Retailers are pouring record investments into AI, but a disconnect is emerging. According to SAP Emarsys's latest AI in Retail Report, while 74% of US marketers say AI is central to their personalization strategy, only 25% of consumers believe brands personalize content to their needs - and just 27% feel they receive fair value in exchange for their data.

The problem isn't consumer expectations; it's operational complexity. Nearly half of marketers report their data is too fragmented to use effectively, creating what amounts to operational inefficiency at scale. Marketing teams are spending valuable cycles wrestling with data silos instead of optimizing customer experiences.

From an operational standpoint, this reflects a fundamental infrastructure decision. Most marketing platforms require extensive integration work to connect with core business systems. The result is fragmented workflows where marketing operates alongside - rather than integrated with inventory management, sales operations, and financial systems.

SAP Emarsys takes a different approach, working natively within SAP's enterprise data models. This eliminates the integration overhead while ensuring marketing operations have real-time access to the full business context - from supply chain status to customer service interactions.

As Gibson Guitars’ business results demonstrate, the operational impact is measurable. Eliminating data silos resulted in increasing email revenue by 50%, doubling engagement rates and generating 40% of revenue through automated customer engagement workflows.

For enterprises operating under regulatory frameworks, this model delivers another operational advantage. Customer data processing occurs within existing governance structures, supporting GDPR compliance and data residency requirements without the complexity of external routing systems.

As AI adoption scales across retail operations, success won't depend on algorithm sophistication alone. It will depend on operational efficiency - specifically, how quickly and accurately businesses can convert enterprise data into customer value.Those who operationalize data effectively will emerge as market leaders.