Qlik AI Strategy Overview

A recognized leader in analytics and data integration and quality, Qlik is trusted by 40,000 customers and 500 non- profits worldwide to help them use data, analytics and AI to create value by solving theirs and the world’s greatest challenges. In this presentation, VP of Analytics and AI Portfolio Marketing, Mary Kern, introduces Qlik’s strategy for helping organizations mitigate the risk, embrace the complexity, and scale the impact of AI.

Kern highlights Qlik’s history of innovation in visual analytics and its continued efforts in analytics, data integration, data quality, AI, and automation. She notes that Qlik supports over 40,000 organizations and 500 NGOs worldwide in leveraging data and AI to solve significant challenges. Kern discusses how Qlik took a step back to understand what organizations want from generative AI, finding that companies seek a partner to help them safely embrace AI, manage its complexity, and scale its positive impact. Qlik aids customers in building a trusted foundation for AI through broad data connectivity, intelligent data pipelines, data transformation engines, robust data catalogs, and lineage for traceability and trust.

Qlik offers turnkey AI solutions, enabling organizations to scale data-driven decisions across their teams through automated insights, natural language experiences, proactive alerts, and notifications. They also provide self-service AI solutions, including AutoML, data science, and generative AI offerings, under the umbrella of Qlik Stage. This set of solutions is designed to bring AI strategies to life while minimizing risk, handling complexity, and maximizing AI’s impact. Kern explains that Qlik has been an AI-enhanced analytics leader for years, using early LLMs like BERT to deliver prompt experiences in analytics. Qlik’s Insight Advisor acts as an AI assistant, helping developers auto-generate visualizations and dashboards, and enabling business users to ask questions and receive relevant answers in various formats and languages.

Qlik’s acquisition of predictive and AutoML capabilities allows customers to scale their data science investments by creating machine learning models to solve business problems. Kern cites examples of customers using Qlik’s AI capabilities, such as Airbus, Schneider Electric, and JB Hunt. During the Q&A, Kern and her colleague Nick elaborate on Qlik’s AutoML, which makes modeling more accessible to technical users. They discuss Qlik’s ability to handle both structured and unstructured data, with a focus on integrating data from diverse sources to find patterns that humans cannot interpret alone. They emphasize Qlik’s agnostic approach to data sources and its support for direct queries and in-memory computation to manage data effectively. The conversation also touches on Qlik’s use of open-source algorithms and standardized practices in AutoML. The company aims to simplify the process from experimentation to deployment, allowing users to easily integrate AI and machine learning into their existing Qlik dashboards and decision-making processes. Qlik’s platform facilitates the ingestion of data, transformation, and deployment of AI solutions without requiring heavy customer engagement or complex hardware setups.