While significant focus has been placed on upgrading asymmetric algorithms in the face of future Quantum threats, an accelerating threat vector is the use of AI and Machine Learning to attack cryptographic keys made from poor-quality entropy. Newly standardized NIST PQC algorithms like ML-KEM and ML-DSA require significantly more entropy than the classic algorithms they will replace, and even AES-256 keys are under threat. This talk will focus on advancing threat research, the state of the commercial market for QRNG, relevant standards, and immediate use cases that can elevate data, application, network, PKI, and cloud security TODAY, independent of PQC algorithm migration.