Qlik today announced a major expansion of its trust and governance capabilities for AI, centered on data products and the operational controls required to make them reliable for both human decision-making and AI-driven action.
As enterprises push AI deeper into workflows, the pressure lands on the data underneath every output. Teams need to know which data products are reliable, whether conditions have changed, and when intervention is required before weak data turns into weak execution.
Qlik’s answer is to make trust operable. This release brings together data products, trust signals, operating standards, anomaly detection, and agent-assisted stewardship into a tighter set of capabilities designed to help teams monitor, govern, and improve the data products that feed analytics and AI.
“As AI moves from answers into decisions and actions, weak data stops being a reporting problem and becomes an execution problem,” said Mike Capone, CEO, Qlik. “Data products need the same accountability as any other production asset, with clear signals for what humans and AI can safely rely on. That is how enterprises scale AI without scaling risk.”
What’s new
- Data Products in Qlik Analytics: Qlik is advancing data products as governed, AI-ready units of value that teams can create, manage, share, and reuse across analytics and AI workflows. This includes shared business definitions for measures, dimensions, and relationships, helping people and AI systems rely on more consistent business meaning.
- Data Product Agent: Qlik is introducing Data Product Agent to help teams create, manage, and deliver data products using natural language. It is designed to evaluate data products for quality, generate Trust Scores, and help humans and AI systems understand where to go for data and how good it is.
- Qlik Trust Score as an operational signal: Trust Score is a visible signal that evaluates data products across dimensions such as accuracy, timeliness, diversity, and completeness. The goal is to help teams inspect readiness before decisions or automated actions depend on it.
- Data contracts and operating expectations: Qlik is introducing a contract layer that helps teams define what a data product is expected to provide, giving producers a clearer operating standard and consumers a more explicit basis for trust.
- Service levels, alerting, and anomaly detection: New service-level objectives, alerting, and anomaly detection help teams monitor whether data products continue to meet expectations over time, surfacing degradation and drift before issues compound into business risk.
- Data Quality Agent for trust workflows: Qlik is extending agent-assisted operations into trust workflows with support for retrieving trust signals and data quality metrics, creating and editing rules, defining service levels, running calculations, and detecting anomalies through conversational interactions.
- AI-enabled stewardship at scale: New stewardship capabilities help teams generate rules, improve glossary coverage, create field descriptions, and recommend remediations more efficiently, reducing manual burden while keeping people in control of final decisions.
Together, these capabilities are designed to help enterprises operationalize trust around data products, giving teams a more practical way to govern quality, understand reliability, and support AI usage with stronger signals and clearer accountability.
This announcement is part of a broader set of releases at Qlik Connect® 2026, Qlik’s annual customer and partner event, focused on agentic analytics, agentic data engineering, operational trust, and sovereignty-ready deployment.
About Qlik
Qlik helps teams get more out of AI with data they can rely on and control. It delivers trusted data products, a powerful analytics engine, and AI agents. This helps teams reduce risk, keep operating costs in check, and scale AI responsibly as needs evolve. Used by 75% of the Fortune 500, Qlik supports customers worldwide. Qlik works with the systems and partners customers already use, so teams can stay flexible without lock-in.
© 2026 QlikTech International AB. All rights reserved. All company and/or product names may be trade names, trademarks and/or registered trademarks of the respective owners with which they are associated.
Any forward-looking statements are based on Qlik’s current expectations and projections about Qlik’s business plan, business strategy and objectives. These forward-looking statements are subject to a number of risks, uncertainties and assumptions. In light of these risks, uncertainties and assumptions, the forward-looking events discussed in this release should not be construed as a commitment from Qlik and may not occur. Qlik undertakes no obligation to update any forward-looking statements for any reason after the date of this presentation to conform these statements to actual results or to changes in expectations.
View source version on businesswire.com: https://www.businesswire.com/news/home/20260414118840/en/
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