Artificial Intelligence and Employee Motivation: 
A Desk-based Empirical Review

Evelyne Ngari; Rosemarie Wanyoike

doi:doi:10.11648/j.jhrm.20261401.18

Research Article |

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Artificial Intelligence and Employee Motivation: A Desk-based Empirical Review

Evelyne Ngari

, Rosemarie Wanyoike^*

Published in Journal of Human Resource Management (Volume 14, Issue 1)

Received: 19 January 2026 Accepted: 27 January 2026 Published: 9 February 2026

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Abstract

Artificial Intelligence, commonly referred to in abbreviation as ‘AI’, is rapidly gaining popularity in the workplace today. The use of AI may be a source of motivation to the employees, or lack of it for various reasons. This empirical study sought to find out how Artificial Intelligence (AI) influences employee motivation at the workplace. Through analysis of various journals, this desk review examined system accuracy, task automation and trust in AI and how these affect employee motivation as the independent variables in the study. To explain motivation as influenced by AI, this review considered enjoyment of work, work involvement and goal achievement as the indicators for motivation which were the independent variables for the study. The Unified Theory of Acceptance and Use of Technology (UTAUT) and the Hertzberg Two Factor Theory were used to explain the variables in the study. The desk review revealed that even though there are positive benefits derived from the use of AI, there are a number of issues that have been left unfulfilled by the adoption of the systems at the workplace, some which affect employee motivation. Finally, the review made several recommendations for practice and future research in the area of AI with relation of employee motivation based on the research gaps identified.

Published in	Journal of Human Resource Management (Volume 14, Issue 1)
DOI	10.11648/j.jhrm.20261401.18
Page(s)	75-81
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2026. Published by Science Publishing Group

Keywords

Employee Motivation, Artificial Intelligence, Employee Wellbeing

1. Introduction

Today, the digital landscape is evolving and Artificial Intelligence (AI) has proven to be transformational in giving a new touch and feel in the modern work place across the world. According to

[20]

, Artificial Intelligence is the simulation of human intelligence in machines that are normally programmed to learn, think and make decisions just like human beings do. With the shift from repetitive processes, to automation which enables data-driven decision making, AI technologies have integrated highly into organizations’ internal processes including the Human Resource processes.

In Organizations, AI systems include predictive analytics, virtual assistants and intelligent automation tools that enhance efficiency and decision making. AI technologies are increasingly integrated into organizational processes across industries

[2, 3]

. Companies continue to enjoy the results of adopting intelligent systems such as high productivity, efficiency among others, to encompass factors such as employee motivation

[6]

. Additionally, some employees consider AI as a tool to simplify work, enhance creativity and foster engagement while others view AI as a source of job insecurity, lower autonomy levels as well as reduced human connection in the processes

[8, 10]

. This review explores the influence of AI on employee motivation, while appreciating the fact that technological change can evoke both positive and negative motivation. The focus is on key dimensions of AI adoption which are system accuracy, task automation and trust in AI while considering how they influence employee motivation. To explain motivation in this context, this study considers intrinsic and extrinsic motivational factors which include enjoyment of the work, involvement at work and goal achievement

[5, 14]

By examining this interrelationship, this desk review seeks to provide insights that are of value and how organizations can strategically utilize AI for sustained motivated, adaptive and future ready workforce while ensuring efficiency.

1.1. Problem Statement

While AI-driven systems enhance efficiency, accuracy, and decision-making, they also introduce new complexities in understanding employee motivation. Despite the perceived organizational benefits of AI, there remains limited empirical understanding of whether these technologies foster or diminish employee motivation

[2]

. The extent to which system accuracy, automation effectiveness and trust in AI influence intrinsic and extrinsic motivation remains underexplored

[13, 18]

There is rapid transformation of AI that is shaping the global workplaces in which Kenya is part. As organizations across different sectors in Kenya embrace digital transformation, AI is increasingly being integrated into core functions such as operations, finance, customer service, and human resource management. In Kenya, both public and private institutions are rapidly adopting intelligent systems to enhance productivity, streamline decision-making, and improve service delivery in line with the Vision 2030 and Digital Economy Blueprint

[16]

. While the adoption of AI promises efficiency and innovation, the impact on employee motivation in Kenya is insufficiently explored. Existing literature suggests that while some employees perceive AI as a supportive tool that simplifies tasks, fosters creativity, and enhances engagement, others associate it with job insecurity, reduced autonomy, and weakened interpersonal connection creating the need to understand which side takes more prominence

[8]

In addition, there are contrasting perceptions where technological adoption coexists with varying levels of digital literacy, organizational preparedness, and socio-economic disparities

[17]

. Furthermore, the role of AI system accuracy and transparency, automation effectiveness, trust in AI, and organizational readiness in shaping employee motivation, particularly in relation to intrinsic factors such as enjoyment of work and work involvement, and extrinsic factors such as goal achievement remains largely unexamined

[13, 18]

. Researchers such as Haenlein et al. (2019) did not investigate how trust is developed at the employee level or how this trust can influence motivation, engagement, or attitudes toward AI notwithstanding the authors stress on the importance of trust in AI systems

[7]

This gap presents a critical problem for organizations seeking to remain competitive, through the balance of technological advancement with human engagement while maintaining a motivated workforce. Without a clear understanding of how AI adoption affects employee motivation, organizations risk either over-relying on automation at the expense of employee morale and enjoyment of work or underutilizing technology that could enhance motivation and ultimately, their performance. Organizations risk misaligning technology strategies with human capital goals.

Therefore, this review seeks to examine the problem of whether and how Artificial Intelligence motivates employees in Kenyan organizations.

1.2. Objectives of the Study

1.2.1. General Objective

The objective of this review is to examine the influence of Artificial Intelligence (AI) on employee motivation.

1.2.2. Specific Objectives

To examine how AI system accuracy influence employee motivation.

To assess how task automation affects employee motivation.

To explore the role of trust in AI in employee motivation.

1.3. Conceptual Framework

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Figure 1. Conceptual Framework.

The conceptual framework indicates that the AI systems accuracy, task automation and trust in AI may affect the employee motivation as the independent variables in the study. These variables may affect employee motivation which is the dependent variable, characterised by enjoyment of the work, involvement in doing the work and the achievement of goals at work.

2. Literature Review

2.1. Theoretical Review

The Unified Theory of Acceptance and Use of Technology (UTAUT) Venkatesh, Morris, Davis, & Davis (2003) combines elements from earlier technology models, to explain how people adopt to technology. UTAUT identifies performance expectancy, effort expectance, social influence and facilitating conditions as the key factors that determine this adoption

[4, 6]

. The theory provides an explanation of how AI could influence employee motivation. When applied on AI activated workplaces, the UTAUT explains why employees could feel motivated or demotivated by the systems.

According to Dwivedi et al., (2021), the UTAUT theory, performance expectancy is explained as the extent to which employees believe that use of technology will improve their job performance

[6]

. Accuracy in the AI systems enhance perceived competence, which is a key indicator of intrinsic motivation.

Similarly, AI-driven automation of routine and repetitive tasks lowers cognitive and physical workload and employees can redirect their efforts to solving problems, enhance creativity and make strategic decisions. According to this theory, automation creates autonomy and improves work meaningfulness which is an intrinsic motivator. UTAUT proves that AI motivates employees by being accurate. When the AI systems are accurate, they correctly and appropriately automate tasks which further enhance performance expectancy and ultimately motivate the employees

[4, 6]

The Herzberg’s two-factory Theory Herzberg, (1959) has been used to explain employee motivation in the two categories which are hygiene factors and motivators

[9]

. This theory explains that when companies introduce AI in the workplace, the employees responses can be explained through the hygiene factors or the motivators. The Hygiene factors create dissatisfaction which brings about one perspective of AI which is negative. These include lack of job security and fear of replacement, which are hygiene issues. They do not motivate the staff and instead may lead to dissatisfaction 9]. Automation which is AI driven can create anxiety and lower morale if employees fear being replaced

[6]

Similarly, when the AI systems are used as surveillance tools to track productivity and behaviour of staff, they may have a feeling of over-control. This indicates a violation of hygiene and may lead to dissatisfaction among the employees but not motivation

[11]

. On the other hand, AI motivates employees when it enhances intrinsic motivators such as achievement, autonomy, recognition, and opportunities for growth

[9]

Evidence shows that AI tools that augment human capabilities improve task mastery and learning, thereby strengthening employee motivation and performance

[6, 8]

2.2. Empirical Review

Existing empirical studies reflect mixed outcomes. According to Jia, J., Ning, X., & Liu, W., (2025), application of the artificial intelligence in organizations comes with many opportunities and challenges for the employees

[12, 15]

. For instance, in a series of four studies which involved more than 3,500 participants, the researchers explored what happened when humans and AI collaborate on performing tasks. The participants completed real tasks and assessment was carried out on their sense of control, intrinsic motivation and levels of boredom. The findings of this study revealed two contrasting outcomes.

First, performance was boosted immediately, AI enhanced the quality, tone and efficiency in task completion. The results indicate that AI can substantially compliment employees’ productivity through polished, engaging and well-structured communication

[23]

. On the other hand and in contrast, the study identified psychological costs. This is where, when the participants took on an unaided task, they revealed reduced intrinsic motivation and increased boredom. The study indicated that participants who performed similar tasks without AI support maintained a stable psychological state throughout. The findings indicate that although AI can increase productivity and satisfaction, it may also diminish users’ level of engagement and autonomy when they engage in tasks that are not AI supported

[23]

Accurate, transparent, and explainable AI systems contribute to the trust, acceptance and motivation during digital transformation projects. Accuracy and transparency enable the employees to understand how and why AI systems make certain decisions which reduces uncertainty and perceptions of loss of control. When the decision logic is clear and accurate, employees are likely to view the system as fair, predictable and aligned with Organization goals, which builds both confidence and willingness to collaborate with AI tools

[6]

Tortorella et al. (2024) noted that the introduction of artificial intelligence (AI) is not only transforming task execution but also reshaping how employees interact with their work.

[21]

. AI’s ability to perform tasks autonomously may trigger worries about job displacement and increased feelings of insecurity among employees

[22]

. These concerns have been highlighted in real-world scenarios such as the use of virtual news anchors replacing human broadcasters. Conversely, AI can function as a supportive collaborator by handling monotonous and repetitive activities, thereby easing employees’ physical and cognitive burdens

[22]

. This support enables employees to enhance their capabilities and engage in more creative and meaningful work

[19]

According to Huang & Rust (2021), automation can get rid of routine tasks which increases enjoyment and creativity for the job

[11]

. The earlier works of Huang & Rust on AI agrees that there is a threat of job loss and possible displacement. While the authors site automation as a benefit to the employees and performance in general, the authors did not address the issues on job insecurity, fear of replacement, technostress and overload and perceived loss of autonomy and control in 2021. According to Asliyah, T. D. L. et al., (2024), AI technology has become more important to be used as human assistance, where enhanced workforce's capability, streamlined operational processes, overall productivity, and decision-making processes are improved

[1]

. On the other hand, excessive automation may reduce the sense of purpose and task identity. A balance between the automation and human activity my enhance intrinsic employee motivation

[1]

A study by Asliyah, T. D. L. et al., (2024) revealed that employee workloads are improved, including enhanced cognitive performance and job satisfaction by the integration of AI systems

[1]

. However, the review also noted that AI could increase employees' stress levels due to the job automation and reduced human interaction, which takes it into concern regarding its long-term impact on employee well-being

[22]

Additionally, trust of a system by employees contributes to work motivation. When employees perceive AI as a supportive and reliable, this enhanced autonomy and decision making, which in turn is likely to engage meaningfully and will sustain motivation among employees

[7]

. However, in their study, Haenlein, Kaplan, Tan, Tan, & Zhang (2019 did not investigate how trust develops at the employee level or how this has influence on motivation, engagement, or attitudes toward AI

[7].

Instead, they stuck to conceptual and organizational analysis which did not indicate the employees’ psychological responses to adoption of AI.

According to Haenlein, Kaplan, Tan, Tan, & Zhang (2019), cultivating trust in AI systems is essential for fostering a positive employee attitude towards technological change and realizing the motivational benefits of both human and AI collaboration

[7]

. AI tools or systems which may make communication easy, enhance collaboration, provide real-time feedback contribute to enjoyment and work flow, increases both engagement and employee satisfaction

[2]

Work involvement explains staff motivation through the integration of AI into Organizational processes. Involvement in the job explains how AI influences employee motivation as it enhances perceptions of autonomy, competence and task significance. When AI systems automate repetitive and routine tasks, employees are freed to focus on more analytical, creative, and intellectually stimulating work, which fosters deeper engagement and intrinsic satisfaction

[7]

. The result of this is that work becomes more meaningful and self-rewarding, which in turn promotes sustained intrinsic motivation and improved productivity

[22]

Walusiak-Skorupa, Kaczmarek, and Wiszniewska (2023) studied the impact of artificial intelligence (AI) on employee health, well-being and stress due to technology, as well as feelings of anxiety about losing a job

[22]

. Their study concluded that AI adoption may trigger stress and job insecurity, which can weaken motivation.

In Kenya, organizations, including financial institutions, county governments, and corporations, are investing in digital literacy and AI-related training. These capacity-building efforts strengthen employees’ sense of competence and create pathways for career advancement, which are key motivators in a rapidly evolving labor market

[17]

When organizations adopt AI with a human-centered approach which is grounded in trust, transparency, training, and job redesign, employees experience greater autonomy, competence, and engagement. Conversely, when AI is introduced without adequate preparation or sensitivity to employee concerns, the result is fear, resistance, and diminished motivation. Thus, the future of AI-driven work in Kenya hinges on balancing technological advancement with the psychological and professional needs of the workforce for successful implementation.

Table 1. Summary of Research Gaps.

Author(s)	Study Focus	Findings	Research gap
Wu et al., 2024.	Effects of AI on Employee Motivation	The study findings indicate that although AI can increase productivity and satisfaction, it may also diminish users’ level of engagement and autonomy when they engage in tasks that are not AI supported improving the level of employee motivation.	The research did not suggest ways in which Organizations can ensure a balance between performance and motivation through use of AI.
Huang & Rust (2021).	AI and automation	Automation can get rid of routine tasks which increases enjoyment and creativity for the job.	The framework did not address job insecurity, fear of replacement and perceived loss of autonomy and control.
Haenlein et al., (2019).	Trust in AI and employee motivation	Haenlein et al., (2019), emphasize the importance of trust in AI for organizational success	The authors do not investigate how trust develops at the employee level or how it influences motivation, engagement, or attitudes toward AI.

3. Research Methodology

This study employed a desk-based literature review to synthesize existing scholarly work relevant to the study objectives. Peer-reviewed journal articles and authoritative academic sources such as Google Scholar, Emerald Insight, and ScienceDirect. This was to allow the summary of literature analyzed, which was based on synthesis of concepts studied and theories applied to generate conclusions.

4. Discussion of Findings

While automation supports autonomy and ultimately improved performance according to the Unified Theory of Acceptance and Use of Technology (UTAUT), over automation on the other hand may be seen as a threat to the employees in the long run in the assumption that the human effort will no longer be required. From the review, automation is seen to support human capabilities to improve task mastery, decision making and learning, which further strengthens employee motivation and performance. This motivation and improved performance can only be experienced if the application of automation by use of AI, is done moderately and not over-automation. According to UTAUT, automation creates autonomy and improves work meaningfulness which is an intrinsic motivator.

AI cannot be a motivator on its own. AI enhances motivators such as achievement, responsibility and opportunities for growth, then this leads to increased motivation among the employees. Similarly, according to the Herzberg’s two-factory Theory, AI may pose as a threat to hygiene factors such as job security, policy and supervision which leads to dissatisfaction instead of motivation. AI systems can significantly enhance or hinder enjoyment of work, which is dependent on how AI systems are designed, implemented and integrated throughout the organization.

Similarly, when employees feel unprotected during technological changes, they lose trust in both the systems and the leadership, hence the need for adequate policies that protect the employees in order to increase motivation and improve their loyalty.

5. Conclusion

AI motivates employees through transformation in the nature of work, making it more involving or engaging, meaningful and personalized to their abilities. The Organizational readiness, ethical design and the mode of implementation of AI can be a great determinant of the success in building motivation for employees through the use of AI. Employees may only feel safer if the AI systems are implemented to automate routine tasks, where the employees are left to concentrate more on the analytical, creative, and intellectual bits of their work, which is a motivating factor.

On the other hand, when implementation of AI does not involve employees, or when the employees do not understand the goal of AI in their organization, they may begin to feel a sense of surveillance and over control, making them lose trust in AI. Additionally, when the systems especially in Human Resource tasks are not accurate, the employees lose trust in the system which further leads to demotivation. This review concluded that AI adoption may trigger stress and job insecurity, which can ultimately weaken employee motivation.

This study adds to AI and employee motivation research by showing how existing motivation theories apply in emerging economies, where limited resources affect how employees respond to AI. By examining human–AI interaction in these settings, the study fills a gap in research that has mainly focused on developed economies.

6. Recommendations

6.1. Recommendations for Practice

Successful companies should have a mix of AI with emotional intelligence, to ensure that technology only magnifies human motivation and not replace the motivation. Organizations should establish clear guidelines with ethical, transparent and responsible use of AI. These guidelines include ability to explain decisions, assure employee data protection, have surveillance limits as well as fairness around decision making. Communication around how decisions are made should be clearly done. These are the determinants of accuracy and trust in AI in an organization.

In addition, Organizations should avoid over-automation, to ensure employees have reasonable engagement with the systems as well as be able to make judgement. This preserves autonomy and purpose which in turn enhances the intrinsic type of motivation among the employees.

Companies should use AI to enhance motivation as opposed to using the systems just for efficiency. Organizations should ensure the systems support creativity, provide feedback and improves the task mastery. This could be through training which improves their task mastery, support learning within the Organization. The findings inform managers and policymakers on aligning AI implementation with employee capabilities and organizational readiness to sustain motivation.

Finally, AI should not be used as a monitoring tool since excessive surveillance causes a reduction in autonomy which may cause dissatisfaction instead of motivating the employees.

6.2. Recommendation of Future Research

Future research is recommended to examine how factors such as job type, age or digital literacy contribute to the level of motivation on individual employees and the overall effect of adoption of AI based on these parameters.

Investigation could also be conducted to determine the optimal levels of automation that may lead to motivation, where future research should identify how much automation is adequate and where the balance between automation and human involvement best enhances employee motivation.

Abbreviations

AI	Artificial Intelligence
UTAUT	Unified Theory of Acceptance and Use of Technology

Conflicts of Interest

The authors declare no conflicts of interest.

References

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Ngari, E., Wanyoike, R. (2026). Artificial Intelligence and Employee Motivation: A Desk-based Empirical Review. Journal of Human Resource Management, 14(1), 75-81. https://doi.org/10.11648/j.jhrm.20261401.18

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Ngari, E.; Wanyoike, R. Artificial Intelligence and Employee Motivation: A Desk-based Empirical Review. J. Hum. Resour. Manag. 2026, 14(1), 75-81. doi: 10.11648/j.jhrm.20261401.18

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Ngari E, Wanyoike R. Artificial Intelligence and Employee Motivation: A Desk-based Empirical Review. J Hum Resour Manag. 2026;14(1):75-81. doi: 10.11648/j.jhrm.20261401.18

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@article{10.11648/j.jhrm.20261401.18,
  author = {Evelyne Ngari and Rosemarie Wanyoike},
  title = {Artificial Intelligence and Employee Motivation: 
A Desk-based Empirical Review},
  journal = {Journal of Human Resource Management},
  volume = {14},
  number = {1},
  pages = {75-81},
  doi = {10.11648/j.jhrm.20261401.18},
  url = {https://doi.org/10.11648/j.jhrm.20261401.18},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jhrm.20261401.18},
  abstract = {Artificial Intelligence, commonly referred to in abbreviation as ‘AI’, is rapidly gaining popularity in the workplace today. The use of AI may be a source of motivation to the employees, or lack of it for various reasons. This empirical study sought to find out how Artificial Intelligence (AI) influences employee motivation at the workplace. Through analysis of various journals, this desk review examined system accuracy, task automation and trust in AI and how these affect employee motivation as the independent variables in the study. To explain motivation as influenced by AI, this review considered enjoyment of work, work involvement and goal achievement as the indicators for motivation which were the independent variables for the study. The Unified Theory of Acceptance and Use of Technology (UTAUT) and the Hertzberg Two Factor Theory were used to explain the variables in the study. The desk review revealed that even though there are positive benefits derived from the use of AI, there are a number of issues that have been left unfulfilled by the adoption of the systems at the workplace, some which affect employee motivation. Finally, the review made several recommendations for practice and future research in the area of AI with relation of employee motivation based on the research gaps identified.},
 year = {2026}
}

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AU  - Rosemarie Wanyoike
Y1  - 2026/02/09
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N1  - https://doi.org/10.11648/j.jhrm.20261401.18
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AB  - Artificial Intelligence, commonly referred to in abbreviation as ‘AI’, is rapidly gaining popularity in the workplace today. The use of AI may be a source of motivation to the employees, or lack of it for various reasons. This empirical study sought to find out how Artificial Intelligence (AI) influences employee motivation at the workplace. Through analysis of various journals, this desk review examined system accuracy, task automation and trust in AI and how these affect employee motivation as the independent variables in the study. To explain motivation as influenced by AI, this review considered enjoyment of work, work involvement and goal achievement as the indicators for motivation which were the independent variables for the study. The Unified Theory of Acceptance and Use of Technology (UTAUT) and the Hertzberg Two Factor Theory were used to explain the variables in the study. The desk review revealed that even though there are positive benefits derived from the use of AI, there are a number of issues that have been left unfulfilled by the adoption of the systems at the workplace, some which affect employee motivation. Finally, the review made several recommendations for practice and future research in the area of AI with relation of employee motivation based on the research gaps identified.
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Author Information

Evelyne Ngari

School of Business, Kenyatta University, Nairobi, Kenya

http://orcid.org/0009-0004-8166-3275
Rosemarie Wanyoike

School of Business, Kenyatta University, Nairobi, Kenya

Contact Email

http://orcid.org/0000-0002-9021-1965

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Figure 1

Figure 1. Conceptual Framework.

Table 1

Table 1. Summary of Research Gaps.

Plain Text BibTeX RIS

APA Style

Ngari, E., Wanyoike, R. (2026). Artificial Intelligence and Employee Motivation: A Desk-based Empirical Review. Journal of Human Resource Management, 14(1), 75-81. https://doi.org/10.11648/j.jhrm.20261401.18

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ACS Style

Ngari, E.; Wanyoike, R. Artificial Intelligence and Employee Motivation: A Desk-based Empirical Review. J. Hum. Resour. Manag. 2026, 14(1), 75-81. doi: 10.11648/j.jhrm.20261401.18

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AMA Style

Ngari E, Wanyoike R. Artificial Intelligence and Employee Motivation: A Desk-based Empirical Review. J Hum Resour Manag. 2026;14(1):75-81. doi: 10.11648/j.jhrm.20261401.18

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@article{10.11648/j.jhrm.20261401.18,
  author = {Evelyne Ngari and Rosemarie Wanyoike},
  title = {Artificial Intelligence and Employee Motivation: 
A Desk-based Empirical Review},
  journal = {Journal of Human Resource Management},
  volume = {14},
  number = {1},
  pages = {75-81},
  doi = {10.11648/j.jhrm.20261401.18},
  url = {https://doi.org/10.11648/j.jhrm.20261401.18},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jhrm.20261401.18},
  abstract = {Artificial Intelligence, commonly referred to in abbreviation as ‘AI’, is rapidly gaining popularity in the workplace today. The use of AI may be a source of motivation to the employees, or lack of it for various reasons. This empirical study sought to find out how Artificial Intelligence (AI) influences employee motivation at the workplace. Through analysis of various journals, this desk review examined system accuracy, task automation and trust in AI and how these affect employee motivation as the independent variables in the study. To explain motivation as influenced by AI, this review considered enjoyment of work, work involvement and goal achievement as the indicators for motivation which were the independent variables for the study. The Unified Theory of Acceptance and Use of Technology (UTAUT) and the Hertzberg Two Factor Theory were used to explain the variables in the study. The desk review revealed that even though there are positive benefits derived from the use of AI, there are a number of issues that have been left unfulfilled by the adoption of the systems at the workplace, some which affect employee motivation. Finally, the review made several recommendations for practice and future research in the area of AI with relation of employee motivation based on the research gaps identified.},
 year = {2026}
}

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TY  - JOUR
T1  - Artificial Intelligence and Employee Motivation: 
A Desk-based Empirical Review
AU  - Evelyne Ngari
AU  - Rosemarie Wanyoike
Y1  - 2026/02/09
PY  - 2026
N1  - https://doi.org/10.11648/j.jhrm.20261401.18
DO  - 10.11648/j.jhrm.20261401.18
T2  - Journal of Human Resource Management
JF  - Journal of Human Resource Management
JO  - Journal of Human Resource Management
SP  - 75
EP  - 81
PB  - Science Publishing Group
SN  - 2331-0715
UR  - https://doi.org/10.11648/j.jhrm.20261401.18
AB  - Artificial Intelligence, commonly referred to in abbreviation as ‘AI’, is rapidly gaining popularity in the workplace today. The use of AI may be a source of motivation to the employees, or lack of it for various reasons. This empirical study sought to find out how Artificial Intelligence (AI) influences employee motivation at the workplace. Through analysis of various journals, this desk review examined system accuracy, task automation and trust in AI and how these affect employee motivation as the independent variables in the study. To explain motivation as influenced by AI, this review considered enjoyment of work, work involvement and goal achievement as the indicators for motivation which were the independent variables for the study. The Unified Theory of Acceptance and Use of Technology (UTAUT) and the Hertzberg Two Factor Theory were used to explain the variables in the study. The desk review revealed that even though there are positive benefits derived from the use of AI, there are a number of issues that have been left unfulfilled by the adoption of the systems at the workplace, some which affect employee motivation. Finally, the review made several recommendations for practice and future research in the area of AI with relation of employee motivation based on the research gaps identified.
VL  - 14
IS  - 1
ER  -

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