The inaccuracy of user-generated data from digital submission poses significant challenges, leading to inefficiencies and operational overhead. The traditional method is a rule-based valuation that limits contextual and semantic error addressing. The AI-driven Form Validator introduces an advanced AI-driven approach for form validation that integrates advanced language models to perform dynamic, contextually aware validation at the point of submission. Unlike the conventional validation method, the approach provides real-time feedback on user input, guiding them to correct input errors before submission, thus improving the data accuracy and reducing rejection rates. The proposed system evaluates live and historical datasets, identifying inconsistencies with high accuracy. Future work will focus on extending the system’s capabilities to handle dynamic form structures and broader data environments.