In this interview at Qlik Connect 2026 Chris Powell of Qlik, chief marketing officer, discusses operationalizing artificial intelligence in enterprise analytics with a focus on building trust, context and adaptability. Rebecca Knight of theCUBE Research and Rob Strechay of theCUBE Research host the conversation and explore Powell’s perspectives on trusted data foundations, context-aware semantic layers and agentic models for production use. Powell provides examples from marketing and supply chain where structured and unstructured data converge, and they emphasize practical steps for moving from experimentation to operational deployment. Powell stresses that organizations prioritize three pillars—data trust, contextualization and flexibility—to scale AI successfully. They highlight human-in-the-loop approaches, cost governance for token and model usage and the development of cross-functional data products that support measurable return on investment. Hosts and analysts note increasing examples of measurable impact and underscore the role of partners and customers in rethinking architectures to move beyond pilots toward business outcomes. This conversation addresses enterprise analytics, data governance, semantic layer design, agentic capabilities and applied use cases such as marketing analytics and United Parcel Service UPS implementations. Viewers gain actionable guidance on governance, model selection and operational considerations to achieve trusted, contextual and adaptable analytics at scale. Watch the full interview to learn practical guidance for operationalizing AI and scaling analytics across the enterprise.