Enterprise investments in commerce AI are at an all-time high, yet the results remain inconsistent. This stems from a pattern of adding new AI capabilities without properly integrating them into a cohesive system. This "point solution pattern" creates a fragmented consumer experience marked by context loss and inconsistency. AI amplifies the cost of this fragmentation, leading to confidently incorrect recommendations due to data incoherence. Individual AI tools may show strong performance metrics in isolation, but these don't reflect the system's overall underperformance. This diagnostic problem means brands might see good tool-level metrics alongside flat or declining overall conversion rates. External factors like AI disintermediation are also pressuring funnels, exacerbating the issue. Companies achieving consistent AI outcomes have implemented a unifying execution layer across their AI investments. This involves a shared data layer for real-time information, a policy framework for governance, and a transaction layer for seamless order completion. These foundational elements ensure AI capabilities work together, compounding improvements. As agentic commerce matures, the need for architectural coherence becomes critical to avoid consumer AI agents abandoning broken processes. Brands that build this coherence now will gain a significant advantage in the coming transactional era. The fragmentation isn't due to bad tools but a lack of essential connective infrastructure.