Building AI models is just the beginning; the real challenge lies in production. The journey from prototype to product can take significant time and expertise, as highlighted by Google's experience. Many companies lack the core competency to build the necessary infrastructure for AI, emphasizing the need for skilled data scientists and engineers to bridge the gap between science and engineering.
