Designation Marks Seven Years of Qlik Being Recognized as a Leader, Continuing to Scale AI-Driven, Trusted Data Outcomes

Qlik^®, a data integration, data quality, analytics, and AI company, today announced its recognition as a Leader in the 2026 Gartner® Magic Quadrant for Augmented Data Quality Solutions, marking its seventh time receiving this recognition. Qlik sees this recognition as validation of its commitment to helping businesses ensure the data quality and governance needed to drive AI confidently at scale.

AI models require consistent, complete, and trusted data to generate accurate insights, yet many organizations struggle with gaps, inconsistencies, and unstructured inputs that undermine AI’s effectiveness. Poor data results in unreliable models, biased predictions, and heightened operational risk.

“We’re entering an era where AI does more than recommend, it initiates and acts, often across systems and workflows,” said Matt Hayes, General Manager, Data Business Unit, Qlik. “That makes data quality and governance a practical requirement, not a technical preference. Organizations need to understand what data they have, how it’s changing, and whether it’s fit for use, so AI can operate with the right guardrails and accountability.”

Gartner estimates that, “By 2027, 70% of organizations will adopt modern data quality solutions to better support their AI adoption and digital business initiatives.” By enabling proactive, governed data pipelines, Qlik helps AI systems operate with high-trust data from the start, allowing businesses to scale AI with confidence.

AI is driving demand for next-generation data quality solutions that go beyond basic cleansing. With innovations like the Qlik Trust Score™ for AI, retrieval-augmented generation (RAG) support, and automated data remediation, businesses can move from reactive fixes to continuous, AI-powered data optimization.

Key Capabilities of Qlik:

• Proven execution at scale with broad customer adoption: Qlik is built to support enterprise data quality programs across teams and domains, enabling consistent standards and repeatable outcomes as deployments grow.
• Metadata-driven data quality and AI readiness: Qlik uses active metadata and lineage to improve transparency, accelerate troubleshooting, and help teams assess whether data is fit for analytics and AI use cases. Qlik Trust Score for AI then provides a clear measure of AI readiness, helping organizations deliver trusted, domain-ready data for confident analytics and AI outcomes.
• Advanced and native AI-augmented capabilities: Embedded directly into existing data quality workflows, Qlik applies automation and AI-assisted approaches to speed data preparation, matching, and remediation, helping reduce manual effort and improve consistency over time.
• Flexible hybrid and multi-cloud deployment options: Supporting SaaS, hybrid, and on-premises needs, Qlik helps organizations maintain consistent quality across distributed environments and complex data landscapes. With usage-based pricing and built-in FinOps visibility, organizations gain clear insight into usage and resource consumption.

AI success starts with trusted data. A complimentary copy of the Gartner Magic Quadrant for Augmented Data Quality Solutions will be available for download on Tuesday, February 17, 2026 at Qlik.com

Gartner, Magic Quadrant for Augmented Data Quality Solutions, Sue Waite, Divya Radhakrishnan, Amy Bickel, 11 February 2026

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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.

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