Qlik®, a global in data integration, data quality, analytics, and artificial intelligence, has announced the general availability of Qlik Trust Score™ for AI.

This innovation is now included within Qlik Talend Cloud®. It helps organizations assess whether data is truly ready for AI before it reaches a model.

The Qlik Trust Score for AI introduces purpose-built scoring across AI-specific dimensions. It is designed to help companies establish strong data foundations for responsible and scalable AI.

As AI adoption grows, many businesses face a critical challenge they don’t know if the data feeding their models is trustworthy. Qlik’s solution addresses this by offering a single, intuitive score that reveals where data trust breaks down. This helps prevent bias, drift, and faulty outcomes.

Drew Clarke, EVP of Product and Technology at Qlik, stated, “Most companies still treat data trust like an IT hygiene issue. It’s not. It’s the foundation of every AI decision a business makes.”

He added that without the ability to measure trust, organizations are gambling with outcomes, compliance, and customer experience. The Qlik Trust Score for AI provides a real-time signal that data is fit for purpose.

This tool builds on Qlik’s existing Trust Score framework with three new AI-focused dimensions:

• Diversity: Measures representativeness and balance to reduce training bias.
• Timeliness: Assesses freshness of data for relevant decision-making.
• Accuracy: Flags values that break business rules or lack reliability.

These features combine with metrics like Discoverability and Usage. The solution supports AI training, Retrieval-Augmented Generation (RAG) pipelines, and intelligent automation. Security and LLM Readiness metrics are expected in future updates.

Qlik also revealed plans for Trust Score historization, enabling users to track trends over time. This helps correlate trust shifts with issues like model drift or performance drops.

In addition, Qlik reported an early access program for an AI-native Data Stewardship experience in Qlik Talend Cloud. Launching this fall, the feature aims to detect and resolve data issues earlier. It will include automated rules, human-in-the-loop workflows, and platform-wide governance.

Ritu Jyoti, Group VP/GM at IDC, noted that many AI initiatives fail because of untrustworthy data. “Without visible metrics for data trust, organizations risk costly failures and stalled adoption,” she said.

Charles Link, Senior Director of Data and Analytics at Reworld, emphasized that trust in data is critical. “The hardest part of AI is rarely the model. It’s trusting the data behind it,” he said.

A recent Qlik survey revealed only 42% of executives fully trust AI-generated insights, despite nearly 90% seeing AI as vital to their strategy.

Qlik Trust Score for AI helps bridge this trust gap with an objective and repeatable framework. It aligns with emerging governance standards.

Qlik is the first to deliver a unified, AI-specific trust signal directly into the data pipeline. It integrates measurement, monitoring, and remediation in one platform.

The feature is now generally available for Qlik Talend Cloud Enterprise Edition customers.

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