Digital transformation today means far more than introducing new technologies – it determines whether organizations remain controllable and capable of making decisions under conditions of uncertainty.

In a world of growing complexity, new business models, interconnected IT landscapes, and increasing use of AI, capabilities and core future competencies are more important than ever. This event demonstrates how model-based approaches from research, practice, and technology help make interdependencies transparent, enable informed decision-making, and ensure effective governance.

An event for everyone who wants to understand, shape, and effectively steer digital transformation.

Markets remain volatile, regulations are increasing, and AI is accelerating change. Meanwhile, companies need to cut costs and secure growth. Within this “wicked mess,” traditional planning reaches its limits.

Enterprise models are becoming the shared operating language between business and IT. These models create transparency around value creation, dependencies, and cause-and-effect relationships, make the impact of decisions visible, and enable informed steering before changes are implemented.

This presentation illustrates how contextualized, trustworthy models create value: as the foundation for a Digital Twin of the Organization and for reliable information that enables evidence-based rather than intuitive decision-making.

Generative artificial intelligence is rapidly transforming how information is created, processed, and used in organizations. While it promises efficiency gains and new capabilities, it also increases complexity in decision-making: information volumes grow, relationships become less transparent, and human judgment and design capabilities risk being eroded.

This talk argues that organizational resilience in the age of generative AI does not primarily result from more technology, but from structure, context, and interpretability. Enterprise Models provide exactly these values and serve as communication interface with AI. This talk presents conceptual modeling as a means to better communicate with AI, guide AI input, and mitigate the risk of human and enterprise deskilling in information systems development.

In this session, BCF will demonstrate how it implements FINMA’s regulatory requirements for managing data- and critical function-related risks using a model-based inventory.

Using ADOIT, critical functions, along with the associated applications and data objects, are identified, structured, and classified to enable targeted protection. This approach includes identifying applications that process customer identification data, assessing them using a decision tree, and reclassifying them based on security criteria.

This initiative provides transparency into dependencies, delivers concrete organizational insights, and creates value through visual representation and a collaborative data foundation.

How can organizational resilience be made actionable?

This presentation demonstrates how organizations use model-based transparency to reveal the relationships between strategy, processes, and IT, and to make well-informed decisions. Through practical examples, the presentation illustrates how ADONIS and ADOIT transform models from mere documentation artifacts into integrated decision support and early warning systems.

Discover how AI-supported analyses, impact and dependency analyses, and automatically updated models can help you systematically identify risks and make targeted adaptations.

This presentation offers a practical perspective for those who want to operationalize resilience rather than merely discuss it.