Artificial Intelligence in Healthcare: Enhancing Shared Decision-Making, Patient Autonomy, and Physician Expertise in the Era of Generative and Agentic AI - JAYABHARATH REDDY, DANDU; MUSTAFAQULOVA , MUHAYYO; O‘KTAMOV , IBROHIM; AZIZA , TAYIROVA (INTERNATIONAL CONFERENCE ON MODERN RESEARCH AND SCIENTIFIC INNOVATION, 2026)
The rapid advancement of artificial intelligence (AI), particularly Generative AI and Large Language Models (LLMs), is transforming healthcare decision-making processes. This paper examines the integration of AI into shared decision-making (SDM), focusing on its implications for patient autonomy, physician expertise, and clinical judgment. The study analyzes three key dimensions: explainability in AI systems, the impact of AI-generated recommendations on patient decision-making, and the influence of AI on physician expertise, including risks such as automation bias and deskilling. Building on recent developments in Explainable AI (XAI), multimodal AI systems, and agentic AI, this paper proposes a conceptual framework for human-centered AI integration in healthcare. The findings suggest that AI can enhance decision-making by reducing cognitive load, structuring complex information, and supporting collaboration between patients and physicians. However, challenges related to transparency, trust, and ethical governance must be addressed. The study concludes that AI should augment rather than replace human expertise, ensuring responsible and effective adoption in clinical environments.