Advancing our understanding of complex diseases necessitates an interdisciplinary dialogue beyond artificial intelligence (AI) in the field of medicine. Two decades after the completion of the Human Genome Project, genetic sequencing has facilitated targeted therapies for gene mutation-related ailments. However, this achievement has unveiled the immense gaps in our comprehension of life and disease mechanisms. Complex diseases, including cancer, diabetes, and autoimmune disorders, remain elusive due to their multifactorial nature. Consequently, a more holistic approach integrating AI with diverse scientific disciplines becomes imperative. This paper emphasizes the urgency of fostering collaboration among genetics, molecular biology, computational biology, and clinical research to unravel the intricate complexities underlying these diseases. By synergizing expertise and data from various domains, we can make significant strides towards unraveling the intricate web of complex diseases, leading to improved diagnosis, treatment, and ultimately, patient outcomes.