Securing sensitive data is essential in the modern digital era due to the rise of cyber threats. Here we are investigating the necessity of integrating graph theory, particularly graph labeling and coloring, with Artificial Intelligence (AI) for digital information validation and authentication through embedding and signature verification. Traditional cryptographic methods face challenges in adapting to evolving cyber threats, necessitating innovative solutions. The present research explores how AI enhances key generation, automates false node insertion, and integrates encryption techniques with graph structures to ensure data authenticity, integrity, and security. We aim to establish a robust framework for verification, authentication, and validation using graph-based cryptographic techniques. The proposed model addresses how AI optimizes security protocols and embeds authentication signatures within graph structures to provide enhanced protection against attacks such as Man-in-the-Middle (MiM) and brute-force attacks. This paper provides detailed analysis, algorithms, flowcharts, and experimental validation signifying the effectiveness of AI-driven cryptographic methods. There is scope for further upgradation of this research soon by enhancing AI-based massive encryption for information security in the digital platform.