Despite the proliferation of guidelines, standards, and best practices for digital accessibility, many platforms and websites remain inaccessible to people with disabilities. Although global awareness is slowly increasing, little has been done to overcome this issue. This study explores the potential of Artificial Intelligence (AI) and Machine Learning to address this problem, focusing on the personalization of user interfaces (UIs) in electric motorcycles. Unlike static guidelines, AI-driven solutions can dynamically adapt to the specific needs of users, creating more inclusive digital experiences. We propose a CAIA (Comprehensive AI Accessibility) framework model as a way to integrate AI into electric motorcycle interfaces, allowing users to configure their accessibility preferences and for AI to automatically adjust the display and controls of the motorcycle, promoting a human-centered computing approach and an adaptive system. The model has shown to effectively improve user models and personalization, ensuring a personalized and inclusive experience. The study concludes that AI-driven systems, when ethically implemented, can enhance digital inclusion while providing a more tailored and adaptive user experience. It also discusses the ethical implications, privacy concerns, and the role of human involvement in the development of assistive technologies and interaction design, offering a comprehensive solution to improve digital inclusion for all types of users.