Qlik AI Demo Showcase

Global Director of AI and Machine Learning, Sean Stauth, demonstrates Qlik’s AI capabilities in market today. In this presentation, he showcase the strategic tenants of a trusted AI foundation, the turnkey benefits of AI-enhanced Solutions, and create custom solutions with self-service AI using real-world use cases with proven AI value: sales, operations, human resources, and IT/information security. Demonstrations include a mix of “day-in-the-life” data science/ML engineering development and end-user experiences with applications from both an analyst’s and executive’s points of view.

Stauth begins with a discussion of the strategic tenets of a trusted AI foundation, the benefits of AI-enhanced solutions, and the creation of custom solutions with self-service AI using real-world use cases in sales, operations, human resources, and IT/information security. His demonstrations cover a range of scenarios, including the use of Qlik’s supervised learning AutoML capability, which has been used to develop over 150,000 models.

Stauth demonstrates the “day-in-the-life” of data science and machine learning development, as well as end-user experiences with applications, providing perspectives from both analysts and executives. He shows how to use the AutoML platform to predict customer churn and build predictive applications with what-if scenarios. He also highlights the importance of explainability in AI models, which allows users to understand why predictions are made and ensures trust in the AI system.

Additionally, Stauth demonstrates the integration of generative AI with Qlik apps in operational use cases, the use of Qlik’s AI assistant with Microsoft Teams for collaboration, and key driver analysis built on top of the predictive AI engine. He emphasizes that the goal is not just to build models but to create apps and solutions that deliver real value to end users.

Stauth also addresses questions about the licensing and pricing of Qlik’s AI capabilities, the differentiation between various types of AI, and the importance of having guardrails and ethical considerations in place when using AI. The presentation concludes with a demonstration of generative AI integration using Amazon Bedrock, showcasing how natural language queries can be used to interact with data and derive insights.