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Abstract— Recent research has underscored the pivotal role
of soft skills in navigating the complexities of today's workplace
dynamics. Soft skills encompass a broad spectrum of attributes,
such as effective communication, adept collaboration, nimble
adaptability, and profound emotional intelligence, all of which
are integral to fostering productive team environments and
driving organizational success. Despite their acknowledged
importance, quantifying and evaluating soft skills has
traditionally been hindered by their inherently subjective
nature. However, the emergence of artificial intelligence (AI)
technologies has revolutionized the landscape of skill assessment,
presenting novel opportunities to address these longstanding
challenges. By leveraging AI-powered algorithms, organizations
can now analyze vast datasets encompassing various facets of
human interaction, enabling a more nuanced and objective
evaluation of individuals' soft skill proficiencies. Moreover, AI-
driven assessments offer scalability, allowing for the efficient
evaluation of large cohorts of employees or candidates.
Nonetheless, this intersection of AI and soft skills measurement
is not without its obstacles. Ethical considerations surrounding
data privacy, algorithmic bias, and the potential for automation-
induced job displacement necessitate careful scrutiny and
regulation. Furthermore, the dynamic nature of soft skills
presents a continuous challenge, as individuals must continually
adapt and refine their abilities to meet evolving workplace
demands. Despite these challenges, the synergistic relationship
between AI and soft skills measurement holds immense promise
for the future of talent assessment and development. By
embracing AI-driven approaches, organizations can cultivate a
workforce equipped with the diverse skill set necessary to thrive
in an ever-changing professional landscape.
Index Terms— natural language processing (NLP), artificial
intelligence (AI), human resources (HR).
I. INTRODUCTION
N RECENT years, the integration of Artificial Intelligence
(AI) technologies into various aspects of human resource
management has garnered significant attention 15]. This
trend is particularly pronounced in the realm of assessing soft
skills as shown in Figure 1, where AI holds the promise of
revolutionizing traditional methodologies. One of the key ad-
vantages of AI in assessing soft skills lies in its ability to miti-
gate the shortcomings of conventional approaches. By lever-
aging machine learning algorithms and natural language pro-
cessing techniques, AI systems can analyze large volumes of
data with unprecedented speed and accuracy 1]. This capa-
bility addresses concerns related to biases, inconsistency, and
I
subjectivity often associated with human-led evaluations.
Moreover, AI-driven assessment tools offer scalability, en-
abling organizations to evaluate soft skills across diverse pop-
ulations efficiently. Whether in the context of recruitment,
performance evaluations, or training programs 16]. AI-pow-
ered solutions can streamline the assessment process while
maintaining rigor and reliability 17]. However, the integra-
tion of AI in soft skills assessment is not without its chal-
lenges. Ensuring the fairness and transparency of AI algo -
rithms, for instance, remains a pressing concern. Biases inher-
ent in training data or algorithmic decision-making processes
can inadvertently perpetuate existing inequalities or overlook
crucial nuances in human behavior 18].
Figure 1 - Example of soft skills
Furthermore, the contextual nature of soft skills poses a
unique set of challenges for AI systems. While machine-
learning models excel at pattern recognition and prediction,
they may struggle to capture the subtleties and nuances of hu-
man interaction that characterize soft skills as also demon-
strated in Figure 2. Nevertheless, the potential benefits of AI
in assessing soft skills are substantial. By harnessing the capa-
bilities of AI technologies, organizations can gain deeper in-
sights into the soft skills landscape, identify talent more effec-
tively, and tailor development programs to individual needs.
As the field continues to evolve, further research and
Exploring the role of Artificial Intelligence in assessing soft skills
Matteo Ciaschi
National Research Council (CNR)
email: matteo.ciaschi@cnr.it
ORCID: 0009-0009-5119-3563
Marco Barone
University Giustino Fortunato
University of Studies of Foggia
Email: marco.barone@unifg.it
Proceedings of the 19th Conference on Computer
Science and Intelligence Systems (FedCSIS) pp. 573–578
DOI: 10.15439/2024F2063
ISSN 2300-5963 ACSIS, Vol. 39
IEEE Catalog Number: CFP2485N-ART ©2024, PTI 573Thematic Session: Self Learning and Self Adaptive Systems
innovation will be essential to unlock the full potential of AI
in enhancing our understanding and assessment of soft skills.
Soft skills often referred to as interpersonal or non-technical
skills, play a critical role in professional success across di-
verse industries. While hard skills are essential for specific
tasks, soft skills are equally important for effective communi-
cation, teamwork, and leadership. However, quantifying and
evaluating soft skills have been traditionally elusive due to
their qualitative and context-dependent nature. This paper in-
vestigates the evolving landscape of soft skills assessment
with the integration of artificial intelligence (AI) technolo-
gies.
Figure 2 - Hard Skills vs Soft Skills
II. THE IMPORTANCE OF SOFT SKILLS
Soft skills, a diverse set of attributes encompassing com-
munication, empathy, creativity, and problem-solving, have
garnered increasing recognition and value from employers.
Studies consistently demonstrate that individuals possessing
robust soft skills not only thrive in team environments but also
exhibit leadership potential and adaptability to change with
greater ease. Despite their pivotal role, soft skills have histor-
ically received scant attention in both educational curricula
and hiring processes. The emergent emphasis on soft skills
reflects a fundamental shift in the priorities of modern work-
places. Employers recognize that technical proficiency alone
does not suffice in today’s dynamic and interconnected busi-
ness landscape. Instead, the ability to communicate effec-
tively, collaborate harmoniously, and think creatively has be-
come indispensable for fostering innovation, driving produc-
tivity, and maintaining competitive advantage 4]. Moreover,
the growing complexity of global markets and the rise of dig-
ital technologies have intensified the demand for individuals
capable of navigating ambiguity and uncertainty. Soft skills,
characterized by their flexibility and adaptability, play a crit-
ical role in enabling individuals to thrive amidst rapid change
and disruption. Yet, despite their demonstrable impact on or-
ganizational success, soft skills remain underdeveloped in
many individuals. Traditional education systems, focused pri-
marily on imparting technical knowledge, often neglect the
cultivation of essential interpersonal and intrapersonal com-
petencies. Similarly, hiring practices frequently prioritize
hard skills over soft skills, overlooking the pivotal role the
latter play in fostering collaboration, innovation, and resili-
ence within teams. Recognizing the significance of soft skills
is the first step towards addressing this gap. By fostering a
culture that values and nurtures these competencies, organi-
zations can unlock the full potential of their workforce and
cultivate a dynamic and resilient workplace environment.
Embracing this holistic approach to talent development is es-
sential for thriving in an increasingly complex and intercon-
nected world.
III. CHALLENGES IN SOFT SKILLS MEASUREMENT
Measuring soft skills presents a complex endeavor due to
their inherent subjectivity and multifaceted nature. Unlike
hard skills, which can be objectively assessed through stand-
ardized tests or quantifiable performance metrics, soft skills
such as communication, teamwork, and emotional intelli-
gence are often more abstract and context-dependent, making
their evaluation inherently challenging.
One of the primary obstacles in measuring soft skills is the
inadequacy of traditional assessment methods to capture the
full spectrum of these skills accurately. Conventional ap-
proaches, such as self-assessment surveys or observation-
based evaluations, may lack the sensitivity to discern subtle
variations in individuals’ soft skill proficiency. Consequently,
there exists a risk of overestimating or underestimating an in-
dividual’s soft skills competency, leading to unreliable results.
Moreover, there is often a noticeable dissonance between self-
reported soft skills and objective assessments conducted by
peers or supervisors. Individuals may have biases or lack self-
awareness when assessing their soft skills, resulting in dis-
crepancies between perceived and actual proficiency levels.
This discordance underscores the importance of incorporating
diverse perspectives and utilizing multiple assessment meth-
ods to validate soft skills measurement.
Furthermore, cultural, and individual differences add another
layer of complexity to soft skills assessment. Cultural norms
and expectations can significantly influence how soft skills
are expressed and valued, leading to variations in interpreta-
tion and evaluation across different contexts. Similarly, indi-
vidual differences in personality, background, and experi-
ences can impact the manifestation and effectiveness of soft
skills, further complicating measurement efforts.
Addressing these challenges requires a multifaceted approach
that acknowledges the dynamic and context-dependent nature
of soft skills. Innovative assessment methods, such as immer-
sive simulations, real-world scenarios, and behavioral obser-
vations, offer promising avenues for capturing the intricacies
of soft skills in diverse contexts. Additionally, integrating
technology, such as AI and data analytics, can provide valua-
ble insights and enhance the reliability of soft skills assess-
ment tools.
574 PROCEEDINGS OF THE FEDCSIS. BELGRADE, SERBIA, 2024
Ultimately, advancing the measurement of soft skills necessi-
tates ongoing collaboration between researchers, educators,
employers, and other stakeholders to develop robust evalua-
tion frameworks that are sensitive to individual differences,
culturally inclusive, and reflective of real-world demands 2].
By overcoming these challenges, we can better understand,
develop, and leverage soft skills to empower individuals and
drive success in various personal, academic, and professional
domains.
IV. AI-POWERED SOLUTIONS
Recent advancements in AI have applications in many ar-
eas including risk management [21], education, communica-
tion, healthcare [22], robotics etc. AI tools including natural
language processing (NLP), machine learning, and affective
computing, offer promising avenues for addressing the chal-
lenges of soft skills assessment [20]. NLP algorithms, for in-
stance, have demonstrated remarkable capabilities in analyz-
ing both written and spoken communication, enabling the in-
ference of qualities such as clarity, persuasiveness, and emo-
tional tone with increasing accuracy. These algorithms can
sift through vast amounts of text or speech data, extracting
meaningful insights that contribute to a more nuanced under-
standing of an individual’s communication skills 3]. Machine
learning models, fueled by large datasets, have emerged as
powerful tools for identifying patterns in behavior and com-
munication that are indicative of specific soft skills. By ana-
lyzing diverse sets of interactions, these models can discern
subtle cues and nuances that traditional assessment methods
might overlook. Through continuous learning and refinement,
machine learning algorithms can adapt to evolving contexts
and provide increasingly accurate assessments of individuals’
soft skill proficiencies 5].
Affective computing techniques represent another frontier in
soft skills assessment, offering the ability to analyze non-ver-
bal cues such as facial expressions, voice intonation, and
physiological signals. By leveraging advancements in com-
puter vision and signal processing, affective computing sys-
tems can decode emotional states, attitudes, and interpersonal
dynamics, shedding light on aspects of emotional intelligence
and social competence that are essential for effective commu-
nication and collaboration.
By integrating these AI-powered solutions into soft skills as-
sessment frameworks, researchers and practitioners can lev-
erage the vast capabilities of technology to overcome
longstanding challenges. These innovations not only enhance
the accuracy and reliability of soft skills evaluation but also
enable more personalized and adaptive approaches that cater
to individual differences and diverse contexts. As AI contin-
ues to evolve, the potential for transformative advancements
in soft skills assessment becomes increasingly apparent, of-
fering new opportunities to unlock the full potential of indi-
viduals and organizations alike 6].
V. APPLICATIONS IN TALENT ASSESSMENT AND
DEVELOPMENT
The integration of AI-driven soft skills assessment tools rep-
resents a transformative leap forward in talent management
practices, offering organizations a wide array of applications
across recruitment, employee training, and performance eval-
uation as presented in Figure 3. These innovative tools har-
ness the power of AI to streamline processes, enhance objec-
tivity, and cultivate a workforce equipped with the essential
soft skills demanded by today’s rapidly evolving business
landscape.
Beginning with recruitment, AI-driven screening processes
have revolutionized traditional candidate selection methods.
By leveraging sophisticated algorithms to analyze vast da-
tasets comprising resumes, cover letters, and online assess-
ments, these tools can swiftly identify candidates whose soft
skill profiles align closely with the specific needs and objec-
tives of the organization. The efficiency of automated screen-
ing not only accelerates the hiring process but also enables
recruiters to focus their efforts on engaging with candidates
who demonstrate the requisite communication, collaboration,
and emotional intelligence competencies. Furthermore, AI-
powered interview platforms equipped with natural language
processing capabilities offer deeper insights into candidates’
soft skills by analyzing linguistic nuances, communication
styles, and behavioral cues, providing invaluable information
to inform hiring decisions and ensure optimal candidate fit
7]. Moving beyond recruitment, AI continues to play a piv-
otal role in shaping employee development initiatives. Per-
sonalized feedback generated by AI systems provides individ-
uals with granular insights into their soft skill strengths and
areas for improvement, empowering them to take ownership
of their professional growth journey. Through tailored learn-
ing recommendations and resources, employees can embark
on targeted skill development paths that align with their
unique career aspirations and organizational goals. Addition-
ally, AI-driven coaching platforms leverage real-time data an-
alytics to offer continuous support and guidance, enabling in-
dividuals to refine their soft skills in response to evolving
workplace challenges and opportunities 8].
In organizational settings, AI-powered analytics serve as in-
dispensable tools for talent management and performance
Figure 3 - Applications of Artificial Intelligence
MATTEO CIASCHI, MARCO BARONE: EXPLORING THE ROLE OF ARTIFICIAL INTELLIGENCE IN ASSESSING SOFT SKILLS 575
evaluation. By analyzing team dynamics, communication pat-
terns, and leadership effectiveness, these analytics offer com-
prehensive insights into the collective soft skill proficiency
within teams and across departments. Armed with this inval-
uable information, organizations can identify opportunities to
optimize team performance, allocate resources strategically,
and foster a culture of continuous learning and development.
Moreover, AI-driven performance evaluations offer objective
assessments of employees’ soft skill competencies, comple-
menting traditional appraisal methods and ensuring fairness
and transparency in talent assessments 9].
The integration of AI-driven soft skills assessment tools rep-
resents more than just a technological advancement; it signi-
fies a fundamental shift in how organizations approach talent
management and development in the digital age. By harness-
ing the transformative potential of AI, organizations can un-
lock the full potential of their workforce, cultivate a culture of
excellence, and gain a competitive edge in today’s fast-paced
and increasingly complex business environment. As AI tech-
nologies continue to evolve and mature, the possibilities for
enhancing talent management practices are limitless, paving
the way for a future where organizations thrive by leveraging
the unique strengths and capabilities of their human capital.
In recent years, the integration of artificial intelligence (AI)
technologies into various domains has revolutionized tradi-
tional approaches to problem-solving and decision-making
19]. One area where AI has made significant strides is in Hu-
man Resources (HR), where it has transformed talent man-
agement practices (Figure 4). This paper explores a compel-
ling example of AI application in HR: the use of AI-driven
recruitment tools. By leveraging AI algorithms, organizations
can streamline the recruitment process, enhance candidate
sourcing, and improve decision-making in talent acquisition.
This article delves into the benefits, challenges, and implica-
tions of AI adoption in HR, shedding light on how these ad-
vancements are reshaping the future of workforce manage-
ment
The advent of artificial intelligence (AI) has brought about a
seismic shift in the field of Human Resources (HR), offering
innovative solutions to age-old challenges in talent manage-
ment. With AI’s ability to analyze vast amounts of data and
derive actionable insights, organizations are reimagining their
HR processes to drive efficiency, effectiveness, and inclusiv-
ity. One notable application of AI in HR is its utilization in
recruitment, where AI-powered tools are revolutionizing how
companies identify, attract, and select top talent. This article
explores the transformative impact of AI in recruitment, ex-
amining its potential to optimize hiring practices and unlock
new avenues for talent acquisition.
Traditionally, the recruitment process has been labor-inten-
sive and time-consuming, often fraught with biases and inef-
ficiencies. However, AI-driven recruitment tools offer a par-
adigm shift in how organizations approach talent acquisition.
By leveraging machine learning algorithms, these tools can
analyze resumes, assess candidate profiles, and predict job fit
with unprecedented accuracy. Furthermore, AI enables organ-
izations to tap into diverse talent pools, mitigating uncon-
scious biases and promoting inclusivity in hiring practices.
From automated candidate screening to personalized job rec-
ommendations, AI streamlines every stage of the recruitment
journey, empowering HR professionals to make data-driven
decisions and optimize their hiring strategies.
The integration of AI in recruitment yields a myriad of bene-
fits for organizations. Firstly, AI-driven tools enhance the ef-
ficiency of the hiring process by automating repetitive tasks,
such as resume screening and candidate matching, freeing up
HR professionals to focus on strategic activities. Moreover,
AI enables organizations to identify high-potential candidates
more effectively, leading to better-quality hires and reduced
time-to-fill positions. Additionally, AI-driven recruitment
platforms facilitate a seamless candidate experience, provid-
ing personalized interactions and timely feedback throughout
the application process. By optimizing recruitment practices,
AI empowers organizations to build diverse, high-performing
teams that drive innovation and competitiveness in the mar-
ketplace. Despite its transformative potential, the adoption of
AI in recruitment is not without challenges. Ethical consider-
ations, such as data privacy and algorithmic bias, require care-
ful attention to ensure fairness and transparency in decision-
making. Moreover, the reliance on AI-driven tools may raise
concerns about job displacement and the humanization of the
hiring process. To address these challenges, organizations
must prioritize ethical AI governance, invest in employee up-
skilling, and foster a culture of transparency and trust in AI-
driven recruitment practices.
Looking ahead, the integration of AI in recruitment heralds a
new era in talent acquisition, characterized by data-driven de-
cision-making, enhanced candidate experiences, and greater
workforce diversity. As AI continues to evolve, HR profes-
sionals must adapt their practices to harness the full potential
of these technologies. By embracing AI-driven recruitment
tools, organizations can gain a competitive edge in attracting
and retaining top talent, positioning themselves for success in
the digital age 10].
The application of AI in recruitment represents a watershed
moment in the evolution of HR practices. By leveraging AI-
driven tools, organizations can optimize their recruitment pro-
cesses, improve decision-making, and foster a more inclusive
Figure 4- Applications of AI in HR
576 PROCEEDINGS OF THE FEDCSIS. BELGRADE, SERBIA, 2024
and diverse workforce. However, to realize the full benefits
of AI in recruitment, organizations must navigate ethical con-
siderations, address potential biases, and invest in employee
development. Ultimately, AI holds the promise of transform-
ing talent acquisition, enabling organizations to build agile,
future-ready teams that drive innovation and sustainable
growth 11].
VI. DISCUSSION
The integration of artificial intelligence (AI) into the as-
sessment of soft skills has become a focal point in both re-
search and practice, offering innovative solutions to
longstanding challenges in talent evaluation. However, this
advancement also brings to the forefront a host of ethical con-
siderations that demand scrutiny. Chief among these concerns
are issues related to privacy, fairness, and algorithmic bias. In
the pursuit of capturing nuanced aspects of human behavior,
AI-driven soft skills assessment often relies on the collection
and analysis of sensitive personal data, ranging from verbal
cues and speech patterns to non-verbal cues such as facial ex-
pressions and body language. Such data collection practices
necessitate a robust framework grounded in transparency and
consent to safeguard individuals’ privacy rights and ensure
their autonomy in the process. Moreover, the inherently com-
plex nature of human behavior poses significant challenges in
developing AI algorithms that can accurately interpret and
evaluate soft skills without introducing biases. The risk of al-
gorithmic bias, whereby AI systems unintentionally discrim-
inate against certain individuals or groups, underscores the
importance of incorporating diversity and inclusivity consid-
erations into the design and implementation of these technol-
ogies. To address these ethical concerns, stakeholders must
prioritize proactive measures aimed at mitigating bias and
promoting fairness in AI-driven soft skills assessment. This
includes adopting strategies to diversify training data, con-
ducting regular audits of algorithmic decision-making pro-
cesses, and implementing mechanisms for ongoing monitor-
ing and evaluation. Despite these challenges, the potential
benefits of AI in advancing soft skills assessment are substan-
tial. By harnessing the power of machine learning and natural
language processing techniques, AI systems can offer insights
into individuals’ interpersonal communication, collaboration,
adaptability, and other critical soft skills with unprecedented
accuracy and granularity. Looking ahead, future research en-
deavors should focus on refining AI models through continu-
ous learning mechanisms that enable adaptation to evolving
patterns of human behavior. Additionally, the integration of
multimodal data sources, such as combining textual and vis-
ual information, holds promise for enhancing the comprehen-
siveness and reliability of soft skills evaluations 12].
Collaboration among interdisciplinary teams comprising AI
researchers, psychologists, educators, and industry stakehold-
ers is paramount in driving innovation and maximizing the
potential impact of AI on workforce development. By foster-
ing an ecosystem of knowledge exchange and collaboration,
we can collectively address the complex challenges and op-
portunities inherent in the intersection of AI and soft skills
assessment. In the rapidly evolving landscape of the modern
workplace, the demand for soft skills continues to grow,
fueled by the increasing emphasis on teamwork, creativity,
and adaptability. In this context, AI represents not only a tool
for improving efficiency and objectivity in talent manage-
ment but also a catalyst for promoting a culture of continuous
learning and development. By leveraging AI technologies
thoughtfully and ethically, organizations can unlock new pos-
sibilities for nurturing talent, driving innovation, and foster-
ing inclusive and thriving work environments.
VII. CONCLUSION
In conclusion, the symbiosis between AI and soft skills
measurement heralds a new era in talent assessment and de-
velopment. As the demand for soft skills continues to rise in
the rapidly evolving workplace landscape, AI presents un-
precedented opportunities for transforming how these skills
are measured and evaluated. By harnessing the capabilities of
AI technologies, organizations can delve deeper into individ-
ual and team competencies, transcending the limitations of
traditional assessment methods. AI-driven analyses offer nu-
anced insights into the subtle nuances of human interaction,
providing stakeholders with a richer understanding of em-
ployees’ strengths and areas for improvement 13].
Moreover, AI-powered assessments enable more informed
decision-making in talent management, facilitating the align-
ment of skills with organizational objectives and the strategic
deployment of human capital. By identifying and nurturing
talent with the requisite soft skills, organizations can cultivate
high-performing teams capable of driving innovation and
adaptability in today’s dynamic business environment.
Furthermore, the integration of AI in soft skills measurement
promotes a culture of continuous learning and development.
By providing individuals with personalized feedback and tar-
geted interventions, AI-driven platforms empower employees
to refine their soft skills iteratively, fostering professional
growth and resilience. This emphasis on lifelong learning not
only enhances individual performance but also contributes to
the overall agility and competitiveness of the organization.
14].
However, it is essential to approach the deployment of AI in
soft skills measurement with caution and mindfulness. Ethical
considerations, including privacy concerns and algorithmic
bias, must be carefully addressed to ensure fairness and trans-
parency in the assessment process. Additionally, organiza-
tions must prioritize the upskilling and reskilling of employ-
ees to navigate the evolving technological landscape and mit-
igate the risk of job displacement.
In essence, the convergence of AI and soft skills measurement
represents a paradigm shift in how we perceive and cultivate
talent in the modern workplace. By embracing AI-driven ap-
proaches, organizations can unlock the full potential of their
workforce, driving sustainable growth and competitive ad-
vantage in an increasingly complex and interconnected world.
MATTEO CIASCHI, MARCO BARONE: EXPLORING THE ROLE OF ARTIFICIAL INTELLIGENCE IN ASSESSING SOFT SKILLS 577
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