Orlando, Florida, May 15 – Qlik, a global leader in data integration, analytics, and AI, launched two groundbreaking innovations — its new agentic experience and the Qlik Open Lakehouse — aimed at transforming enterprise decision-making and productivity in the AI era. These announcements were made during the company’s annual flagship event, Qlik Connect 2025.
Conversational Agentic AI for Enterprise Decision-Making
Qlik’s agentic experience introduces a conversational interface that enables users across all levels of an organization to interact naturally with data. Designed to simplify complex workflows, this new interface leverages AI agents to deliver rapid insights and actionable intelligence, helping teams make faster, more accurate decisions.Qlik CEO Mike Capone explained the vision behind the innovation:
“People want a seamless, conversational way to engage with their data — one that fits naturally into their work and delivers clear, trusted answers in context. We've built this experience to reflect how decisions actually get made in a business.”
At the core of this agentic experience lies Qlik’s proprietary engine, which uniquely indexes relationships across data to uncover unexpected insights. The new interface, set to roll out this summer, is built to drive productivity and decision-making in fast-changing environments.
Launch of Qlik Open Lakehouse: Real-Time, Scalable, and Cost-Efficient
Qlik also introduced the Qlik Open Lakehouse — a fully managed solution based on Apache Iceberg, tailored for enterprises that need to scale rapidly while reducing operational costs. The Open Lakehouse delivers real-time data ingestion, automated optimization, and compatibility with multiple analytics and ML engines, eliminating vendor lock-in.Capone emphasized the strategic importance of this architecture in the AI era:
“With Qlik Open Lakehouse, enterprises gain real-time scale, full control over their data, and the freedom to choose the tools that work best for them. We built this to meet the demands of AI and analytics at enterprise scale, without compromise.”
The platform claims up to 2.5 to 5 times faster query performance and as much as 50% reduction in infrastructure costs compared to traditional data warehouses.
AI Adoption: The Gap Between Experimentation and Execution
Despite record investments in AI, many enterprises remain stalled at the experimentation stage. According to IDC research presented at the event, although 80% of companies plan to deploy agentic AI workflows, only 12% feel ready to support autonomous decision-making at scale. Concerns about hallucinations, bias, and regulatory risks continue to erode trust in AI outputs.Qlik’s AI Council emphasized that trust must be designed in from the start. Verifiability, explainability, and actionability are now critical differentiators.
“Companies aren’t losing ground because they lack powerful models,” Capone noted. “They’re losing because they haven’t embedded trusted AI into the fabric of their operations. If your data isn’t trusted, your AI isn’t either. And if your AI can’t be trusted, it won’t be used.”