Introduction
A regional government faced growing challenges in connecting its citizens with the right career opportunities and training programs. The existing services lacked personalization and accessibility, creating a disconnect between job seekers, employers, and educational institutions. The government needed a digital solution that would analyze user profiles, align individual skills with labor market trends, and provide tailored career guidance to bridge skill gaps effectively.
VE3’s Approach
VE3 adopted a collaborative, phased approach to develop a proof-of-concept (POC) platform that incorporated cutting-edge AI and user-centric design principles
- Conducted workshops with policymakers, employers, and training providers to identify critical challenges in the career services ecosystem.Â
- Gathered user input from job seekers to ensure the platform addressed their needs
- AI-Powered Recommendation Engine: Built a machine learning model using TensorFlow to provide career suggestions based on user input, such as education level, work experience, and location. The model utilized regional labor market data to ensure relevance.Â
- Interactive Career Quiz: Designed an engaging quiz using React.js and Python to assess user interests, strengths, and preferences, mapping them to specific job roles and industries.Â
- Employer and Training Provider Integration: Created dedicated portals for businesses to upload job postings and for training providers to showcase their programs.Â
- Integrated external labor market datasets (e.g., EMSI and O*NET) to ensure accurate and up-to-date insights for job seekers.Â
- Incorporated AI-based predictive analytics to identify emerging trends in the labor market
- Conducted multiple user testing phases, gathering feedback from job seekers and employers.Â
- Refined the user interface to make it accessible for all demographics, including those with limited digital literacy.Â
Results
The POC successfully demonstrated the potential to transform career guidance in the region:
- User Outcomes: 70% of pilot participants reported high satisfaction with the personalized career recommendations they received.Â
- Efficiency Gains: Average job search time was reduced by 25%, enabling users to find opportunities faster.Â
- Employer Engagement: Employers experienced a 40% increase in the number of qualified applicants for their postings.Â
- Scalability: The platform’s modular design allowed the regional government to scale its deployment seamlessly.Â