The 2019 O’Reilly AI Conference in New York City highlighted significant discussions on AI's evolving role in business, with notable contributions from experts like Matt Zeiler, CEO of Clarifai. Zeiler's talk addressed the challenge of AI systems losing accuracy over time, emphasizing the importance of implementing feedback loops to maintain and enhance AI performance. Feedback loops involve reusing an AI model's predicted outputs as training data for new model versions, thereby reinforcing the model's learning and accuracy. This process is likened to a teacher correcting students' work, where both auto-labeled and human-verified data are fed back into the system. The feedback loop ensures AI models continuously learn and adapt, preventing performance stagnation by aligning training data with real-world conditions that matter to customers.