Business intelligence users often struggle with standardized dashboards and limited chart options, requiring cumbersome CSV exports for deeper analysis. Designing custom dashboards that meet specific needs, like executive briefings or customer portals, is also challenging with typical grid-based tools. Previously, this led to building custom applications, a process now faster with AI but still hindered by production deployment issues. These issues include a lack of governed data, row-level security, and a clear security review path. To address this, Looker is launching Looker Data Apps, which combine AI's speed with Looker's governance framework.Data apps are AI-generated, interactive web applications hosted within Looker, designed for specific operational workflows. They offer bespoke layouts, allow user input for scenario testing and simulations, and connect analysis to execution tasks like updating records or dispatching events. These apps are built using AI developer tools grounded in Looker's semantic layer. They expand upon dashboards by enabling active execution and custom web components, unlike dashboards' aggregate visibility and standardized charts.Looker Data Apps are grounded in governed data, ensuring accuracy and consistency through the semantic layer. They transform analysis into action with customizable, multi-page web app experiences. Designed for enterprises, these apps inherit existing semantic models, row-level security, and access controls. They offer zero-code deployment of agent-generated applications, with no runtime token costs for end-user interactions. Deploying data apps is as simple as embedding a dashboard, allowing them to be integrated into external portals seamlessly. Looker Data Apps enable the transition from prototype to production-grade tools in minutes, bridging the gap between basic dashboards and complex custom systems.