Remote and underserved communities continue to face serious challenges in accessing quality healthcare. Factors such as weak infrastructure, difficult terrain, and financial constraints often prevent people from receiving timely medical support. Telemedicine has emerged as a potential solution to bridge these gaps, but its effectiveness is frequently limited by poor internet connectivity, restricted diagnostic capabilities, and the shortage of specialized healthcare professionals. Recent advancements in Artificial Intelligence (AI) are opening up new opportunities to strengthen telemedicine services. With tools like predictive analysis, automated diagnostic support, and tailored treatment recommendations, AI has the potential to improve both the reach and reliability of healthcare in such regions. This paper explores how AI can be integrated into telemedicine systems to expand medical access, improve diagnostic accuracy, and create long-term, sustainable healthcare models. It also highlights practical examples, major challenges in implementation, and the ethical aspects that must be addressed, while suggesting a framework for developing inclusive AI-powered telehealth systems that can help achieve greater equity in global healthcare.