Qlik AI-Enhanced and AI Roadmap Deep Dive

In this presentation, VP of AI Strategy, Nick Magnuson, will share Qlik’s product direction for helping customers mitigate the risk, embrace the complexity, and scale the impact of AI by creating a trusted AI foundation, benefiting from AI-enhanced solutions, and creating custom solutions with self-service AI. Grounded in market and customer research, he shares how Qlik’s vision for helping customers integrate generative AI across their organizations. Joining Nick is Ryan Welsh, Field CTO and former CEO of Kyndi, an innovator in natural language processing, search, and generative AI, recently acquired by Qlik.

Magnuson outlines a three-pillar strategy for AI implementation: establishing a trusted AI foundation, infusing AI into their data integration and analytics products, and enabling customers to build custom AI solutions. He emphasizes the importance of data foundations, including data veracity, processing, observation, quality, integration, governance, and lineage. He also discusses the use of AI to make data foundation tasks more efficient, such as using natural language to generate SQL queries. He addresses questions about where the AI runs and clarifies that Qlik provides the pipeline for data movement, not a data warehouse, and mentions the acquisition of Talend for enhancing their portfolio.

The presentation includes a discussion about the use of AutoML, which has seen rapid adoption and has helped customers like ARH, a regional health system, save significant amounts of money by predicting patient no-shows and taking appropriate actions. Magnuson also touches upon the roadmap for AI, which includes advanced analytics and time series forecasting. He stresses the importance of feedback in shaping their AI strategy and notes the shift towards practical applications of generative AI in 2023.

Ryan Welsh, Field CTO and former CEO of Kyndi, speaks about the acquisition of Kyndi by Qlik and its implications. Kyndi specialized in natural language processing, search, and generative AI, and their technology aimed to provide trustworthy answers from unstructured text data. Welsh highlights the challenges of making large language models understand domain-specific content and explains how Kyndi’s technology addresses this issue.