As deep learning grapples with 'black box' limitations, neuro-symbolic AI merges neural networks' pattern recognition with symbolic systems' logical reasoning to create auditable, transparent AI. This hybrid approach is gaining traction for high-stakes applications in healthcare, cybersecurity, and law, where explainability is non-negotiable. Pioneered by IBM, MIT, and DARPA, it represents a paradigm shift toward AI that doesn't just predict but justifies its decisions.