Enhancing User Login Efficiency via Single Sign-On Integration in Internal Quality Assurance System (eSPMI)

In the continually evolving digital era, authentication system efficiency has become crucial for accelerating processes and enhancing user security. This research aims to analyze the integration of Single Sign-On (SSO) features in authentication systems and its impact on user login efficiency, incorporating Artificial Intelligence (AI) concepts. Using a comparative analysis between traditional authentication systems and those integrated with SSO, sample data from three major technology companies show that SSO integration reduces average login time by 60% and increases user satisfaction by 70%. Additionally, integrating AI in SSO systems enhances security by providing predictive analytics for potential security threats and optimizing the overall user experience. These findings suggest that broader adoption of AI-enhanced SSO can significantly strengthen security and efficiency in corporate authentication systems, making it a valuable strategy for organizations aiming to improve user satisfaction and data protection.