Answer
Backpropagation matters in Deep Learning because it directly affects how well AI systems perform in this area. Teams that understand it can design solutions that are more accurate, efficient, and easier to maintain over time.
Real-world example When a neural network mislabels a cat photo as a dog, backpropagation adjusts the internal weights so the next prediction is more likely to be correct.