In this Podcast we introduce and explain homomorphic encryption (HE), a groundbreaking cryptographic method that permits computations directly on encrypted data without prior decryption. We highlight how HE addresses critical security gaps in "data-in-use," where traditional encryption methods fall short. It categorizes HE into partially, somewhat, and fully homomorphic schemes, with fully homomorphic encryption (FHE) being the most robust, allowing unlimited operations through techniques like bootstrapping, despite its current computational overhead. The discussion also explore diverse applications of HE, including secure cloud computing, privacy-preserving AI and machine learning, healthcare analytics, financial fraud detection, and secure voting, underscoring its role in enhancing data privacy and regulatory compliance. Finally, we discuss the historical evolution of HE, from its theoretical inception in 1978 to modern lattice-based schemes, acknowledging ongoing challenges like performance but projecting a future of increased adoption driven by algorithmic improvements, hardware acceleration, and standardization efforts.