<b>Artificial Intelligence in Healthcare: Present Utilization, Key Challenges, and Emerging Opportunities</b>

Abstract

Background: Artificial Intelligence has rapidly emerged as a transformative force in healthcare, supporting advancements in clinical practice, diagnostics, treatment planning, and health system management. Its integration has improved accuracy, efficiency, and personalised patient care. However, alongside these advancements, significant challenges hinder its optimal utilization and widespread adoption. Objective: This review aims to examine the current utilization of AI in healthcare, identify key challenges associated with its development and implementation, and highlight emerging opportunities that can shape the future of AI-driven healthcare. Methodology: A narrative review methodology was adopted. Relevant peer-reviewed articles, reports, and policy documents published between 2014 and 2024 were retrieved from PubMed, Scopus, Web of Science, and Google Scholar. Keywords included “Artificial Intelligence in Healthcare,” “AI Applications,” “Healthcare Challenges,” and “Opportunities in AI.” Literature was screened for relevance and synthesised to provide an overview of current applications, challenges, and future opportunities. Results: AI is currently utilized in diagnostic imaging, predictive analytics, clinical decision support, telemedicine, robotic surgery, drug discovery, and personalised medicine. These applications contribute to faster diagnosis, improved treatment outcomes, and enhanced healthcare efficiency. However, adoption remains limited due to challenges such as data privacy concerns, algorithmic bias, high implementation costs, lack of clinician training, and insufficient regulatory clarity. Emerging opportunities include explainable AI, enhanced data governance, interdisciplinary collaboration, and increased access to AI-driven tools through scalable digital health solutions. Conclusion: AI holds substantial potential to advance healthcare delivery. Addressing existing challenges through ethical practices, strengthened regulations, capacity building, and equitable access will be essential for harnessing AI’s emerging opportunities to improve global health outcomes.

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