Emarsys: Most brands struggle to operationalize AI

INDIANAPOLIS — While most enterprises view artificial intelligence as essential to customer engagement, many lack the real-time and operational data required to use the technology effectively, according to new research from Emarsys.

The SAP company’s 2026 Global Engagement Index found that 78% of enterprises consider AI essential, yet 77% are unable to operationalize it effectively. The research is based on responses from 10,000 consumers and 4,800 enterprise decision-makers across six countries.

Data accessibility is a major obstacle. Emarsys found that 54% of enterprises cannot access and use real-time data, and 60% have “dark data,” information that is collected but never activated. Another 55% said their data is too unstructured to use effectively.

The findings point to a gap between brands’ investment in AI-powered marketing and their ability to integrate those systems with operational information, such as inventory levels, order status, fulfillment timelines, and customer service activity.

Without those connections, AI systems may be able to interpret browsing, purchasing, and marketing engagement behavior but remain unaware of what is happening elsewhere in the business. This can result in customers receiving promotions for products they have already purchased, recommendations for unavailable merchandise, or offers that conflict with recent transactions.

Emarsys said operational data is a critical layer for retailers and brands seeking to move AI beyond campaign optimization and apply it across the customer experience.

AI-powered customer engagement can combine machine learning, predictive AI, generative AI, and AI agents to identify customer patterns and determine relevant interactions throughout the customer lifecycle. Unlike conventional marketing automation, which typically follows predetermined rules and triggers, AI can interpret patterns and adjust decisions in response to changing customer behavior.

However, the effectiveness of those capabilities depends on the information available to the AI system. Connecting behavioral information with inventory, commerce, fulfillment, and service data can enable customer engagement decisions to reflect both what shoppers are likely to want and what a retailer can actually deliver.

The Emarsys research suggests that strengthening those underlying data connections will become increasingly important as retailers and consumer brands expand their use of AI for personalization, customer journeys, and marketing automation.