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In recent years, the rapid development of artificial intelligence (AI) has spurred significant advances across a range of disciplines, not least in the domain of sustainable life sciences. This research paper investigates implemented AI solutions in sustainable life sciences, examining their global applicability and effectiveness over the period 2020 to 2024. Through a systematic review of recent literature and detailed case study analyses, we present quantitative data on AI performance indicators and sustainability metrics, underlining the benefits and challenges associated with these novel applications. In this study, interdisciplinary perspectives—spanning computer science, environmental science, biotechnology, and ethics—are synthesized to provide a comprehensive understanding of how AI can drive sustainability in life sciences, improve operational efficiency, and support decision making in various regulated industries. Real-world implementations from developed nations are examined to present comparative analyses, and data visualizations are employed to illustrate the financial, environmental, and performance metrics achieved by these AI systems. Ethical considerations are addressed throughout the study to ensure that the integration of AI in sustainable life sciences complies with current societal and environmental norms. The paper concludes with actionable recommendations and a five-year projection regarding the technology adoption curve for AI solutions in sustainable life sciences.