In this interview from Qlik Connect 2026, Christopher Powell, chief marketing officer of Qlik, joins theCUBE Research's Rebecca Knight and Rob Strechay to discuss how enterprises are moving past AI experimentation toward operational dependence — and what foundational work that shift demands. Powell argues the AI inflection point is less about whether the technology works and more about whether the data does. He outlines three prerequisites for enterprises ready to operationalize AI: a trusted data foundation, deep contextual understanding of proprietary environments and architectural flexibility to adapt as innovation accelerates. To address the trust dimension, Powell highlights Qlik's trust score for AI, which evaluates data lineage, provenance and access history to give AI systems confidence in the inputs they're acting on. The conversation also explores how leading organizations are building human expertise into agentic systems before removing humans from the loop — a model demonstrated on stage with UPS, where domain knowledge defines the boundaries of autonomous action. Powell breaks down the evolution from standalone AI tools to agents to fully agentic workflows, noting how this progression is dissolving organizational silos and forcing companies to build shared data foundations across marketing, sales and customer success. He underscores cost management as a strategic imperative, warning that AI environments built without embedded cost controls will fail to scale. From emerging efficiency stories — including customers spending a few hundred thousand dollars to save $15 million annually — to the broader organizational rethinking required to lead in the AI era, Powell outlines why companies that ask not how AI can improve existing processes, but how it will fundamentally transform them, are the ones best positioned to win.