Generative AI and its agentic offspring may be foundational technologies, but they are still following the normal technology hype cycle: excitement at the potential, followed by news of failed deployments, followed by a more mature understanding of what’s required for success. The third stage generally comes down to a realization that the main obstacles are organizational, not technical: projects fail due to poor internal alignment, change management, reward systems, and so on. Similarly, when it comes to customer data (and all other business data), there’s a dawning recognition that whether the data resides in a CDP, cloud warehouse, or marketing platform, the real challenge is still transforming raw data into usable information through quality management, unification, and mapping.  We’re just beginning to see the third-stage insights from the industry’s more advanced thinkers.…