Qlik CEO: ‘Trusted Data Foundation’ For AI Is The Theme At This Week’s Connect Event

Why It Matters

Without reliable, governed data, AI initiatives cannot deliver the promised efficiency or financial returns, making Qlik’s data‑centric approach a critical differentiator for enterprises seeking measurable AI ROI.

Key Takeaways

• Qlik spent $2 billion on R&D and 14 acquisitions to build data foundation
• 86% of AI projects fail to deliver expected ROI, according to studies
• Qlik’s Trust Score lets customers assess data quality before AI modeling
• New partnership with ServiceNow links data governance to workflow automation
• Qlik Connect will showcase real ROI from agentic AI deployments

Pulse Analysis

Enterprises are racing to embed AI into core processes, yet a growing body of research shows that poor data quality is the primary cause of stalled projects. Qlik’s CEO Mike Capone emphasized that a “trusted data foundation” is non‑negotiable for agentic AI, which automates decisions across the organization. By integrating data from ERP, mainframes and cloud sources, Qlik claims to deliver the clean, governed datasets that AI models require. This message anchors the agenda of the Orlando‑based Qlik Connect conference, where the company will demonstrate how its platform turns raw data into actionable intelligence.

Qlik’s roadmap is backed by roughly $2 billion in R&D spend and fourteen strategic acquisitions, a scale that underpins its Trust Score—a metric that lets customers audit data readiness before feeding models. The AI Council, composed of external ethicists and regulators, further differentiates Qlik by addressing compliance and governance concerns that many vendors overlook. Recent announcements, including the Qlik Discovery Agent, MCP Server and an expanded partnership with ServiceNow, extend the platform’s reach into workflow automation, enabling a seamless hand‑off from insight to execution.

For the broader market, Qlik’s open‑architecture stance challenges the closed‑loop approaches of large ERP and CRM vendors. By supporting heterogeneous environments such as Snowflake, Databricks and Azure Synapse, Qlik positions itself as a neutral data layer that can accelerate AI ROI—a claim bolstered by early customer case studies showing top‑line and bottom‑line gains. Partners can leverage flexible, capacity‑based pricing and the new global channel leadership to tap into the growing demand for trustworthy AI pipelines. If Qlik can consistently deliver on its trusted data promise, it could reshape how enterprises operationalize AI at scale.