Data-driven Innovation (DDI) Framework:

In this training, participants will gain practical experience of how to apply the Data-driven Innovation (DDI) Framework and Canvas to identify and explore data-driven business opportunities.

The full program will run from 10am – 4pm including lunch.

Date: Wednesday 11^th March 2026
Time: 10am – 4pm
Venue: Room 0M08, UQ Brisbane City, 308 Queen Street, Brisbane City, QLD

Register (Free) by Tuesday 3^rd March 2026

Description of the Course:

Data and Artificial Intelligence (AI) will impact on everyone, every sector, and every citizen. The full impact of Data and AI will be in our hospitals, on our farms, on our roads, in warehouses and at home. In every sector of the economy. Data-driven and AI-enhanced solutions will augment human activity and will change how the digital and physical world interact. To capture the complexity data-driven systems, the design of data-driven business opportunities needs to incorporate various perspectives ranging from customer and user needs and their willingness to pay for new data-driven solutions to data availability and technical capabilities while taking into account the currently established relationships with within the ecosystem.

In this training, we will introduce the Data-driven Innovation (DDI) Framework and show along concrete examples how it can be used to identify and explore data-driven innovation opportunities. Being based on a conceptual model in form of an ontology with a set of categories and concepts describing all relevant aspects of data-driven business opportunities, the DDI Framework provides a tool to reflect the dynamics of supply and demand and the co-evolution and interactions between the scope of the offering (supply) and the context of the market (demand) in systematic manner.

Participants of this course will can gain practical experience of how to apply the DDI Framework and Canvas for an in-depth check of all relevant factors of data-driven business opportunities. Link: https://ddi-canvas.com/

Learning Objectives:

After completing the training, the participant will be able

• to systematically explore data-driven business opportunities
• to answer the majority of questions centered around the irreversible rise of global data businesses.
• to transform non-specific threads of data-driven businesses into (calculable) risks,
• to explore the full potential of data driven business opportunities and
• to successfully manage the transition from initial data-driven ideas towards completely new business models and processes of value creation.

Prof. Dr. Sonja Zillner Biography

Prof. Zillner is the Principal for Industrial Trustworthy Artificial Intelligence at Siemens Foundational Technology. Since 2020, she has been the Head of the Core Company Technology Module “Trustworthy AI” at Siemens AG, and since 2023, she has been leading the design, development, and implementation of the Generative AI Risk Management Process for Siemens industrial products. Since 2021, Prof. Zillner has been an honorary professor at the Technical University of Munich (TUM), Germany.

Prior to her current roles, from 2016 to 2019, Prof. Zillner was invited to consult the Siemens Advisory Board on strategic decisions regarding artificial intelligence. She was the chief editor of the Strategic Research Innovation and Deployment Agenda of the new Partnership in AI, Data and Robotics, and the leading editor of the Strategic Research and Innovation Agenda of the Big Data Value Association (BDVA).

Prof. Zillner studied mathematics and psychology at the Albert-Ludwig-University in Freiburg and earned her Ph.D. in computer science, specializing in symbolic AI, at the Technical University of Vienna.

Prof. Zillner is the author of more than 90 publications and more than 25 patents in the areas of semantics, artificial intelligence, and data-driven innovation.

She currently holds the following positions:

• Head of Trustworthy AI, Siemens AG, Foundational Technologies
• Head of Generative AI Risk Management for Siemens Products, Siemens AG, Foundational Technologies
• Principal Industrial Trustworthy AI, Siemens AG, Foundational Technologies
• Member of the Scientific Advisory Board of the Technical TIB Leibniz Information Center for Science & Technology
• Co-Lead of AI Taskforce in the Charter of Trust Alliance

Register by 3 March 2026. Limited Seats Available.