Secure and Explainable Artificial Intelligence (XAI) frameworks are becoming essential components of modern intelligent enterprise platforms, especially in ecosystems integrating SAP cloud computing and advanced cybersecurity architectures. As enterprises increasingly rely on AI-driven decision-making for finance, supply chain, human resources, and operations, the need for transparency, trust, and security has intensified. Traditional black-box AI models often lack interpretability, making it difficult for organizations to validate decisions, ensure regulatory compliance, and mitigate cyber risks. This paper explores a comprehensive framework that integrates explainable AI techniques with SAP cloud-based enterprise systems while embedding cybersecurity-by-design principles. The proposed approach enhances model transparency through interpretable machine learning, feature attribution methods, and rule-based explanation layers while ensuring secure data pipelines using encryption, identity access management, and zero-trust architectures. Furthermore, the framework leverages SAP’s intelligent enterprise capabilities, including SAP S/4HANA and SAP BTP, to enable scalable deployment of AI services. The integration of cybersecurity ensures resilience against adversarial attacks, data breaches, and model manipulation. Overall, this study highlights how secure and explainable AI can improve trust, governance, and operational efficiency in enterprise environments, enabling organizations to adopt AI responsibly while maintaining compliance and security standards.