Qlik launches Trust Score for AI to strengthen data readiness

Qlik has announced the general availability of its Trust Score for AI, a pioneering feature designed to help enterprises evaluate whether their data is truly ready for artificial intelligence before it ever reaches a model. Now part of Qlik Talend Cloud, the Trust Score provides a single, intuitive metric to highlight data weaknesses, enabling organisations to improve reliability, reduce risk, and avoid flawed AI outcomes.

Specifically tailored for AI use cases, this latest solution introduces key dimensions: Diversity, Timeliness, and Accuracy, which help assess data representativeness, freshness, and integrity. These measures are crucial in mitigating bias, maintaining relevance, and ensuring data quality for AI training, generative models, and automation workflows.

Drew Clarke, EVP of Product and Technology at Qlik, noted, “Data trust isn’t a hygiene issue; it’s the foundation of every AI decision. Without it, you're gambling with outcomes and compliance.”

The Trust Score for AI enhances Qlik’s existing framework, which already includes metrics such as Discoverability and Usage, with Security and LLM Readiness features set to launch soon. Qlik also plans to introduce Trust Score historisation, enabling teams to monitor changes over time and assess downstream impacts such as model drift or performance degradation.

Qlik is also developing an AI-native Data Stewardship feature within Qlik Talend Cloud. This will combine automated checks, human-in-the-loop processes, and end-to-end governance to help AI and data teams collaborate more effectively on data quality.

With just 42% of executives expressing full trust in AI-generated insights, Qlik’s Trust Score offers a measurable, repeatable approach to close the data trust gap and make AI deployment more secure, scalable, and impactful. 

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