Artificial Intelligence

Abstract

Artificial intelligence (AI) is reshaping the healthcare landscape, presenting opportunities and challenges for healthcare leaders. This chapter explores the dual role of AI as a disruptor and enabler, providing a detailed analysis of its applications and implications across the health ecosystem. Key AI technologies, including machine learning (ML), deep learning (DL), natural language processing (NLP), and large language models (LLM) are examined in the context of diagnosis and clinical decision assistance, patient- and consumer-centric care, and operational efficiency. The chapter also highlights ethical and regulatory considerations, such as data privacy and algorithmic bias, as well as the risk of cultural bias in maintaining Indigenous Data Sovereignty and transparency in decision making. Global examples illustrate the transformative potential of AI in precision medicine, clinical trials, surgical robotic systems, health system optimisation, and patient flow. Despite advances, a significant challenge for health managers and leaders is establishing and integrating robust governance, leveraging public–private partnerships while maintaining strong data and cyber provisions, and investments in equitable access to AI technologies for clinicians and consumers. Workforce preparedness, including education and leadership development, remains critical for successful AI integration. This chapter serves as a blueprint for healthcare leaders aiming to leverage AI responsibly and effectively in transformative and learning healthcare systems.

Ähnliche Arbeiten