Democratizing AI: Current Landscape and Framework Development for No-Code AI Adoption

This paper talks about the need for making artificial intelligence (AI) available and easily accessible across organizational teams through no-code interfaces. Despite the widespread use of AI technologies, an expertise gap prevents its adoption beyond data science or highly technical teams. Through analysis of public datasets, industry surveys, and comparative evaluation of existing frameworks, this paper develops a comprehensive model for AI democratization that balances accessibility with governance. The proposed framework integrates technical architecture considerations with organizational change management principles, creating a way for cross-functional AI implementation. Findings indicate that successful democratization requires not only simplified interfaces but also structured knowledge transfer mechanisms, appropriate governance structures, and cultural adaptation strategies. This research contributes to both theoretical understanding of AI democratization and practical implementation guidance for organizations seeking to broaden AI utilization across diverse departmental contexts.