The purpose of this research is to create an integrated framework as one single environment that can automatically and efficiently track compliance in the process of GDPR by embedding AI, blockchain technology, and smart contracts into the integrated framework. This is an application framework that has been suggested as a way of closing the gap between legal requirements and technical solutions, as the amount of data continues to increase rapidly and cyber threats are becoming increasingly sophisticated. Our proposed system is based on a newly developed hybrid architecture, which involves exploiting possible threats or vulnerabilities and extracting security-related features from the text data using the Secure BERT model. Apart from that, a high level of accuracy is obtained by using a Random Forest classifier to identify the risk level of cybersecurity in real time. Moreover, Hyperledger Fabric is able to provide a secure distributed ledger that offers an audit trail and transparency of transactions, allowing transactions to be traced back to their origin, and smart contracts are also being applied here to automate the requirements of GDPR; requirements are translated into rules that are executable, thus automating the rules without human intervention in the background. We evaluated the system with 5,000 records for training. Results showed that the framework proposed can achieve a high performance, higher than traditional hand-crafted methods with an accuracy of 95.2% in classification tasks. Another advantage of the system was a reduction in compliance decision execution time by over 99.9%, reducing processing time from hours to seconds—this demonstrates its formidable efficiency at real-time engagement and data management. The proposed framework is found to be a smarter approach to managing the complexity of compliance and something similar to an independent cyber defense system which is self-regulated, transparent, and reduces operational costs as well as the audit and compliance process in the modern digital environment.