APPLICANT-SIDE AI AGENTS AND THE REDISTRIBUTION OF AGENCY IN ALGORITHMIC LABOR MARKETS: A DESIGN SCIENCE STUDY OF JOB SEARCH AUTOMATION AND CSR IN RECRUITMENT

Research Progress
Pre-Publication
90%

Artificial intelligence is reshaping recruitment, yet research focuses mainly on employer-side systems. Using Design Science Research and an Automation–Augmentation–Agency framework, this study develops and preliminarily evaluates an author-built, human-supervised applicant-side AI agent implemented in n8n. The artifact integrates job discovery, deduplication, fit screening, structured review, applicant approval, cover-letter generation, notification, and tracking. Testing across four job categories and 40 configured queries produced 1,828 vacancy records; 799 (43.7%) passed category-specific thresholds. Manual review found no obvious fabricated vacancies or claims, while generated cover letters were generally coherent and tailored but still required human review. The artifact reduced search burden while preserving information access, decision autonomy, and strategic control, contributing to AI recruitment, Design Science Research, and CSR scholarship.