en.Wedoany.com Reported - Qlik has announced the full rollout of new intelligent data engineering capabilities in Qlik Cloud, officially putting into production the features introduced at Qlik Connect 2026. This release aims to help data teams leverage dedicated AI agents and declarative workflows to find trusted data, define business meanings, assess quality, shape data products, and create pipelines through existing tools, thereby accelerating the delivery of governed data into analytics, automation, and AI workflows.
As enterprises move AI from pilot projects to business workflows, data engineering becomes a critical bottleneck. The speed at which AI agents recommend, generate, and act outpaces the construction, governance, or maintenance of traditional data pipelines. This imposes new requirements on data teams: to deliver at scale without sacrificing quality, lineage, governance, or architectural choices. Qlik's intelligent data engineering capabilities bring AI assistance into more data engineering workflows, extending beyond code generation to help teams move faster from intent to trusted data products while retaining human control over key decisions. These data products can be reused across analytics, automation, and AI use cases without needing to be recreated for each project.
Drew Clarke, Executive Vice President of Products and Technology at Qlik, stated that organizations are using multiple AI tools rather than relying on a single assistant, model, or data platform. Qlik's approach is to bring governed Qlik context into the tools data teams already use, accelerating engineering work through agents while preserving choice, transparency, and control.
The new capabilities span several areas: In data quality, agents assist users in retrieving trust scores and data quality indicators, creating or editing data quality rules, defining service level objectives, running computations, and detecting or reporting anomalies through natural language or MCP-enabled workflows. In data products, they help teams create, manage, and govern trusted data products, making curated AI-ready datasets easier to specify, maintain, and consume through intelligent AI in analytics and AI use cases. In catalog terminology, they help users discover data assets, standardize terms, and connect business definitions to governed metadata, reducing ambiguity for data teams, analytics users, and AI systems. In declarative pipelines and code, they allow data engineers to generate and modify pipelines using approved third-party coding agents and development environments based on governed pipeline context. In extended MCP data tools, they enable authorized AI clients to access Qlik capabilities and context, helping teams use their preferred AI assistants while maintaining enterprise control.
These capabilities are designed to help organizations address the barrier to AI value realization: the gap between ambition and data readiness. AI agents and analytics teams need timely data, consistent meanings, quality signals, lineage, and policy controls to operate reliably. Qlik brings these elements into data engineering workflows, enabling teams to accelerate the delivery of trusted data products for AI, analytics, and automation without governance becoming an afterthought.
Stephen Catanzano, Chief Analyst for Data and AI at Omdia, noted that enterprises face pressure to operationalize AI faster, but data engineering and governance remain major bottlenecks. The distinctive aspect of Qlik's approach lies in embedding intelligent capabilities directly into governed data workflows, helping organizations accelerate the delivery of AI-ready data products without separating speed from oversight. Robin Astle, Head of Qlik Analytics at Valpak, said the new capabilities help find the right assets, understand quality, and put trusted data products into use faster while keeping governance processes unchanged—this balance of speed and control makes AI practical.
This announcement builds on Qlik's AI strategy in analytics and data integration, including the Qlik Predict Agent and Qlik Automate Agent launched in June, as well as the Qlik Analytics Agent planned for the third quarter of 2026. The intelligent data engineering capabilities are now generally available in Qlik Talend Cloud and Qlik Cloud Analytics, with availability varying by capability, region, licensing, and deployment configuration.
