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Human Resources Management and Services 2025, 7(1), 4132.
https://doi.org/10.18282/hrms4132
1
Article
Exploring and addressing AI challenges in HRM: Insights and evidence
from the UAE workforce
Divya Upadhyay
Management, Abu Dhabi School of Management, Abu Dhabi 6844, UAE; d.upadhyay@adsm.ac.ae
Abstract: Purpose: This article explores the adoption of Artificial Intelligence (AI) in Human
Resource Management (HRM) in the UAE, focusing on the critical challenges of fairness, bias,
and privacy in recruitment processes. The study aims to understand how AI is transforming
HR practices in the UAE, highlighting the issues of bias and privacy while examining real-
world applications of AI in recruitment, employee engagement, talent management, and
learning and development. Methodology: Through case study methodology, detailed insights
are gathered from these companies to understand real-world applications of AI in HRM. A
comparative analysis is conducted, comparing AI-driven HRM practices in UAE-based
organizations with international examples to highlight global trends and best practices.
Findings: The research reveals that while AI holds significant potential to streamline HR
functions such as recruitment, onboarding, performance monitoring, and talent management, it
also discusses challenges and strategies companies face and develop in integrating AI into their
HRM processes, reflecting the broader context of AI adoption in the UAE’s HR landscape.
Originality: This paper contributes to the growing body of literature on AI in HRM by
focusing on the unique context of the UAE, a rapidly developing market with a highly diverse
workforce. It highlights the specific challenges and opportunities faced by organizations in the
UAE when implementing AI in HRM, particularly regarding fairness, bias, and data privacy.
Keywords: artificial intelligence; human resource management; strategies; UAE
1. Introduction
The integration of Artificial Intelligence (AI) into Human Resource Management
(HRM) in the UAE is rapidly advancing, propelled by the nation’s focus on digital
transformation and innovation as outlined in initiatives like the UAE Vision 2030
(Pereira, 2020). AI-powered tools are increasingly employed to enhance recruitment
processes, utilizing algorithms to screen resumes, match candidates to job profiles, and
conduct preliminary interviews via AI-driven chatbots. These technologies reduce
biases, accelerate the hiring process, and enable organizations to identify top talent
efficiently (Aboramadan et al., 2024). In addition to recruitment, AI-driven platforms
are pivotal in monitoring employee engagement and predicting turnover rates. By
analyzing data on employee interactions, feedback, and performance, these systems
allow HR managers to address potential issues proactively. In the UAE’s highly
competitive labor market, where employee retention is a priority, AI empowers HR
teams to devise more effective retention strategies (Singh and Shaurya, 2021). The
adoption of AI in HRM optimizes operational efficiency and aligns with the UAE’s
broader vision of leveraging technology for economic and organizational development
(Fenech et al., 2019).
CITATION
Upadhyay D. (2025). Exploring and
addressing AI challenges in HRM:
Insights and evidence from the UAE
workforce. Human Resources
Management and Services. 7(1):
4132.
https://doi.org/10.18282/hrms4132
ARTICLE INFO
Received: 20 February 2025
Accepted: 14 March 2025
Available online: 26 March 2025
COPYRIGHT
Copyright © 2025 by author(s).
Human Resources Management and
Services is published by PiscoMed
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licensed under the Creative
Commons Attribution (CC BY)
license.
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by/4.0/
Human Resources Management and Services 2025, 7(1), 4132.
2
The UAE’s focus on skills development, particularly in light of the country’s
innovation agenda, has led to the adoption of AI in personalized learning. AI-powered
platforms can tailor learning experiences based on employees’ skill gaps, learning
pace, and career goals. This ensures employees have the skills needed for the future
(Shaya et al., 2023). AI tools in performance management help continuously track and
evaluate employee performance. Through real-time feedback and data analysis, HR
professionals in the UAE can make more informed decisions about promotions,
rewards, and training needs. This aligns with the nation’s emphasis on building high-
performing organizations. AI’s ability to process vast amounts of data helps HR
departments forecast workforce needs, identify trends in employee behavior, and
improve workforce allocation. In the UAE, where industries such as technology,
construction, and finance are expanding, AI-enabled workforce analytics provide
insights that support strategic planning (Li et al., 2023).
While existing research explores the role of AI in HRM globally, limited studies
focus on AI-driven HR practices in the UAE, a region with a highly diverse workforce
and unique regulatory landscape. Most studies highlight AI’s general impact on
recruitment, talent management, and learning (Aboramadan et al., 2024; Fenech et al.,
2019), but few address the specific challenges of fairness, bias, and privacy in the UAE
context. Additionally, comparative analyses between UAE-based organizations and
international AI-driven HRM practices remain scarce, creating a need for localized
insights into how AI aligns with cultural, legal, and economic factors in the region.
This study contributes to the literature by offering a UAE-specific analysis of AI
adoption in HRM, bridging the gap between global trends and local practices. Insights
into fairness, bias, and privacy challenges, which are critical but underexplored in the
UAE’s AI-driven HR landscape. By addressing these gaps, this research serves as a
valuable resource for HR professionals, policymakers, and researchers, guiding AI’s
ethical and strategic integration into the UAE’s evolving HR ecosystem.
2. Relevance of AI in HRM in UAE
The UAE’s commitment to becoming a global leader in AI is evident in its
establishment of a Minister of AI and the implementation of various AI strategies. The
integration of AI into HRM aligns with the country’s broader vision to transform
traditional sectors, improve efficiency, and innovate across both public and private
organizations (Du, 2024; McKinsey, 2021). By automating key HR tasks such as
candidate screening, onboarding, and payroll management, AI enables HR
departments to reduce operational costs and administrative workloads, which is
particularly crucial in the UAE’s fast-evolving market (Pandya and Al Janahi, 2021).
With the UAE’s dynamic job market, where sectors like technology, finance, and
construction are experiencing high demand for talent, AI is instrumental in optimizing
recruitment processes. AI-powered systems can quickly analyze large volumes of
resumes, match candidates with suitable job profiles, and even conduct pre-interview
assessments, helping organizations attract the right talent efficiently (McKinsey,
2021). Additionally, AI fosters more inclusive hiring processes by mitigating
unconscious biases in recruitment, a critical factor given the UAE’s diverse expatriate
Human Resources Management and Services 2025, 7(1), 4132.
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population. This enhances fairness and ensures that talent acquisition remains
inclusive and unbiased.
AI-driven analytics provide HR professionals with real-time insights into
employee performance, engagement, and satisfaction. In a competitive labor market
like the UAE, where employee retention is a priority, AI allows HR managers to
monitor employee well-being and productivity, helping to prevent turnover and
improve organizational performance (McKinsey, 2021). Furthermore, AI supports the
UAE’s emphasis on skills development by offering personalized learning experiences
for employees. AI-powered platforms can identify skill gaps and tailor training
programs to individual career goals, which is essential for advancing the country’s
knowledge-based economy.
AI-driven workforce analytics also contribute to long-term strategic planning by
predicting future workforce needs and identifying talent gaps. This is particularly
important for industries like construction, hospitality, and finance, which are vital to
the UAE’s economy. With such insights, organizations can ensure optimal human
resource allocation and plan for future demands. In addition, AI helps HR departments
make data-driven decisions about promotions, performance appraisals, and
compensation, leading to more objective and accurate HR practices in the UAE’s
competitive business environment (McKinsey, 2021).
As the UAE’s regulatory framework evolves, particularly with the
implementation of data protection legislation like the UAE Data Protection Law, AI
technologies have become instrumental in enabling HR departments to comply with
these regulations. By automating data management processes and monitoring legal
obligations, AI ensures adherence to compliance standards, thereby safeguarding
employee trust and upholding organizational accountability (Okatta et al., 2024). In
addition, the post-pandemic shift to flexible work models, including hybrid and remote
arrangements, has further highlighted the role of AI in modern HR practices. AI-driven
solutions facilitate seamless virtual onboarding processes, enhance employee
engagement, and support collaborative efforts, making them indispensable in today’s
dynamic work environment (Mer and Virdi, 2023). These innovations not only
streamline HR operations but also contribute to maintaining productivity and fostering
organizational resilience in an era of rapid digital transformation (Fenwick et al., 2024;
Krishnan and Chinnathambi, 2024).
3. Challenges and ethical considerations
Artificial Intelligence (AI) in HRM offers substantial advantages, including
heightened efficiency, data-driven decision-making, and improved employee
engagement. AI enables HR departments to streamline operations and foster a more
strategic approach to managing talent. However, these benefits are accompanied by
challenges related to data privacy, job displacement, and fairness in decision-making
processes (Bankins, 2021; Mendy et al., 2024). In the UAE, organizations face the
dual responsibility of leveraging AI’s potential while adhering to local labor laws and
data protection regulations, such as the UAE Data Protection Law. This regulatory
framework emphasizes the ethical handling of employee data, underscoring the
importance of transparency and compliance in AI-driven HR practices (Elhaj, 2022).
Human Resources Management and Services 2025, 7(1), 4132.
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While AI can transform HRM into a more strategic and data-focused function,
organizations must carefully address ethical concerns to maintain trust and equity in
the workplace. The risk of biases embedded in AI algorithms and potential job
displacement necessitates the implementation of robust governance frameworks that
prioritize fairness, accountability, and inclusivity (Khair et al., 2020). Achieving this
balance ensures that adopting AI contributes positively to organizational performance
while upholding ethical standards and fostering employee trust.
Bias and Discrimination: One of the major ethical challenges in using AI in HRM
is the risk of bias in algorithms. AI systems are trained on historical data, and if that
data contains biases (e.g., gender, race, or socioeconomic biases), the AI can
perpetuate or even amplify those biases in decisions like recruitment, performance
evaluations, and promotions. Bias in AI can lead to unfair hiring practices or biased
employee evaluations, which violate principles of fairness and equality. AI must be
carefully designed and regularly audited to ensure it does not discriminate against
specific groups.
Data Privacy and Security: AI relies on vast amounts of data, often including
sensitive personal information about employees. This raises concerns about how that
data is collected, stored, and used. In HR, where personal information like
performance records, health data, and feedback is critical, the risk of data breaches or
misuse is high. Organizations using AI in HR must ensure they comply with data
privacy laws, such as the UAE Data Protection Law. Transparent data handling and
clear consent processes are essential to protect employees’ privacy.
Transparency and Accountability: AI algorithms in HR often operate as “black
boxes,” meaning that HR managers may not fully understand how decisions are made.
This lack of transparency can make it difficult for employees to challenge or appeal
AI-driven decisions regarding recruitment, promotions, or terminations. There is a
need for transparency in how AI-driven decisions are made. Organizations must be
able to explain AI’s decision-making processes and ensure accountability for those
decisions.
Job Displacement and Automation: As AI automates various HR tasks, such as
recruitment, employee onboarding, and performance evaluations, there is growing
concern about the displacement of HR professionals and the reduction in the human
element of HRM. AI-driven automation might eliminate roles in recruitment or payroll
processing, impacting employment within the HR sector itself. Organizations need to
strike a balance between leveraging AI for efficiency and preserving the human touch
in HR. There is also a social responsibility to retrain employees whose roles might be
affected by AI-driven automation.
Invasion of Employee Privacy: AI tools used for monitoring employee
productivity and behavior can sometimes cross ethical lines, leading to an invasion of
privacy. For example, AI systems that track keystrokes, time spent on applications, or
even social media activity may be seen as overly intrusive. There is a fine line between
using AI to enhance productivity and violating employee privacy. Ethical concerns
arise when AI monitoring becomes invasive or leads to micromanagement.
AI Decision-Making vs. Human Judgment: While AI can analyze data quickly
and make decisions based on patterns, it often lacks the emotional intelligence and
nuanced understanding of human behavior that HR professionals bring to decision-
Human Resources Management and Services 2025, 7(1), 4132.
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making. This raises concerns about the over-reliance on AI in HR processes that
require empathy, ethical judgment, or the consideration of context. AI should
complement, not replace, human decision-making, especially in areas like conflict
resolution, employee development, or terminations, where human judgment and
empathy are critical.
Employee Trust and Acceptance: Implementing AI in HR can sometimes lead to
resistance from employees who fear job displacement or do not trust the AI’s fairness.
Building employee trust in AI systems is crucial for their successful adoption in HR
processes. Companies must foster a culture of transparency, where employees
understand how AI is used and how it benefits them. Without clear communication,
employees may feel that their autonomy and job security are threatened.
Lack of Regulation and Standardization: The rapid development of AI in HRM
has outpaced the creation of comprehensive regulatory frameworks, leaving ethical
gaps in areas such as accountability, data protection, and fairness. While some regions,
such as the EU, have made strides with AI regulations, many countries, including the
UAE, are still developing comprehensive AI-specific regulatory frameworks. Without
clear regulations, organizations must adopt ethical guidelines proactively to ensure
responsible AI use in HR. Failure to do so can lead to ethical breaches, legal risks, and
damage to an organization’s reputation.
This article explores the adoption of AI in HRM in the UAE, focusing on the
critical challenges of fairness, bias, and privacy in recruitment processes. The study
aims to understand how AI is transforming HR practices in the UAE, highlighting the
issues of bias and privacy while examining real-world applications of AI in
recruitment, employee engagement, talent management, and learning and
development. Further, this paper develops tables that capture the distinct yet
overlapping challenges and strategies these companies face and develop in integrating
AI into their HRM processes, reflecting the broader context of AI adoption in the
UAE’s HR landscape.
4. Methodology
This paper employs a case study method and comparative analysis based on
secondary data available methodology to investigate the integration of AI into HRM
practices within the UAE, with a focus on recruitment, employee development, and
workforce analytics. The methodology explores AI’s role in HRM practices in leading
UAE organizations. These organizations are recognized for their progressive adoption
of AI technologies, making them ideal candidates for this study.
Comparative analysis: A comparative analysis of the HRM practices at Etihad
Airways, Etisalat, and Careem was conducted to understand how these companies
integrate AI into their HR processes, and Table 1 is developed. This analysis also
compared these practices with international examples, providing a broader perspective
on global trends and regional variations in AI adoption.
Case study method: The four leading UAE-based organizations were selected for
in-depth case studies:
1) Emirates Group: Known for its AI-driven recruitment processes and employee
development programs, particularly in the aviation sector. This case study
Human Resources Management and Services 2025, 7(1), 4132.
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explores how Etihad leverages AI for candidate screening, onboarding, and talent
management. Additionally, it examines the company’s AI tools for monitoring
employee performance, engagement, and retention.
2) Etisalat: As a major telecommunications company, Etisalat has integrated AI into
its HRM to enhance recruitment processes, employee training, and workforce
analytics. This case study investigates Etisalat’s use of AI for skill gap analysis,
personalized employee development, and fostering diversity and inclusion.
3) Careem: As a leading UAE-based tech company in the ride-hailing industry,
Careem has adopted AI technologies in its HR practices, particularly in employee
training, performance management, and retention. The study analyzes how
Careem uses AI to personalize learning experiences, track employee performance,
and enhance employee satisfaction and well-being.
4) Etihad Airways: Known for its AI-driven recruitment processes and employee
development programs, particularly in the aviation sector, Etihad Airways
exemplifies how AI transforms HRM. The use of AI for candidate screening,
onboarding, and talent management ensures a streamlined and efficient hiring
process. Implementing AI tools to monitor employee performance, engagement,
and retention enables proactive HR interventions.
The selection of Etihad Airways, Etisalat, Careem, and Emirates Group was
based on the following criteria: Industry Leadership in AI Adoption: These
organizations are recognized as pioneers in AI-driven HRM in their respective sectors
(aviation, telecommunications, technology, and transportation). Diversity in Sectors:
The study includes companies from different industries to provide a comprehensive
view of AI applications in HRM across various business environments. Availability
of Secondary Data: The companies were selected based on the availability of public
reports, company disclosures, and industry insights that provide valuable information
on AI-driven HR practices. The inclusion of companies from different industries
allows for a broader understanding of how AI adoption in HRM varies across sectors
while identifying common trends and challenges.
This study relies on secondary data sources to examine AI integration into HRM.
The data was collected from annual reports and HR policy documents from Etisalat,
Careem, Emirates Group, and Etihad Airways. Whitepapers on AI-driven HR
transformations were released by these organizations. Reports from consulting firms
on AI adoption in HRM in the UAE. Government and policy documents related to AI
regulations in HR practices (e.g., UAE’s Artificial Intelligence Strategy 2031). Media
sources detailing AI-driven HR innovations within the selected companies.
5. Evidence from the UAE challenges
Several UAE companies have begun adopting AI in their HRM practices to
enhance efficiency, streamline recruitment, and support employee development.
These examples highlight how AI is transforming HR functions in various
organizations:
Emirates Group: The Emirates Group, one of the largest aviation conglomerates
in the UAE, utilizes AI to enhance its HR processes, particularly in recruitment. AI-
powered tools are employed to screen thousands of resumes quickly and efficiently,
Human Resources Management and Services 2025, 7(1), 4132.
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identifying the best candidates based on predefined criteria. By leveraging AI,
Emirates ensures it can handle large volumes of applications without sacrificing speed
or accuracy. The system also helps reduce bias by focusing on specific skill sets and
qualifications rather than relying on subjective judgments made by human recruiters.
While the Emirates Group has embraced AI to streamline its HR processes,
particularly in recruitment, the implementation of AI in HRM is not without challenges.
Some of the key challenges faced by Emirates Group in implementing AI in HRM
include:
Bias and fairness: Although AI is designed to reduce bias by focusing on
objective criteria such as skills and qualifications, it can still unintentionally perpetuate
biases present in the training data. If the historical data used to train AI models reflects
biased hiring practices, such as favoring certain nationalities or genders, the AI system
may continue to replicate these biases, leading to unfair recruitment outcomes.
Ensuring that the AI models are free from bias and capable of fair decision-making is
an ongoing challenge. The claim that AI removes subjective human judgment by
making data-driven decisions and ensuring fair and objective hiring is often challenged
by the reality that AI models are only as unbiased as the data they are trained on. If
historical hiring data contains inherent biases related to gender, nationality, or other
demographic factors, AI systems may inadvertently learn and perpetuate these patterns,
leading to discriminatory hiring outcomes (Mehrabi et al., 2021). To mitigate this risk,
organizations must prioritize the use of diverse and representative datasets that
accurately reflect fair hiring practices. Additionally, conducting regular bias audits
allows HR teams to identify and rectify any disparities in AI-driven decision-making
processes. Implementing fairness-aware algorithms further ensures that AI models
actively detect and adjust for bias, promoting more equitable hiring outcomes. By
adopting these strategies, organizations can harness AI’s efficiency while minimizing
its potential for reinforcing discriminatory practices in recruitment.
Data privacy and security: AI systems used in HRM require vast amounts of
personal data, including candidates’ resumes, performance records, and other sensitive
information. In a country like the UAE, where data privacy regulations are evolving,
Emirates Group faces the challenge of ensuring compliance with data protection laws
while using AI for HR processes. Any data breach or misuse of personal information
could lead to reputational damage and legal consequences.
Transparency and accountability: One of the significant challenges of using AI
in HR is the lack of transparency in how AI-driven decisions are made. The “black
box” nature of many AI algorithms makes it difficult for HR teams and candidates to
understand why certain decisions were made, such as why a particular candidate was
rejected. Ensuring transparency in AI decisions and maintaining accountability in the
recruitment process can be challenging.
Workforce resistance and change management: The introduction of AI in HRM
can lead to concerns among HR staff and employees about job displacement or
changes in their roles. Some employees may be resistant to adopting AI technologies,
fearing that AI will replace their jobs or make human intervention less relevant.
Effective change management strategies are needed to address these concerns and
ensure that employees understand how AI will complement rather than replace their
roles.
Human Resources Management and Services 2025, 7(1), 4132.
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Skill gaps in HR teams: Implementing AI in HRM requires HR professionals to
have a certain level of technical proficiency to work with AI tools effectively. The
Emirates Group may face challenges in upskilling its HR staff to understand and
operate AI systems, interpret the results, and make informed decisions based on AI-
driven insights. Bridging the skill gap between traditional HR roles and technology-
oriented roles can be a significant challenge.
Cost of implementation: AI systems are expensive to develop, implement, and
maintain. The Emirates Group, like many large organizations, may face high initial
costs in integrating AI into its HRM processes. Moreover, continuous updates and
monitoring are required to ensure that AI systems are functioning optimally and
staying aligned with regulatory requirements, further adding to operational costs.
Cultural sensitivity: The UAE’s diverse and multicultural workforce necessitates
the design and implementation of AI systems that are sensitive to varied cultural
contexts. The Emirates Group must ensure that AI tools do not inadvertently prioritize
or disadvantage certain cultural groups. For example, an AI system may interpret
communication styles or work experiences differently across nationalities, which can
lead to unintended exclusion in recruitment and performance assessments.
Etisalat: Etisalat, the UAE’s leading telecommunications company, uses AI and
machine learning to support various HR functions. The company has implemented AI-
driven solutions to forecast workforce needs, enabling more precise HR planning.
Predictive analytics help Etisalat determine which skills will be needed in the future,
allowing the organization to tailor its recruitment strategies accordingly. Moreover,
AI assists in performance management and employee development, where data is used
to assess employee progress and recommend personalized training programs.
As the UAE’s leading telecommunications company, Etisalat has embraced AI
and machine learning to optimize its HR functions. However, like any organization
implementing AI in Human Resource Management (HRM), Etisalat faces several
challenges. These include:
Data quality and bias: AI systems rely heavily on high-quality data for effective
decision-making. In HR, data such as employee performance records, recruitment
histories, and skill assessments are used to train AI models. However, if the data is
incomplete, inaccurate, or biased, the AI-driven predictions and recommendations
may be flawed. Bias in data—whether related to gender, age, nationality, or other
factors—could lead to unfair recruitment decisions or skewed performance
assessments, perpetuating systemic inequalities.
Privacy and data security: AI-driven HR solutions require access to sensitive
personal data about employees and candidates. Etisalat must navigate stringent data
privacy regulations in the UAE, ensuring that the AI systems comply with data
protection laws such as the UAE Personal Data Protection Law (PDPL). Unauthorized
access, data breaches, or mishandling of personal information could lead to legal
liabilities, reputational damage, and erosion of employee trust.
Algorithm transparency and accountability: One of the significant challenges in
AI-driven HRM systems is the lack of transparency in how AI algorithms reach their
decisions. For example, AI tools may recommend certain candidates or suggest
personalized employee training without providing clear explanations as to why those
choices were made. This “black box” issue can create a lack of trust among employees
Human Resources Management and Services 2025, 7(1), 4132.
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and HR teams. Ensuring that AI models are explainable, accountable, and auditable is
critical but often challenging.
Workforce resistance to AI: Introducing AI-driven systems can create anxiety
among employees, who may fear job displacement or reduced control over HR
decisions. HR professionals may also feel uncertain about the role of AI, worrying that
AI could replace traditional HR functions or marginalize human decision-making.
Managing employee expectations, addressing concerns, and implementing change
management strategies to foster acceptance of AI tools are challenges Etisalat needs
to navigate.
Skills and training gaps in HR teams: For AI to be effectively integrated into HR
processes, HR professionals at Etisalat must have the technical skills to understand
and work alongside AI systems. This includes interpreting predictive analytics,
managing AI tools, and ensuring the technology aligns with organizational goals.
Upskilling HR personnel and closing the gap between traditional HR functions and
AI-based methods is a significant challenge, particularly as AI technologies continue
to evolve.
Cost of implementation and maintenance: The development, integration, and
ongoing maintenance of AI systems in HR can be costly. While AI can bring long-
term efficiency, the initial setup involves significant financial investments in
technology infrastructure, data collection, and system customization. Additionally,
ongoing costs related to software updates, data management, and compliance with
regulatory changes are factors Etisalat must consider when implementing AI in HRM.
Ethical concerns: AI systems in HR raise ethical questions about the balance
between automation and human oversight. Etisalat must ensure that AI does not
dehumanize the HR process, especially in sensitive areas such as employee
development, performance evaluations, and workforce planning. One of the major
ethical dilemmas in AI-driven HR is ensuring that automation does not replace human
empathy, intuition, and fairness in decision-making.
AI-based tools assist in resume screening, candidate matching, and employee
monitoring, but relying solely on AI may depersonalize HR processes. Ensuring that
AI systems maintain a balance between efficiency and empathy is an ongoing
challenge, requiring clear ethical guidelines and human oversight.
Adapting AI to a multicultural workforce: The UAE’s highly diverse workforce
includes employees from various nationalities and cultural backgrounds. AI systems
in HR must account for this diversity, ensuring that recruitment, performance
assessments, and employee development programs do not favor one group over
another. Developing AI tools that can understand and respect cultural differences
while providing fair and inclusive outcomes is crucial but difficult to implement
effectively.
Careem: As one of the UAE’s fastest-growing tech companies, Careem uses AI
to enhance its HR operations. Careem leverages AI to streamline recruitment, utilizing
algorithms that analyze job applicants’ skills and qualifications to identify the best-fit
candidates. Moreover, AI assists the company in managing its large workforce by
predicting employee attrition and helping the HR team intervene early to retain
valuable talent. AI-driven tools at Careem also support employee engagement and
development, offering tailored career growth opportunities for employees.
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As one of the UAE’s leading tech companies, Careem has effectively integrated
AI into its HR operations to improve recruitment and manage its workforce. However,
implementing AI in HRM comes with its own set of challenges. Some of the key
challenges Careem may face include:
Data privacy and compliance: Careem’s use of AI relies on collecting and
analyzing significant amounts of personal data from employees and candidates.
Compliance with data privacy regulations, such as the UAE’s Personal Data Protection
Law (PDPL), is crucial to avoid legal issues and reputational damage. Careem must
ensure that it manages personal data responsibly and transparently, safeguarding
against potential data breaches that could undermine employee trust.
Bias in AI algorithms: Despite the aim to create a fair recruitment process, AI
algorithms can unintentionally perpetuate existing biases present in training data. If
historical data reflects biased hiring practices, AI systems may replicate those biases
in candidate selection, disadvantaging qualified individuals from certain backgrounds
or demographics. Careem needs to continuously audit its algorithms to identify and
mitigate any biases that may arise.
Change management and employee buy-in: The introduction of AI-driven
processes may lead to concerns among employees regarding job security and the
potential for reduced human interaction in HR functions. Employees may resist
adopting AI technologies, fearing that it will diminish their roles or replace them
entirely. Careem must implement effective change management strategies to educate
employees about the benefits of AI and foster acceptance of new tools.
Skill gaps in HR teams: To leverage AI effectively, HR professionals at Careem
must possess a certain level of technical proficiency. The integration of AI tools may
require HR teams to develop new skills to understand and interpret AI-driven insights,
which could be challenging if the workforce lacks the necessary expertise. Careem
may need to invest in training and development programs to upskill its HR staff.
Algorithm transparency: AI algorithms can be complex and difficult to interpret.
For HR decisions, it is vital to provide transparency and explainability to ensure that
candidates and employees understand how decisions are made, particularly in
recruitment and performance evaluations. Careem faces the challenge of ensuring that
its AI tools are transparent and that the rationale behind AI-driven decisions is clear
and understandable.
Cost of implementation and maintenance: While AI can lead to increased
efficiency in HR processes, the initial costs associated with developing and
implementing AI systems can be significant. Careem must balance the upfront
investment in technology with the long-term benefits. Additionally, ongoing costs
related to software updates, system maintenance, and data management should be
accounted for in the budgeting process.
Cultural sensitivity: Given the diverse workforce in the UAE, Careem must
ensure that its AI-driven HR practices are culturally sensitive and inclusive. The
algorithms used in recruitment and employee development need to account for
different cultural backgrounds and communication styles to avoid alienating or
excluding certain groups.
Employee engagement and personalization: While AI can enhance employee
engagement by offering tailored career growth opportunities, the challenge lies in
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ensuring that these recommendations resonate with individual employee aspirations
and career paths. Careem must ensure that AI-driven solutions are not only data-driven
but also take into account the unique motivations and preferences of its workforce.
These examples demonstrate how UAE companies are increasingly relying on AI
to optimize HR functions, from recruitment and workforce planning to employee
development. By integrating AI, these companies can operate more efficiently while
addressing challenges related to talent acquisition and management in a rapidly
changing business environment.
As mentioned, refer to Tables 1 and 2 which capture the distinct yet overlapping
challenges and strategies these companies face and develop in integrating AI into their
HRM processes, reflecting the broader context of AI adoption in the UAE’s HR
landscape. Tables 1 and 2 explore how companies integrate AI into their HR processes.
Table 1. Comprehensive table summarizing the challenges faced by Emirates Group, Etisalat, Careem, and Etihad
Airways in integrating AI into their HRM practices.
Company
Challenges
Details
Emirates
Group
Bias and fairness
AI models may perpetuate biases in training data, affecting recruitment outcomes.
Data privacy and security
Compliance with the UAE’s evolving data privacy laws and safeguarding sensitive
personal data is critical.
Transparency and accountability
Difficulty in explaining AI-driven recruitment decisions due to the “black box” nature
of algorithms.
Workforce resistance and change
management
Employees fear job displacement or role changes due to AI adoption.
Skill gaps in HR teams
HR staff require upskilling to operate AI tools effectively and interpret their insights.
Cost of implementation
High costs for AI development, integration, and ongoing updates.
Cultural sensitivity
Ensuring AI systems accommodate diverse cultural backgrounds in the UAE
workforce.
Etisalat
Data quality and bias
Flawed or incomplete data may lead to inaccurate predictions or recommendations.
Privacy and data security
Complying with data protection laws and preventing data breaches.
Algorithm transparency and
accountability
Lack of clarity on how AI reaches decisions undermines trust.
Workforce resistance to AI
Employees may resist AI adoption due to fears of marginalization or replacement.
Skills and training gaps in HR teams
Need for technical expertise in HR teams to interpret AI-driven insights.
Cost of implementation and
maintenance
Significant upfront and ongoing costs for AI integration and compliance.
Ethical concerns
Balancing automation with human oversight to avoid dehumanizing HR processes.
Adapting AI to a multicultural
workforce
Ensuring AI systems provide fair and inclusive outcomes across diverse nationalities.
Careem
Data privacy and compliance
Managing sensitive employee data responsibly while adhering to the UAE’s PDPL.
Bias in AI algorithms
Risk of replicating biases from training data in recruitment decisions.
Change management and employee
buy-in
Addressing employee concerns about AI replacing human roles.
Skill gaps in HR teams
HR professionals need training to work effectively with AI systems.
Algorithm transparency and
explainability
Providing clear explanations for AI-driven decisions to build trust.
Human Resources Management and Services 2025, 7(1), 4132.
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Table 1. (Continued).
Company
Challenges
Details
Cost of implementation and
maintenance
Balancing high initial costs with long-term benefits while managing ongoing
expenses.
Cultural sensitivity
Creating AI systems that respect diverse cultural and communication styles.
Employee engagement and
personalization
Ensuring AI recommendations align with individual career aspirations and
motivations.
Etihad
Airways
Bias and fairness
Recruitment tools risk prioritizing certain groups over others due to biased training
data or unintended algorithmic behavior.
Data privacy and security
Handling sensitive employee and applicant data securely, especially in compliance
with aviation and UAE-specific regulations.
Transparency in decision-making
Difficulty explaining AI decisions in recruitment and performance reviews, leading to
potential mistrust.
Employee adaptability and change
management
Resistance from staff to AI adoption due to concerns about job security and the
relevance of human roles.
Skills gap in HR departments
HR teams require specialized training to interpret AI analytics and incorporate them
into decision-making processes effectively.
Cost of AI integration
Substantial investments in AI systems for HRM, including software development,
hardware, and ongoing updates.
Ethical considerations
Ensuring AI systems respect diversity and inclusivity while maintaining fairness in
decision-making for a globally diverse workforce.
Employee engagement and monitoring
Proactively addressing disengagement risks highlighted by AI while balancing
human-centered approaches in a heavily regulated industry.
6. Strategies supported by AI in recruitment, selection, training,
and development
6.1. Recruitment and selection
AI-Powered Recruitment: The company has adopted AI solutions, particularly
for recruiting new staff at Etihad Airways. These tools facilitate resume screening and
candidate assessment, significantly reducing the time spent on initial evaluations
(Singh and Shaurya, 2021). For example, in 2022, the airline implemented software
for resume parsing and skill mapping, allowing them to align candidates’ skills with
job requirements and enabling HR staff to focus on other activities such as interviews
and engaging candidates. This efficiency is crucial, particularly in an industry where
the speed of hiring impacts overall operational performance.
Challenges of Bias and Fairness: Using AI in recruitment has a problem with
fairness and the possibility of bias. Should the algorithm be trained on data
encompassing previous discriminations like the preferred candidates’ demography or
educational attainment, then the algorithms will extend discriminations (Manroop et
al., 2024). A recent example reported in the tech industry was Amazon launching an
AI recruitment tool that was later abandoned because it was biased against female
candidates. For Etihad, it is crucial to make a point that there must be safeguards
against the use of AI with biases of the society entrenched in them. The recruitment
process is also likely to be influenced by bias, and therefore, AI algorithms require
periodic checks to remove any bias.
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6.2. Training and development
Commitment to employee development: Another important element of Etihad
Airways’ operations is the company’s understanding of its personnel as the main
resource and its focus on training and skill development. Introduced in 2023, the AI
Academy, in collaboration with Microsoft, provides online and instructor-led courses
to increase AI understanding throughout the organization (Etihad Airways, 2022).
This is appropriate in an industry that heavily depends on technology and data analysis
to work efficiently.
Upskilling for future needs: Upskilling employees with AI technologies will help
Etihad prepare its workforce for the future and give it a competitive advantage. The
training programs cover aspects that will enable the employees to use AI tools
optimally, enhancing organizational performance. Such commitment to learning is
crucial, especially with high technology innovation and customer needs dynamics.
Analyzing employee contributions: The AI component of the platform improves
the written ideas and feedback to ensure that the most valuable and beneficial
suggestions are highlighted for further evaluation and consideration. Implementing
this strategy effectively empowers employees and will contribute to Etihad’s strategic
goals of enhancing operational efficiency and customer satisfaction. Nonetheless, for
these initiatives to succeed, it’s essential to have the backing and involvement of
employees throughout the process. Consequently, Etihad must guarantee that the
platform remains accessible and that employees feel encouraged to share their
perspectives, regardless of whether those ideas might challenge existing norms and
processes within the organization.
Innovative AI-driven strategies in HRM
AI is gradually disrupting the HRM models by changing how organizations
manage human capital, attract and select talents, and develop and recruit them (Krović
and Krović, 2023). Since organizations continue encountering new and complex issues
in these spheres, applying AI solutions may improve performance while considering
diversity. This paper reviews current practices, strategizes future activities, and uses
best-performing UAE organizations such as Etihad Airways and Emirates Airlines.
Current challenges in HRM:
i. Talent acquisition: The job market in the UAE is relatively stiff, and the major
issue of talent acquisition arises from the following: The new reality is that the
workforce is diverse, as organizations have to deal with skills deficits, most
sharply where start-up businesses need it, for instance, in technology and
digitalization. Employment and staffing techniques are inadequate when it comes
to identifying the best talents in the market, resulting in long periods of hiring
and expenditure.
ii. Continuing education: Because industries are fast-changing, it is pivotal for
employees to keep learning and developing. However, most organizations find it
difficult to deliver training programs that address all their employees’
requirements. Insufficient creation plans could result in lower employee
participation and increased staff turnover (Malik et al., 2020).
iii. Workplace diversity and inclusion practice: Diversity and inclusion within the
workplace are the right things to do and the right things to do for business. This
Human Resources Management and Services 2025, 7(1), 4132.
14
means that firms’ recruitment and selection procedures must be fair, and the
workplace must embrace diversity. However, achieving this goal is still difficult
for many organizations (Roohani, 2023).
iv. Data privacy and security: Employee data has become sensitive and needs
protection as more organizations implement AI. Every business has to ensure the
protection of the data and meet the regulatory requirements that are in place, like
GDPR and other laws (Almesafri and Habes, 2022).
6.3. Continuous employee learning and development
Human resource management AI-driven learning platforms talent development
is essential to keep good employees around and improve the workforce’s skills.
Companies can use intelligent learning solutions and present employee training
options depending on their skills deficiency and career path. For example, Etihad
Airways has incorporated a digital learning program incorporating artificial
intelligence to deliver content that is most relevant and interesting to the employees
through training sessions. Virtual Reality and augmented reality training using VR and
AR in training can allow learners to engage in interactive and effective training
modalities.
6.4. Fostering diversity and inclusion
AI-enhanced bias detection AI requires further advocacy for diversity and
inclusion, especially in recruiting and selecting employees. Thus, AI algorithms can
study recruitment patterns and detect possible discrimination. For instance, AI systems
in Etihad Airways were launched to analyze recruitment strategies and determine their
adherence to diversity and inclusion policies. Diversity hiring AI can also help write
diverse job descriptions to encourage the best talent to apply. Thus, organizations can
make their job advertisements more inclusive by analyzing the language used and
determining which terms may be discriminatory. These measures can assist companies
in drawing talent from different fields, which improves organizational diversity (Al
Ali and Badi, 2021).
6.5. Measures of data privacy and security
Effective data management standards as employee data plays a crucial role in
organizational operations, organizations need to establish robust and sound data
management standards, particularly when they utilize AI to handle and manage this
data. Companies need to establish benchmarks and standards for collecting, processing,
and storing data, as well as ensuring legal compliance. Etihad Airways implements
robust data management policies and utilizes advanced security technologies to protect
the information of its customers and employees. Employees ought to receive training
on data privacy and security. Organizations ought to promote data privacy by
educating and training their employees on security-related issues. As individuals
increasingly recognize the importance of safeguarding confidential information,
companies can foster a culture of data protection. Some areas that need to be covered
in this training could include detecting phishing scams, managing sensitive security
information, and understanding data protection regulations.
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6.6. Employee development
The implementation of AI-driven strategies will also be beneficial to employee
development. Etisalat can introduce such learning platforms that can be tailored to
employee requirements of skill sets, benefiting their performance in the department
(Kulkov et al., 2024). These may suggest learning modules based on organizational
needs and employees’ career goals. Likewise, the use of AI can help in tracking skill
gap analysis across the workforce. Etisalat’s HR can assess the existing skills of
employees against skills that may be required in the future with technological
advancement and emerging business needs.
The use of predictive recruitment analytics leverages insights on strategies related
to the recruitment side. Etisalat must ensure AI in its systems for HR practices but also
establish guidelines prioritizing transparency, fairness, and accountability. Such
concerns as data security, bias, and privacy can be controlled through regular audit
checks. Adopting AI-driven innovative strategies for workforce management, talent
acquisition, employee development, and recruitment raises efficiency while
encouraging constant development and fairness in HR systems, refer to Table 2.
Table 2. Table of AI-driven strategies for HRM.
HR Area
AI-Driven Strategy
Impact
Example/Implementation
Recruitment &
Selection
AI Resume Screening & Skill Matching
Reduces time for initial candidate
evaluation; better alignment with job
requirements.
Etihad Airways uses software for
resume parsing & skill mapping.
AI-Powered Candidate Assessment
(Cognitive/Behavioral)
Ensures more accurate selection and
reduces human bias.
Etisalat uses facial recognition &
language pattern analysis.
AI Chatbots & Virtual Recruitment
Assistants
Enhances candidate experience through
timely updates and personalized
communication.
AI-driven chatbots at Etisalat for real-
time engagement.
Training &
Development
AI-Powered Learning Platforms &
Personalized Training Programs
Facilitates continuous learning,
addresses skill gaps, and supports career
growth.
Etihad Academy with Microsoft:
Personalized AI-driven training
modules.
VR/AR-Based Training for Real-Life
Simulations
Improves practical skills and readiness
through immersive training.
VR-based training for Etihad cabin crew
and pilots.
AI for Skill Gap Analysis & Career
Path Recommendations
Helps employees improve their
performance based on data-driven
insights into skills and needs.
AI is assessing skill gaps in Etisalat
employees.
Diversity &
Inclusion
AI for Bias Detection in Recruitment &
Selection
Ensures fair hiring practices and
promotes diverse candidate pools.
AI analysis of Etihad’s recruitment
strategies for diversity adherence.
AI for Inclusive Job Descriptions &
Recruitment Messaging
Attracts a broader, more diverse range
of candidates.
AI tools at Etisalat to write inclusive job
descriptions.
Employee
Engagement
AI-Powered Employee Wellness
Programs (Mental Health & Work-Life
Balance)
Supports employee well-being through
personalized stress management and
work-life balance tools.
AI-driven wellness programs and
employee satisfaction monitoring.
Ethical Use of
AI
AI Transparency, Fairness, and Bias
Prevention Measures
Prevents the use of biased algorithms
and ensures ethical decision-making in
HR processes.
Regular audits of AI systems to ensure
fairness and accountability.
Data Privacy &
Security
AI-Based Data Management & Privacy
Compliance
Ensures that employee data is securely
stored and compliant with privacy
regulations.
Etihad Airways is implementing
advanced data protection technologies.
Human Resources Management and Services 2025, 7(1), 4132.
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To evaluate the strategic implications of training in the effective management of
international human resources (HR) for Etisalat UAE, various concerns are
highlighted. Firstly, training programs need to be focused on developing global
competence, which incorporates cross-cultural communicational skills, cultural
compassion, and knowledge about international HR practices. Moreover, efficient
international HR management knows how to adapt to business environments, customs,
and laws on account of local practices. For this, training on cultural sensitivity and
local regulations to safeguard compliance and effective operations is held abroad.
Leadership development is also crucial when implementing global roles (Song et
al., 2024). Such programs are needed to train managers, helping them to lead teams
globally. Further, there is also a need to integrate technology into international HR
training for constant learning experiences. Lastly, key performance indicators are to
be used to know about employee retention rates and cultural integration, helping
Etisalat polish strategies with strategic HR objectives, which ensures growth and
success in competing markets.
7. Practical implications
The practical implications of integrating AI into HRM are significant and
transformative for organizations such as Etihad Airways and Etisalat. By leveraging
AI technologies, HR departments can streamline recruitment processes, reduce the
time spent on resume screening, and enhance candidate selection accuracy. This leads
to faster hiring cycles, improved employee fit, and reduced turnover rates. AI-powered
tools also support personalized employee development by identifying skill gaps and
suggesting targeted training programs, ensuring employees’ growth aligns with
organizational needs.
Additionally, AI can play a pivotal role in fostering diversity and inclusion by
eliminating biases in recruitment and selection processes. With AI systems
continuously analyzing hiring patterns, organizations can ensure a fairer and more
inclusive hiring process. AI also helps in providing real-time feedback, enhancing
employee engagement, and facilitating continuous learning through personalized
training experiences. However, the adoption of AI in HRM requires organizations to
implement robust data protection measures and establish guidelines for transparency
and fairness to avoid ethical issues. Continuous monitoring of AI algorithms for bias
and discrimination is necessary to maintain fairness in recruitment and selection
practices. Furthermore, organizations must ensure that AI does not replace the human
element of decision-making (Upadhyay, 2023), particularly in areas such as employee
relations and leadership development.
8. Societal implications
The adoption of AI in HRM in the UAE has significant social implications,
particularly about fairness, diversity, and privacy.
One of the most profound social benefits of AI in HRM is its potential to promote
diversity and inclusion in recruitment. AI can help mitigate human biases that often
influence hiring decisions based on nationality, gender, or ethnicity. In the UAE,
where the workforce is highly diverse due to the large expatriate population, AI can
Human Resources Management and Services 2025, 7(1), 4132.
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foster a more equitable hiring process, ensuring that all candidates are evaluated fairly
based on their skills and experience. This can contribute to creating more inclusive
organizational cultures and a workforce that better reflects the diverse demographic
landscape of the UAE. AI can help reduce the impact of unconscious bias in
recruitment and performance evaluation processes, which is a key social concern in
the UAE. By utilizing data-driven algorithms that are regularly tested for bias, HR
departments can ensure a more objective approach to candidate selection and
employee assessments. This promotes fairness and equal opportunities, regardless of
a person’s background, thereby enhancing social mobility and creating more socially
inclusive work environments. As AI systems in HRM handle large amounts of
personal data, there are significant social implications regarding privacy and security.
With increasing concerns over data breaches and misuse, it becomes essential for
organizations to implement AI solutions that prioritize data protection. In the UAE,
where data protection laws are evolving, AI tools that ensure compliance with
regulations such as the UAE Data Protection Law help safeguard employees’ personal
information. This fosters trust between employees and employers, contributing to a
healthy social environment within organizations.
AI can help level the playing field for employees by offering personalized
learning experiences based on their individual needs, career goals, and skill gaps. In
the context of the UAE’s vision for a knowledge-based economy, AI-driven training
and development platforms provide employees with access to continuous learning,
irrespective of their backgrounds. This ensures that all employees, regardless of their
current skill set, have the opportunity to grow and advance in their careers, thus
promoting social equality in the workplace.
9. Limitations
The study relies primarily on secondary data, which may limit the ability to
capture firsthand accounts or nuanced perspectives from HR professionals directly
involved in AI integration.
The study is geographically limited to the UAE, and the findings may not be fully
applicable to other regions with different cultural or regulatory contexts. Due to the
relatively recent integration of AI in HRM, some data might be in the early stages of
implementation, which could affect the comprehensiveness of the findings.
10. Conclusion
In conclusion, AI has become a transformative force in HRM, offering significant
benefits to organizations like Etihad Airways and Etisalat in areas such as recruitment,
training, and employee development. AI-powered tools enhance efficiency, reduce
biases, and improve candidate experiences, ultimately contributing to more effective
workforce management. The use of AI for personalized learning and development
ensures that employees can adapt to rapidly changing technological landscapes,
fostering a culture of continuous improvement. Furthermore, AI can drive diversity
and inclusion by analyzing recruitment patterns and supporting fair hiring practices.
However, as AI continues to shape HR practices, organizations must address the
associated challenges, including the risk of biased algorithms, data security concerns,
Human Resources Management and Services 2025, 7(1), 4132.
18
and the ethical implications of AI deployment (Nawaz et al., 2024). Regular audits,
transparent processes, and employee involvement in decision-making can mitigate
these risks (Malin et al., 2024). Additionally, HR professionals must be mindful of the
ethical considerations around AI use to ensure that these technologies serve the
broader goal of fairness, accountability, and employee well-being. As companies like
Etihad Airways and Etisalat lead the way, the strategic integration of AI in HRM can
be a key enabler of organizational success, improving both operational efficiency and
employee satisfaction in the long term.
Conflict of interest: The author declares no conflict of interest.
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