Abstract
<jats:p>The integration of artificial intelligence (AI) into electronic health record (EHR) systems is reshaping how patients and clinicians interact, making healthcare more collaborative, efficient, and personalized. Traditional EHRs often burden clinicians with documentation and fragmented data, leaving patients as passive participants. AI transforms this dynamic through intelligent automation, predictive analytics, and natural language processing that extract insights, streamline workflows, and enhance communication. Clinicians can detect early warning signs, recommend tailored treatments, and focus more on patient care, while AI-driven dashboards and chatbots help patients understand their data, engage in shared decisions, and track progress. Yet, challenges such as privacy, bias, and transparency require strong governance and ethical design. This chapter examines how responsibly integrating AI into EHRs can bridge the gap between data and care, strengthen trust, and promote equitable, human-centered healthcare.</jats:p>