Qlik Connect 2026 Expands Keynote Program as Enterprises Prepare for the Next Wave of AI

Why It Matters

Enterprises that can operationalize AI with trusted data will gain a competitive edge as AI becomes a core business expectation. Qlik’s focus on governance and accountability addresses the growing demand for transparent, auditable AI deployments.

Key Takeaways

• Qlik Connect 2026 adds AI thought leaders Jason Del Rey
• Dr. Rumman Chowdhury joins to discuss ethical AI
• Program shifts focus from AI hype to operational accountability
• Sessions will showcase Qlik’s upcoming agentic AI features
• Customers share measurable outcomes from data‑driven AI projects

Pulse Analysis

The 2026 edition of Qlik Connect arrives at a pivotal moment for enterprise AI. After years of pilot projects, organizations are now pressed to embed machine‑learning models into daily decision‑making pipelines. Qlik’s expanded keynote roster—featuring journalist Jason Del Rey and ethics specialist Dr. Rumman Chowdhury—signals a broader industry shift toward not just building models, but ensuring those models operate under clear governance, auditability, and trust. By framing AI as an operational expectation, the conference underscores the need for data platforms that can enforce lineage, access controls, and real‑time monitoring.

Qlik’s strategy for the event centers on practical enablement. Workshops and breakout sessions will walk attendees through the company’s upcoming agentic capabilities, which promise to automate routine actions while preserving human oversight. The integration of MCP‑based interoperability aims to break down data silos, allowing analytics to flow seamlessly into business applications. For data leaders, these sessions provide a roadmap for scaling AI initiatives without sacrificing compliance, a concern amplified by recent regulations and heightened stakeholder scrutiny.

Beyond technology, Qlik Connect 2026 tackles the cultural and organizational dimensions of AI adoption. Speakers will discuss how to embed accountability into team structures, align AI outcomes with measurable business value, and foster cross‑functional collaboration between data engineers, analysts, and business units. By delivering concrete use‑case narratives and measurable ROI examples, the conference equips executives with the confidence to transition AI from experimental labs to reliable, revenue‑generating engines.