An AI-Driven Closed-Loop Framework for Cross-Domain Collaboration Integrating Vocational Education and Economic Management

With the rapid advancement of the digital economy, vocational education and economic management are undergoing fundamental transformation, requiring the elimination of data silos and cross-domain collaboration. To address challenges such as system separation, decision delays, privacy barriers, and limited model interpretability, this study proposes an AI-driven “Perception–Analysis–Action” closed-loop framework. The perception layer integrates multi-source data from learning, market, and financial systems; the analysis layer, based on graph neural networks and reinforcement learning, explores cross-domain relationships; and the action layer achieves real-time personalized learning paths, adaptive budgeting, and risk alerts with federated learning and differential privacy ensuring security. Experiments on 600,000 records show improved accuracy (2–5%), latency reduction (to 19 ms), and better interpretability, validating the framework's role in promoting intelligent and transparent cross-domain collaboration.