
The Data Innovation Summit ANZ brings together the most innovative minds in data, analytics, and AI from across the region. This influential annual event connects enterprise practitioners, technology providers, startup innovators, and academics who work with applied data innovation, data science, big data, machine learning, and generative AI. The summit creates a unique space for professionals to discuss ways to accelerate AI-driven transformation throughout companies, industries, and public organizations.
The event is designed to address all elements of data-driven and AI-ready business including data, people, processes, and technology. With over 30 speakers spread across three main stages, the summit balances business and technical content while remaining both practical and inspirational. The format includes keynote presentations, TIP sessions, and extensive networking opportunities in the exhibition area.
Attendees can explore four distinct stages, each with specialized focus areas. The keynote stage sets the tone with visionary presentations from leading experts. The AI Value & Strategy Stage concentrates on aligning generative AI with core business objectives and managing implementation risks. The Modern Data Strategy Stage emphasizes scalable data ecosystems and cloud integration.
The Business and Data Analytics Stage shifts focus from data-driven insights to decision-centric practices. This track covers emerging technologies in self-service analytics, real-time processing, and AI-driven insights. Sessions explore decision intelligence, natural language processing in analytics, and embedding analytics directly into business processes.
As part of a worldwide movement with over 1500 practical case studies presented across Europe, MEA, APAC, and ANZ regions, this summit connects a global community of data and AI practitioners. The event is limited to 200 delegates, creating an intimate environment for meaningful connections and knowledge sharing among professionals working to enhance customer experience, improve operations, and develop data-driven products and services.