Qlik Extends Analytics from Answers to Agentic Action
Qlik Extends Analytics from Answers to Agentic Action
New capabilities across Qlik Answers, Discovery Agent, MCP Server, and new agents for prediction, automation, and analytics development help teams move from inquiry to action, with Discovery Agent surfacing more than 100,000 discoveries for customers since its February GA.
Key takeaways:
- Agentic analytics is already gaining traction: Since the February GA of Qlik’s agentic experience, the majority of Qlik Cloud accounts with agentic tools are actively using their agents.
- Qlik Answers becomes an on-demand analyst for decisions: New capabilities for discovery, analysis, prediction, and automation help teams move from signal to action in one governed flow.
- Prediction becomes part of the agentic flow: Qlik brings predictive signals, explainable reasoning, and workflow action together so users can understand what is likely to happen, why it matters, and how best to respond.
KISSIMMEE, Fla.--(BUSINESS WIRE)--Qlik® today announced a major expansion of its agentic analytics capabilities, bringing together Qlik Answers, Discovery Agent, and MCP Server with new agents for prediction, automation, and analytics development to support a more complete path from question to action.
The pressure on enterprise AI initiatives has changed. Teams are being asked to move faster, prove value sooner, and make outputs usable inside real operating workflows. A simple question-answer bot does not solve that problem. Enterprises need AI systems that can surface what matters, reason in context, and drive action with traceability, control, and trust.
Qlik’s latest agentic analytics release is designed around that reality. Qlik Answers remains the entry point, combining structured analytics and unstructured content to deliver richer, more contextual answers. Discovery Agent monitors key data areas and helps surface important changes and anomalies early so users can act faster. Automate Agent executes actions and workflows in downstream systems based on insight and agentic reasoning. Predict Agent builds machine learning models, generates predictions, and helps answer forward-looking questions. Analytics Agent helps teams accelerate analytics development tasks and creation workflows more efficiently.
“The bar for enterprise AI is getting much higher,” said Mike Capone, CEO, Qlik. “It is not enough to produce a fluent answer. AI has to understand the business in context, run on a trusted foundation, and connect insight to action in the systems teams already use. That is how organizations create value without adding more fragility, lock-in, or spend.”
Key advances in agentic analytics
- Qlik Answers as the entry point for agentic analytics: Qlik Answers brings together structured analytics and unstructured content in one governed experience, designed to support richer responses and follow-up reasoning rather than isolated prompts.
- Semantic Layer for governed business context: Qlik is extending data products with shared, reusable business definitions — including measures, dimensions, and relationships — so Qlik Answers, analytics apps, and third-party assistants can work from more consistent business meaning across analytics and AI workflows.
- Discovery Agent for early signal detection: Discovery Agent monitors key data areas, detects anomalies and important changes, and delivers prioritized signals so users can investigate earlier and act faster.
- Analytics Agent for analytics development: Analytics Agent can now support analytics development tasks in addition to generating insights, helping teams move through creation workflows more efficiently.
- Automate Agent to take action: Qlik extends the path from analysis into execution by enabling teams to trigger workflows directly using natural language.
- Predict Agent for forward-looking insight: Users can ask forward-looking questions, and Predict Agent will build machine learning models, generate predictions, and interpret results to help teams act earlier and with more confidence.
- MCP Server for broader AI access: MCP Server allows third-party AI assistants to use Qlik analytics to support decisions, bringing Qlik’s context-rich calculations into the assistants teams already use while helping preserve value from existing Qlik investments.
Together, these capabilities create a more complete agentic experience: detect, investigate, predict, and act. They also reflect a broader Qlik view that analytics becomes materially more useful when answers are grounded in context, supported by explainable reasoning, and connected to execution.
“What stands out here is the focus on the part that usually gets harder after the demo, helping teams understand what matters, work through why it matters, and move into action without losing trust,” said Charles (Cal) Link, Sr. Director - Data and Analytics, Reworld. “For organizations trying to make AI useful in day-to-day operations, that combination of reasoning, prediction, and workflow follow-through is exactly where the conversation needs to go.”
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, open and reusable data foundations, 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.
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