, and loyalty.”[2.1, 2.4, 2.5]
Thereafter, Creativity and Innovation emerged as a prominent theme (17%) since AI
enhances employees’ talent by increasing their job learnings, allowing them to indulge in
creativity and innovation in management processes and functions by freeing their time from
mundane tasks. With the adoption of AI in I4.0 and its integration of computing abilities,
90
80
70
60
50
40
30
20
10
0
Very Negative Moderately
Negative
Moderately
Positive
Very Positive
S. No. Responses Frequency Percentage
2.1 Flexibility and autonomy 30 21
2.2 Creativity and innovation 24 17
2.3 Transparency of information 13 9
2.4 Enhanced decision making 10 7
2.5 Better work-life balance 9 6
2.6 Collaboration and career progression 8 6
Note(s): Only themes having a frequency of more than two were included
Figure 3.
Word cloud and
sentiment analysis
based on research
question 2
Table 3.
Responses for research
question 2 (RQ2)
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11. there will be an increase in the inputs of employee’s decision making by increase of
intelligence, abundance of information and AI’s ease of providing diverse solutions. Real-time
data provided by AI can facilitate prediction of the future and faster judgment by employees.
This tends to increase their scope of creative thinking. Quoted below are some instances from
the respondents’ answers:
Respondent 23: “AI can act as an efficient tool to facilitate transparent decision making for employee
rewards and recognition, thereby reducing the probability of individual preferences and choice. This
would also increase their scope of creative thinking.” [2.2, 2.4, 2.3]
AI deployment also streamlines and facilitates organizational processes thereby increasing
transparency in information flow (9%). This results in improved job performance by aiding
more informed decision making (7%). Organizations by adopting 4.0 automate the mundane,
repetitive tasks through technologies like “Robotics Automation Process”, this frees up mind
space for focus on innovation, creativity and more customer interaction such as applying
Design Thinking. AI has allowed the employees to do smart work making it very easier for
the employees to meet deadlines. Usage of AI along with human intelligence can improve
performance exponentially. AI is complementing human productivity and contrary to normal
perception, not posing any threats. AI adoption also embeds confidence in the employees’ that
they will be able to meet the organization’s performance expectation, i.e. job-fit. Quoted below
are some instances from the respondents’ answers:
Respondent 17: “When an employee uses AI there is transparency of Information. Employees benefit
too as not having to commute means they’ll have more free time, a better work-life balance and
greater flexibility leading to overall employee satisfaction, more collaborations, career progression
and commitment.” [2.3, 2.6]
These findings are in line with findings by Jarrahi (2018) and Bader and Kaiser (2019),
wherein they have claimed that AI enhances employee intelligence by functioning as an
enabler in the decision-making process. In addition, Jarrahi (2018) has posited that AI
deployment enhances the creative skills of employees. Researchers have also vouched for AI
interventions helping in essential management tasks, solving functional challenges and
streamlining processes (Syam and Sharma, 2018; Makridakis, 2017; Kuo et al., 2017).
4.3 Impact of technological changes and technostress among employees in I4.0
Word cloud in Figure 4 depicts that “employees” is the most frequent word used in the
responses followed by technostress, technology, stress, work and change, etc. The sentiment
analysis indicated a moderately negative/very negative sentiment harbored by the
respondents. This leads us to believe that AI deployment in I4.0 is creating technostress
among employees.
The thematic analysis of the third question revealed some definitive themes related to
technostress creation among employees. The themes can be categorized as work overload
(14%). This implies that increased expectation of productivity has led to prolonged working
hours and faster turnaround time thereby increasing workloads. IT AI systems can
increase employee productivity to a certain level, and after that, they only cause technical
overload and technostress. Such systems can drive employees to work nonstop, leaving no
leisure time meant for rest, family and other tasks. Quoted below are some instances from the
respondents’ answers:
Respondent 11: “Work overload, role ambiguity, invasion of privacy, work-home conflict, dynamism,
and job insecurity substantiality affect psychological safety of the employees which further add to
technostress. Another factor is lack of face to face interactions might lead to communication gap in
certain cases which is a major stress for the employees.” [3.1, 3.6, 3.4, 3.2]
AI and
industry 4.0 led
organizations

12. Respondent 30: Many AI related applications are too complex to understand for many employees. IT
AI systems can increase employee productivity to a certain level, and after that, they only cause
technical overload and technostress. Such systems can drive employees to work nonstop, even in the
time that is meant for rest, family, and other tasks.” [3.1, 3.3]
Another dominant theme was job insecurity (12%), which is pertaining to a situation where
workforce feel helpless and are always concerned about losing their jobs to those who are
more amenable to technology interventions. The users of ICT feel endangered by being
replaced by technology or more savvy people. Technostress stems from stressors, situational
factors and strain. The adoption of technology is easier for digital natives, whereas aligning
the digital immigrants poses a challenge. Most of the workforce members are traditional and
are not compatible with new technologies and are therefore very critical of the latest
90
80
70
60
50
40
30
20
10
0
Very Negative Moderately
Negative
Moderately
Positive
Very Positive
Positive impacts
on employees
Adoption of AI
In Industry 4.0
Firms
Unintended
consequences and
adverse impacts on
employees
1.1 Information Security and Data Privacy
1.2 changes resulting in Digital transformation
1.3 Job risk (job loss/role loss)
1.4 Increased stress and overload
1.5 Managing changes
1.6 Biases in decision making
1.7 Misinformation management
2.1 Flexibility and autonomy
2.2 Creativity and innovation
2.3 Transparency of information
2.4 Enhanced decision making
2.5 Better work life balance
2.6 Collaboration and career progression
3.1 Work overload
3.2 Job insecurity
3.3 Job complexity
3.4 Invasion in personal life
3.5 Uncertainty
3.6 Role ambiguity
3.7 Digital overdependence
Impacts of
technological
changes
Figure 4.
Word cloud and
sentiment analysis
based on research
question 3
Figure 5.
Conceptual model for
estimation of impact of
AI on employees in I4.0
IJM

13. developments. There might be insecurity brewing in the minds of such employees. In
addition, the availability of a plethora of AI-based communication systems instead of the
traditional intranet has perplexed some employees. This is where reverse mentoring becomes
relevant which leads to an additional workload and involves a steeper learning curve for the
digital immigrants. Quoted below are some instances from the respondents’ answers:
Respondent 15: “Situation where people feels threatened about losing their jobs to other people who
have a better understanding of new technology. There might be insecurity budding in the minds of
employees with high digital overdependence.” [3.2, 3.5, 3.7]
Respondent 25: “AI intervention in I4.0 has changed the way of communication and it has brought
invasion in personal life and digital overdependence. It has reduced the human social interaction
among the employees of the organization.” [3.2, 3.4, 3.7]
Thereafter complexity (12%) in Table 4 also emerged as a theme. Many AI-related
applications are too complex to understand for many employees. Some new applications
rolled out may not see a desired/intended result. Users may try to work much longer hours
with the new AI application for understanding the complexities. This leads to information
overload and technostress which in turn leads to lower job satisfaction. Also, users of ICT
believe that they are not skilled enough because of the complexity involved in the use of
technology. As a result, they are required to spend time and money studying different facets
of technology and understanding them.
AI 4.0 requires employees to upskill themselves with the latest, state-of-the-art technology.
They need to understand new systems and figure out their very own use cases. Quoted below
are some instances from the respondents’ answers:
Respondent 20: “Employees are always exposed to a lot of work and uncertainty where working
hours are extended and remain connected with the same task and it is impossible to cut away.
Employees tend to miss their social commitments due to omnipresence of workplace.” [3.3, 3.1, 3.5]
Drawing from past literature, researchers have posited that the onslaught of I4.0 has not only
increased employee workload but also created a constant need for adaptation to new
technological interventions and excessive dependence on them. This has consequentially led
to technostress among employees (Wang et al., 2008; Tarafdar et al., 2010, 2011; Bulgurcu
et al., 2010; Turel et al., 2011). Several antecedents of technostress have been cited in literature.
Some of them are information overload and excessive work overload which lead to frustrated
and demotivated employees and poor work performance (Tarafdar et al., 2007, 2010, 2011,
2014; Ragu-Nathan et al., 2008). Further Tarafdar et al. (2007) conducted a detailed study on
technostress and identified five factors that lead to technostress: techno-invasion (refers to an
invasion into privacy and personal life by all-pervasive technology interventions and the
employee can be reached anywhere and anytime), techno-overload (use of technology forces
people to work more and faster), techno-complexity (complex computer systems are difficult
S. No. Responses Frequency Percentage
3.1 Work overload 21 14
3.2 Job insecurity 19 12
3.3 Job complexity 18 12
3.4 Invasion in personal life 12 8
3.5 Uncertainty 10 6
3.6 Role ambiguity 8 4
3.7 Digital overdependence 7 4
Note(s): Only themes having a frequency of more than two were included
Table 4.
Responses for research
question 3 (RQ3)
AI and
industry 4.0 led
organizations

14. to understand, hence understanding and learning requires a lot of effort by the employees,
leading to stress), techno-uncertainty (short life cycles of computer systems require
employees to constantly upgrade and re-learn) and techno-insecurity(employees feel
threatened about losing their jobs to more technically savvy counterparts).
5. Discussion
The current study makes some noteworthy contributions that have implications in the arenas
of both research and practice. While the discussion on the findings is already integrated with
the specific findings, we highlight in this section, areas where we extend the existing
boundaries of knowledge and the implications of our findings.
5.1 Research implications
Firstly, there are several studies in extant literature that have dealt with various aspects of
organizational stress. Prior researchers have identified a plethora of job-related stress
creators, which tend to have negative outcomes like excessive strain, reduced productivity
and overall professional dissatisfaction (Ragu-Nathan et al., 2008; Tarafdar et al., 2010). There
are however divergent views on stress. On one hand, researchers have explained stress as a
natural consequence of living and an impact of various external influences; while on the other
Selye (1964, 1987) differentiated between distress (bad stress) and eustress (good stress).
Researchers have further elaborated that bad stress has negative job-related outcomes, while
good stress can result in enhanced productivity and positive outcomes (Code and Langan-
Fox, 2001; Edwards and Cooper, 1988; Selye, 1987). The current study has performed an in-
depth analysis of the unintended consequences of AI deployment in organizational processes.
This research makes the unique contribution of establishing a qualitative hierarchy of
prominent factors constituting unintended consequences and adverse impacts of
incorporation of AI in I4.0. The findings revealed the following factors: potential risk of
data leaks and security breaches, drastic changes resulting from digital transformations and
job risk and insecurity brewing in the employee psyche. Further research can be carried out in
this direction to reveal whether these factors are causing only negative impacts or on further
probing, they can have certain positive job outcomes as well. It is possible that the adverse
impact elements when viewed in the long-term perspective can have some positive outcomes
on the employee psyche as well as their job-related performance. The IT or digital resources
have a three-pronged impact in terms of digital infrastructure, technical skills acquired by
employees and enhanced knowledge, better customer orientation and synergistic benefits. All
these resources can drive innovation in organizations (Bharadwaj, 2000). However, I4.0 has
changed the very premise of doing business, which in turn calls for a different path to be
traveled for managing human resources (Whysall et al., 2019).
Secondly, this research study attempts to comprehend in detail the positive impacts of AI
deployment in organizational work processes. The study proposes a hierarchy of factors
comprising the positive impacts. These factors are work-related flexibility and autonomy,
creativity and innovation and overall enhancement in job performance. Prior research has
indicated that AI-based technological intervention is considered relatively superior. It not
only enhances creative thinking but also supports context awareness, reasoning ability,
communication ability and self-organization ability (Eriksson et al., 2020). It is the
combination of AI, big data and robotics which has initiated the fourth edition of the
industrial revolution (Grover et al., 2020). The premise behind this deployment is not to
replace human resources, but to function as a complementary facilitator to augment human
intelligence and knowledge (Jarrahi, 2018). Human resource development has emerged as a
vital research area in I4.0. Although most manufacturing firms have failed to fully take
advantage of the opportunities presented by the digital era and the accompanying human
IJM

15. resource challenges (Calabrese et al., 2020). Firms that have adopted these technologies have
displayed enhanced productivity even in small enterprises (B€
uchi et al., 2020). Future
research can attempt to empirically validate these factors in creating a positive impact on job
performance as well as test their moderating or mediating impact. I4.0 calls for a dynamic
systems approach, in terms of further development and advancement of the talent
management theory and practice (Whysall et al., 2019).
Thirdly, the current study after performing a detailed analysis of the impact of AI usage in
creating technostress (among employees) also gave a hierarchy of factors for the same. These
factors are work overload, job insecurity and complexity. Prior research on technostress has
revealed both positive and negative impacts. Several antecedents of technostress have been
cited in the literature. Some of them are information overload and excessive work overload
which lead to frustrated and demotivated employees and poor work performance (Tarafdar
et al., 2007, 2010, 2011, 2014; Ragu-Nathan et al., 2008; Ayyagari et al., 2011). Automation has
inculcated a fear of the unknown as well as loss of jobs among employees. Organizations must
address these insecurity issues, by a gradual and phase-wise adoption of digital interventions,
while upskilling and training the employees (Nam, 2019). Taking into cognizance the
importance of human capital, future researchcan investigate theimpactofdifferent contexts on
the consequences of technostress. For instance, organizational interventions and social support
may help mitigate the negative outcomes of technostress.
5.2 Practical implications
Firstly, an organization’s digitization process is affected by its age and size. Thus, technological
interventions like AI need to be implemented at a different pace in startup firms since they
possess a greater entrepreneurial spirit with a flatter organizational structure in comparison to
traditional organizations. The traditional organizational structure will need to have a step-wise
diffusion of technological interventions with a gradual blending and transition of various
workflow processes. The human resource aspect of an organization is being driven by the
emerging knowledge economy and technological interventions. These changes are the driving
force for the evolution of the human resource element of a firm (Evans, 2019). The job profiles
are changing, hence the need for different skillsets and technological competencies.
Secondly, HR mangers need to focus their efforts on integration of various emerging
technologies with the proposed utilitarian benefits supposed to accrue from them. By
achieving this integration, I4.0 will be able to achieve the true potential of the technological
evolution for accomplishing marked improvement in complex organizational ecosystems.
The emerging requisite technical skills are expertise in big data analytics, programming,
robotics and so on. The requisite soft skills include critical thinking, continuous learning and
innovation (Jerman et al., 2020). Hence, the organization needs to implement strategic
manpower development measures deploying dynamic capabilities involving up-gradation of
skills and knowledge management (Garavan et al., 2016). This digitization necessitates
innovative management practices. The skill, knowledge and performance gaps can be
bridged by designing meaningful training programs using tools like ADDIE (Li, 2016). The IS
managers can share the potential benefits and complementary facilitation with the employees
for a smoother transition into I4.0. The organization can also design various interventions for
identifying, managing and preventing technostress. For instance, certain modifications could
be introduced in job-related demands, and then certain customized strategies could be used
for individuals experiencing excessive stress. In addition, certain therapeutic treatments
could be recommended as a preventive measure for the onset of technostress.
Thirdly, organizations can implement AI-based decision making either in a sequential or
an aggregated manner. AI adoption and deployment is driven by employees’ attitude
(towards technology) and the infrastructure of the firm (Berlak et al., 2020). Another factor
having an impact is the level of intelligence and education of employees (Morikawa, 2017).
AI and
industry 4.0 led
organizations

16. The organization has to deploy a sequential AI implementation procedure by first selecting
data sources, followed by algorithms and finally the training and deployment. The immense
potential of virtual reality can also be explored for value-added training programs for
existing and new manpower resources (Khandelwal and Upadhyay, 2019). With the
unlocking of the digital potential, I4.0 has affected the work styles and life of organizational
human resources. Hence, employees need to understand in order to support them in the
evolving socio-technical organizational relationships. This will result in improved work
performance. The success of AI driven systems lies in the symbiotic relationship between
employees and AI machines (Grover et al., 2020; Jarrahi, 2018).
6. Conclusion
There exists an evolving and reciprocal relationship between technology interventions and
organizational HR elements and their roles. These relationships can be lucidly explained by
such in-depth qualitative studies. Through this exploratory study, we explore the impacts of
AI adoption within I4.0 firms, specifically focusing on the employees. Prominent adverse
impacts of the adoption of AI like the potential risk of data security breaches, drastic
organizational changes resulting from digital transformations and job risk and insecurity
often trouble the employees. Concerns surrounding biases in decision making and
misinformation-related challenges were also highlighted. The negative impacts accentuate
some dysfunctional organizational aspects. This study contributes to the technostress
literature and opens up avenues for future research.
However, positive impacts like work-related flexibility and autonomy, creativity and
innovation, and overall enhancement in job performance are also identified. Further factors
contributing to technostress among employees including work overload, disruption of work-
life balance, job insecurity and complexity were also identified. Such a study provides a
comprehensive understanding adding to the considerable existing literature on technology
deployment and interplay of organizational roles and structure. The study is one of its kinds
to focus on the adverse outcomes of AI adoption while focusing on employees of firms
undertaking I4.0 projects and digital transformation.
The bottom line is that findings of this study provide valuable developmental information
for managers in the human resource domain, challenged by digitization issues. It calls for
multifaceted organizational support in the form of developing soft skills such as
communication skills (helps achieve clarity in communication), problem-solving skills (helps
take initiatives and arrive at appropriate solutions), team building and team work skills (helps
in role definitions and collaborative work), learning skills (helps in always having a learning
attitude), analytical thinking skills (helps information comprehension and evaluation and
sound decision making), conflict resolution skills (helps in peaceful resolution of conflicting
situations), time management skills (helps in enhancing efficiency and effectiveness), creative
thinking skills (helps in devising new ways and means to complete tasks), interpersonal skills
(helps in interaction with people) and leadership skills (helps in motivation and inspiring people
to work for a common cause). All these soft skills are essential life savers in a technology-driven
world and help employees to withstand technostress and maintain their physical as well as
psychological wellbeing (Duke et al., 2009; Li et al., 2019).
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Corresponding author
Shivam Gupta can be contacted at: shivam.gupta@neoma-bs.fr
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