<p>The growing digitalization of academic credentials requires safe, effective, and reliable verification mechanisms to avoid forgery and exploitation. This study puts forward a Blockchain-Enhanced AI-Powered Academic Credential Authentication System that combines Convolutional Neural Networks (CNN) for authentic image-based verification of academic certificates with Ethereum blockchain technology for tamper-proof and decentralized record maintenance. The framework employs the publicly available Certificate Forgery Dataset from Kaggle, which contains images of genuine and forged academic certificates used to train and evaluate the CNN-based document authenticity verification model. Optical Character Recognition (OCR) also extracts text data for verification, enhancing accuracy and resilience. Experimental outcome proves that OCR accuracy was enhanced from 70 to 90%, and efficiency up to 88%. The CNN model had a classification accuracy of 99.15%, precision of 99.10%, recall of 99.04%, and F1-score of 99.01%. Blockchain integration secures storage of cryptographic hashes through smart contracts, streamlining issuance, verification, and revocation functions with tamper-proof transparency. The system lowers transaction gas fees by about 50% relative to traditional Ethereum fees and keeps tamper resistance and smart contract enforcement scores at around 95%. This hybrid AI-blockchain system presents a scalable, transparent, and secure academic credential authentication solution that is flexible to various educational environments.</p>