The rapid adoption of generative artificial intelligence (GenAI) in legal technology has made the design of trusted user interfaces (UIs) for contract lifecycle management (CLM) systems a pressing research concern. Despite the growing availability of AI-powered CLM platforms, there remains a significant gap in formalized architectural and methodological frameworks that govern how such interfaces should be structured to satisfy transparency, explainability, and human oversight requirements. This study investigates the architectural principles and methodological patterns underlying trusted UI design for GenAI-assisted contract preparation, review, and approval systems. The research applies a systematic literature review, comparative analysis of existing CLM platforms, and content analysis of technical specifications. Key results include a proposed four-layer UI architecture, a human-in-the-loop confidence routing model, and a trust signal component taxonomy, all grounded in evidence from industry deployments and peer-reviewed sources. The study concludes that integrating structured explainability overlays, role-aware access controls, and audit-traceable interactions offers a structured methodological basis for trusted GenAI interfaces. Practitioners in legal technology, enterprise software architecture, and AI governance may find the presented framework useful as a reference architecture and evaluation aid.