At Sierra Ventures’ 20th Annual CXO Summit, Pantomath’s CEO and SIERRA Partner, Shashank Saxena, sat down with Snowflakes' EVP of Product, Christian Kleinerman. The discussion focused on how data architecture is emerging as the foundation of enterprise AI, emphasizing that even the most advanced models are only as powerful as the quality, accessibility, and context of the data that powers them.

From Analytics To Intelligence

Enterprises are moving from using data primarily for reporting to using it for real-time intelligence. AI has reignited the importance of data-driven decision-making, prompting organizations to rethink how data flows across every process. This transformation requires new skill sets, modern systems, and more dynamic ways of connecting data with business logic.

AI Without Enterprise Data Is Just ChatGPT

AI without high-quality, trusted enterprise data is just a generic tool. The most powerful AI systems are those that understand the language, logic, and context of a business. Generic models can answer general questions, but true enterprise value comes from aligning AI with a company’s unique logic and definitions, such as how it measures revenue, defines success, and governs access. Context and memory are becoming the new differentiators, transforming reactive chatbots into intelligent business partners.

Open Standards And Interoperability

The conversation also highlighted the end of the warehouse versus lakehouse debate. The industry is converging around a shared goal: data must be open, interoperable, and portable across systems. Projects like Apache Polaris™and the Open Semantic Interchange reflect this push toward openness, ensuring that semantic data, the meaning behind the numbers, can travel across platforms.

Healthy Competition, Better Outcomes

Competition among major data platforms is driving faster innovation and better outcomes for enterprises. The ability to switch between tools or combine them freely keeps vendors accountable and prevents lock-in. Flexibility is becoming the new defining principle — enabling organizations to build strong platforms, while maintaining the freedom to connect, experiment, and evolve.

AI transformation begins with data. The enterprises that will lead in this next wave are those creating open, contextual, and interoperable data ecosystems that allow intelligence to flow seamlessly across their organizations.