Gartner has named Qlik a Leader in the 2026 Gartner® Magic Quadrant™ for Augmented Data Quality Solutions, our seventh time being recognized as a Leader in this Magic Quadrant.
As AI becomes operational, data quality matters more than ever. We’re past the phase where AI just produces outputs. AI is starting to initiate, route, and act across real workflows. The market reaction to our recent agentic experience launch has been outstanding, across customers and partners, one partner summed it up perfectly, ‘It’s what you’ve been hoping AI would be.’
That shift is exciting, and it’s also where the stakes go up fast. Once AI is acting, “pretty good data” stops being good enough.
Here’s a real-life example why. Imagine an AI agent that detects churn risk and automatically triggers a retention workflow, it offers a discount, routes a case to a rep, and updates a renewal forecast. If the underlying account data is duplicated, the product entitlements are out of date, or the contract status is wrong, the agent does not just produce a bad insight, it takes the wrong action, at scale. That is why “pretty good data” stops being good enough.
AI is moving from insight to action, and trust becomes the requirement
The market is accelerating with AI, GenAI, and agents. Data quality is in the middle of it, because trusted, governed data is what makes these initiatives real. One line from the report that stuck with me is the Gartner strategic assumption that “by 2027, 70% of organizations will adopt modern data quality solutions to better support AI adoption and digital business initiatives.” That’s not a “tools are trending” statement, it’s a sign the center of gravity is moving.
When AI is operational, quality and governance are no longer technical preferences. They’re the guardrails that determine whether AI is safe to deploy at scale.
“Augmented” data quality isn’t just faster cleanup
Data quality used to be treated like a reactive project, profile the data, clean it, move on. That model breaks because in an Agentic AI world, data doesn’t sit still. Augmented data quality is about using AI-enhanced capabilities powered by activated metadata to spot issues earlier, recommend fixes in context, and automate what can be automated, so data stays reliable and usable over time. In plain language, it’s what you proactively need when your data estate is hybrid, your sources keep expanding, and AI systems need data they can trust continuously, not once.
In our opinion this year’s Magic Quadrant represents a clear shift in priorities regarding AI Augmentation. It is no longer "nice to have" but critical for success.
Why Qlik’s approach matters in the agentic era
I believe Qlik’s performance aligns with what customers are asking for right now, a metadata-driven approach that supports quality and governance across hybrid environments, with automation and Qlik Trust Score™ for AI helping assess dataset fitness for AI readiness. Unstructured data quality is now a core requirement and no longer an emerging trend, something we have built in within our data pipelines and expanded with our acquisition and our introduction of Qlik Answers®.
If you’re building toward agentic data engineering project, that foundation for AI matters. It’s how you answer questions like: what data this agent is using and of what quality, where did it come from, what rules apply, what changed and when, and who owns remediation. That’s the difference between AI that is impressive in a demo, and AI you can put into production with accountability — backed by the data you can trust.
Download the report for more insight (and there are some interesting moves this year), but here are my takeaways:
First, this category rewards execution. You only get value when data quality runs reliably at scale, every day and anywhere supporting hybrid, multi-cloud setups.
Second, AI-augmented capabilities need to show up natively inside the workflow, helping teams move faster on rules and remediation while keeping stewardship and governance in the loop.
Third, data quality is an operating model, not a one-time deployment, so global support and a strong partner ecosystem matter more than most people expect. Standalone data quality tools no longer cut it.
And if you want to go deeper in data and agentic AI, join us at Qlik Connect on April 13–15 in Kissimmee, Florida. Come for the hands-on sessions, stay for the conversations with like-minded peers and Qlik experts.
Gartner, Magic Quadrant for Augmented Data Quality Solutions. Sue Waite, Divya Radhakrishnan, Amy Bickel, 11 February 2026.
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