Qlik Connect 2026: Turning AI Ambition Into Action

At Qlik Connect 2026, recently held in Orlando, Florida, it was made clear the AI conversation has shifted. It is no longer about experimenting with AI. It is about making it work in real-world enterprise environments, where trust, governance and measurable outcomes are important.

Across two days of general sessions, press releases and direct conversations with executives including Sam Pierson CTO and Ryan Welsh, Field CTO it became apparent that organizations are under pressure to turn AI ambitions into operational reality.

That pressure is coming from the top. As Mike Capone, Qlik’s CEO, noted during the opening general session, “Companies are spending a lot of money on AI, but they’re not getting the return.”

This framing set the tone for the week, emphasizing that the industry is moving past pilots and into a phase where results are expected.

From dashboards to outcomes

One of the most significant shifts discussed was the move away from traditional dashboards toward agent-driven outcomes. In a direct conversation with Sam Pierson, CTO at Qlik, he explained how the company is rethinking the ways users interact with data.

“The future of SaaS is not going to be people going and looking at dashboards. They’re looking at dashboards and they’re looking at data to accomplish a job. So, if we can accomplish that job easier, faster or more automatically, then it’s a big benefit for our users,” Pierson said.

This shift is driving Qlik’s broader push into agentic AI. Rather than simply presenting insights, the platform is evolving to help users take action. New capabilities across Qlik Answers, Discovery Agent and automation tools are designed to move users from detecting signals to executing decisions within the same workflow.

The introduction of additional agents across the platform reinforces this direction, with automation extending from simple productivity gains to more complex analysis and decision support.

Making AI practical with advisory services

To address the gap between AI ideas and execution, Qlik introduced a new advisory offering aimed at helping enterprises prioritize and operationalize use cases.

As highlighted in the announcement, “The hardest part of agentic AI is usually not generating ideas… It’s deciding what to pursue, shaping that into a use case the business can execute.”

This reflects a growing challenge across industries. Many organizations have no shortage of AI concepts, but they lack a structured way to evaluate and implement them. The new advisory service focuses on aligning use cases with business value, governance readiness and execution planning.

Ryan Welsh, field CTO GenAI at Qlik, reinforced this point in conversation, noting the importance of narrowing focus.

“It can solve all problems and no problems. When you’re trying to solve all problems, you just don’t have enough focus to actually address something. And there is a gap between industry understanding of what can be solved and the technologies themselves; and one way of solving that is by actually putting people in the middle and advising your customers on how to use these technologies appropriately.”

Trust becomes a requirement, not a feature

Another major theme was trust. As AI moves deeper into decision-making and automation, the reliability of underlying data has become critical.

Qlik’s expanded trust and governance capabilities aim to make data quality visible and actionable through mechanisms such as trust scores, anomaly detection and service-level monitoring. The goal is to ensure both humans and AI systems can act with confidence.

This aligns with a broader industry realization that poor data quality directly impacts AI outcomes. As explained during the keynote, on the topic of adoption – trust can quickly erode when results are inconsistent or unverifiable.

AI sovereignty and enterprise constraints

As organizations scale AI globally, new challenges are emerging around data residency, compliance and infrastructure limitations. Qlik’s AI Sovereignty Initiative addresses these concerns by giving enterprises more control over where data and AI workloads are deployed.

This is particularly relevant as regulatory requirements continue to evolve.

Welsh emphasized how vital this has become for customers operating across regions.

“It’s just absolutely critical for us to operate within the rules and regulations of global governments, but then also just in support of our customers,” he said.

The initiative also reflects a broader shift in enterprise architecture, where flexibility and governance must coexist. Organizations need to move quickly while maintaining control over sensitive data and ensuring compliance with regional policies.

Data engineering becomes agent-driven

Behind the scenes, data engineering is also undergoing transformation. New capabilities such as declarative pipelines, real-time routing and streaming integration are designed to reduce manual effort and accelerate the delivery of AI-ready data.

Capone highlighted the underlying challenge in a press statement, stating, “Most companies do not struggle to imagine AI use cases. They struggle to deliver the trusted, current data those use cases depend on.”

In a conversation with Pierson, he followed Capone’s statement by pointing to the complexity of making analytics usable for AI systems.

“Being able to move that from this programmatic mathematical representation, being able to put that into a set of language and context that the LLMs can understand and then pass back to the user, I think those have been some of the really interesting technical challenges that we’ve had,” said Pierson.

This shift toward agent-assisted engineering reflects a broader move toward intent-driven workflows, where teams define outcomes and systems handle execution.

Strengthening the ecosystem through partnerships

Qlik also announced an expanded partnership with ServiceNow, aimed at connecting enterprise data with workflow execution. This integration brings governed analytics directly into operational systems, enabling more context-aware decisions.

“Workflows and AI agents are being asked to do more than route work. They are being asked to interpret business conditions and act with better judgment,” said James Fisher, chief strategy officer at Qlik, via the press announcement about it. “That takes more than system data on its own. It takes the ability to combine ServiceNow signals with broader enterprise context, apply analytics and AI, and feed that intelligence back into the workflow where action happens.”

This partnership underscores the importance of embedding AI into existing systems rather than treating it as a standalone capability.

A shift toward operational AI

The announcements at Qlik Connect 2026 point in a clear direction. The focus is no longer on isolated AI tools, but on building integrated systems that connect data, analytics and action. The combination of agentic analytics, governance frameworks, advisory services and ecosystem integrations reflects a thoughtful approach to enterprise AI. Qlik has shown that the future of AI will be defined not by experimentation, but by execution.

The post Qlik Connect 2026: Turning AI Ambition Into Action appeared first on Enterprise Times.