"92% of all POCs today in the US are failing because they're trying to use bad data and LLMs that are standardized or generalized."   At Money 2020 I sat down with Deuna (www.deuna.com) co-founder Roberto Kafati (REKS) and their US head of GTM Chase Foster to explore the critical importance of leveraging high-quality, actionable data and intelligent systems to drive business value, especially in complex enterprise environments. The core challenge today is that while most companies possess vast amounts of data, a staggering 92% of AI pilot projects fail because they rely on data that isn't "AI-ready" that is lacking the necessary context, cleanliness, and standardization to be effectively used by large language models (LLMs). The key is transforming raw data, such as the 638 direct and indirect data points per payment transaction, into a strategically usable asset that goes beyond cost-cutting to unlock significant revenue growth across the organization.   The company's platform, Athia, is designed to solve this by acting as an agentic intelligence platform that utilizes merchant-specific data from massive commerce operations (like major airlines, movie chains, and retailers) to provide proactive, highly focused insights. Instead of forcing teams to manually analyze hundreds of performance dashboards, Athia surfaces the most critical information, alerting teams to revenue leakages and recommending direct, real-time actions, such as optimizing payment routing or detecting opportunities in developing economies. This approach allows businesses to embrace the future of "agentic commerce" by maintaining control over the customer experience and ensuring data-driven decision-making is implemented automatically and continuously across all critical functions, fostering a new era of cross-departmental collaboration between areas like payments and marketing.