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ARTIFICIAL INTELLIGENCE (AI) APPLICATION FOR CAREER
GUIDANCE AND JOB MATCHING FOR UNIVERSITY GRADUATES
PhD. Do Quoc Phong
European International University
MSc, Ha Quoc Viet
HCMC University of Technology, VNU-HCMC
Abstract
Artificial Intelligence (AI) is transforming multiple sectors, including education and
the labor market. Particularly in the field of career services, AI enables personalized career
orientation, skill counseling, and precise job matching for students and recent graduates.
Leveraging big data analytics, machine learning, and natural language processing, AI
systems can assess competencies, identify interests, forecast career trends, and propose
optimal development paths for individuals.
According to reports by the World Economic Forum [1] and LinkedIn [2], AI is
expected to play a key role in shaping the future workforce, especially in the context of an
increasingly competitive job market and rapidly evolving skill demands.
Theoretically, this study provides a systematic review of AI’s potential in career
guidance. Practically, it proposes integrated AI models for personalized counseling and
effective, sustainable job matching for graduates.
Keywords: Artificial Intelligence (AI), career guidance, job matching, students, digital
transformation.
1. Introduction
At the Industrial Revolution 4.0, the demand for high-quality human resources continues to
rise. However, recent graduates often face challenges such as lack of career direction,
insufficient skills, and limited access to employers. Traditional career guidance methods are
Figure 1. The impact of AI on the future workforce (The
Future of Jobs Report 2025)
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often generic and outdated, lacking the personalized approach required to meet real-world
demands.
AI has emerged as a promising solution, capable of deeply analyzing user behavior and
forecasting career trends. AI systems not only offer personalized career advice based on
individual profiles but also proactively match candidates with job opportunities and support
essential skill development via smart learning platforms.
In Vietnam, the National Strategy on AI Research, Development, and Application to 2030
(Decision 127/QD-TTg) emphasizes the importance of integrating AI into education and the
labor market to enhance national competitiveness. However, its implementation remains
fragmented, especially in graduate career support. [3]
2. Research Content
2.1. Current Limitations
Current career guidance and job matching systems for students face several notable
challenges:
Lack of Personalization: most career counseling is delivered via large-scale workshops or
seminars, making it difficult to tailor content to individual students’ strengths, interests, and
career goals. Personalized assessments, one-on-one mentoring, and individualized career
roadmaps remain rare.
Figure 2. Global AI market in education by region, 2016–2027 (in million USD)
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Figure 3. Training in small and medium-sized enterprises and innovative startup training
needs improvement [4]
Skill Gap Between Education and Employment: Despite frequent curriculum updates,
graduates often lack soft skills and practical experience. Employers report deficiencies in
communication, teamwork, critical thinking, and digital tools proficiency among fresh
graduates.
Outdated Career Trend Information: As new jobs and skills emerge, both students and career
service units struggle to keep up due to the absence of real-time analytics platforms. Manual
updates via news or general forums are often too slow, leading to a mismatch between
academic training and job market demands.
Inefficient Job Matching: Traditional recruitment channels rarely offer accurate job
suggestions based on a student’s qualifications and aspirations. As a result, students often
apply indiscriminately, reducing their chances of finding optimal opportunities.
To overcome these issues, higher education institutions should integrate technology - such
as online assessment systems, AI - based job suggestions, and real-time job updates - with
personalized mentoring, small - group workshops, and selective internship programs.
Strengthening collaboration with businesses to align training and practical experiences is
also essential.
2.2. Innovation Need
In today’s highly competitive global labor market, integrating AI into career guidance and
job matching is not only inevitable but also presents breakthrough opportunities for both
students and employers.
AI enables deeply personalized career orientation by analyzing academic records, skill
assessments, internships, interests, and labor market trends to generate customized career
Figure 4. Today's labor market is undergoing rapid and
continuous changes. [5]
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maps. This guides students through defined pathways, aligning strengths with market needs
and minimizing time wasted on mismatched careers.
Moreover, AI optimizes job recommendations through intelligent algorithms [6], using deep
learning models to suggest jobs based on skill compatibility, work history, and even
company culture—beyond simple keyword matching.
Table 1: Comparison between current research models and popular tools at home, abroad
Criteria
Model in This Study
Common Domestic/International
Studies
Machine Learning
Algorithms
Multi-model approach:
Random Forest, XGBoost,
CatBoost, MLP, fine-tuned
with Optuna
Hyperparameter
Tuning
Utilizes Optuna for optimizing
Random Forest (improves
accuracy, reduces RMSE)
Interpretability
Analyzes feature importance,
uses 3D simulations to
visualize input factor impacts
Simulation
Capability
Includes 3D modeling of
relationships among budget
allocation – graduation rate –
students
Data Utilization
Mix of numerical and
categorical data; enables
models to handle multi-
dimensional input
Generalization &
Scalability
Modular architecture, easily
extensible with region, field of
study, tuition level, etc.
AI also facilitates lifelong skill development by recommending relevant courses and
certifications throughout one’s career [7]. For instance, a junior programmer lacking
cybersecurity skills may be automatically recommended a security course after completing a
related project.
From the employer's perspective, AI dramatically improves recruitment efficiency by
automating resume filtering and conducting multidimensional candidate evaluations based
on predetermined criteria such as qualifications, soft skills, salary expectations, and cultural
fit.
3. AI Applications in Career Guidance and Job Matching
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3.1. Mechanism and AI role
An AI-powered career guidance and job matching system continuously collects and updates
a student's academic
records, skills (both
technical and soft),
career preferences,
internship
experiences, and
extracurricular
activities. Using
clustering, regression,
or decision trees,
machine learning
algorithms generate a
digital "competency
card" that identifies
strengths and areas for improvement [8].
Deep learning models combine this data with labor market information (e.g., trending skills,
average salaries, hiring patterns) to construct personalized career maps, suggesting
timelines, certifications, real-world projects, and suitable courses. When job hunting begins,
the system uses semantic matching and ranking techniques to align student profiles with job
listings and offers tools like CV drafting, cover letter writing, and interview simulations
with voice analysis and personalized feedback.
AI continues to act as a virtual career coach, reminding students of deadlines, sharing skill
trend reports, and collecting post-interview feedback to refine recommendations.
3.2. Integrated AI Ecosystem
A comprehensive AI-powered career guidance ecosystem consists of five core components
[9]:
1. Automated Assessment Platform: Gathers and analyzes cognitive, personality,
and skill data via online tests.
2. Career Pathway Builder: Uses assessment results and market data to map
personalized career paths.
3. Smart Job Recommendation System: Matches resumes and job descriptions
semantically, with real-time updates.
4. 24/7 Chatbot Advisor: Assists with CV writing, interview practice, and course
suggestions.
5. AI-Integrated Career Social Network: Fosters student-employer connections
and organizes networking events.
4. Implementation Challenges
Despite its promise, deploying AI in career services involves key challenges [10]:
Figure 5. The application of AI in predicting career development is
not limited by physical conditions. [11]