Pathfinder AI: Decentralizing Career Mobility for the Underserved and Next-Gen Workforce
The developments in artificial intelligence (AI) and beginning of a decentralized platform offers the possibility to replace the welfare model of career mobility for underserved populations and next generation workforce. The focus of this study is to analyze the contribution of Pathfinder AI, an AI aimed decentralized platform designed to resolve the barriers marginalized workers face when it comes to gaining career advancement opportunities. Taking a hold of AI tools and block chain technologies Pathfinder AI intends to eliminate the barriers to job opportunity access democratizing access to job opportunities, personalize career development pathway and knock down systemic biases in recruitment process. The study tests this relationship between the usage of AI tools, career mobility, as well as job search success with a survey-based methodology involving 400 participants from various backgrounds. An analysis is done by using SPSS to conduct descriptive statistics, regression analysis, as well as Chi-square tests to evaluate how Pathfinder AI can enhance career outcomes for underserved workers. Results indicate that the more AI tools an employee utilizes, the greater likelihood they have of a change in career mobility (B = 0.56, p < 0.001) and success in job search (r = 0.47, p < 0.01). Participants using Pathfinder AI also saw a 15% boost over Those not using the Platform when using the Platform offering. The results indicate that Pathfinder AI holds a very large positive effect on career mobility for employees for whom fewer traditional career advancement resources are available. It is decentralized that it creates a greater level of transparency, trust and fair job matching for the marginalized groups. The final point of this study is that AI driven decentralized platform can change the future of work and allow all workers to have equal access to career growth and economic mobility irrespective of the background they come from.
Authors
- Md. Abu Sayem (ORCID: https://orcid.org/0000-0001-6690-0982)
- Rajesh Sikder
- Ahmed Selim Anwar
- M Kar
- Fariba Chowdhury
- Shuvo Dutta
Publication Details
- Journal
- Cognizance Journal of Multidisciplinary Studies
- Published
- 2025-04-21
- DOI
- https://doi.org/10.47760/cognizance.2025.v05i04.017
- Primary Topic
- Engineering Education and Technology
- Type
- article
- Field-Weighted Citation Impact
- 0.00