Responsible AI Engineering through the Systematic Management of Generative AI Risks

Sonja Zillner, Head of Strategic Research Program Trustworthy AI at Siemens AG

Artificial Intelligence (AI) presents significant opportunities for new business ventures within the industrial domain. However, its adoption introduces a broad spectrum of risk sources across dimensions such as cybersecurity, reliability, robustness, safety, transparency, or human oversight. Simultaneously, organizations are confronted with an increasing amount of digital and AI-based legislation in the international environment. This leads to a fragmented landscape of legal and risk-related requirements, often inconsistent, overlapping, and duplicated. This results in high uncertainty and bureaucratic burden during the development and deployment of AI products. To address these challenges, a systematic, responsible, and efficient approach is required to handle the complex legal requirements as well as the emerging wide range of risk sources. Responsible AI Engineering describes such a systematic approach, enabling the efficient and innovative development of AI products while ensuring compliance with the complex and fragmented legal landscape. In this presentation, I will introduce the Siemens Generative Risk Management Process as an example of a responsible AI engineering approach. This demonstrates how organizations can drive AI innovation forward in a compliant and risk-aware manner.

The European Data Portal: Enabling data ecosystems and AI in Europe

Inmaculada Farfán Velasco, Project Manager in the Publications Office of the European Union

This presentation will highlight the pivotal role of the European Data Portal in providing guidelines and tools for the development of data spaces and to boost artificial intelligence through data sharing and reuse. We will showcase how the portal serves as a central access point to support the implementation of European data policies by facilitating the reuse of open data across Europe. By its solid experience with stakeholders, technologies, governance mechanisms, standards and data processes, the portal will play an overarching role in the evolution of robust data ecosystems.

Harnessing the Power of GenAI: From wild horsepower to reliable agents

Roberto Gonzalez, Program Manager at NEC Laboratories Europe GmbH

GenAI brings enormous horsepower—but without control, it won’t move the business. This presentation makes the case that reliability, not raw capability, is the bottleneck. It introduces a clear, executive-level approach to making GenAI useful: put a harness on it through transparency (observable behavior and traces), verification (grounding and policy/compliance checks), and control (clear objectives, constraints, and accountable human oversight). It contrasts “autopilot” uses with steerable agents designed for risk-managed outcomes, and outlines pragmatic next steps to instrument, measure, and govern. The takeaway: power matters—but stewardship turns GenAI from wild potential into dependable value.

AI Governance in HTO

Ioannis Tsiliras, Data & AI Transformation Director at OTE Group

Powering AI and Big Data Exploitation with Federated National e-Infrastructures.

Ville Tenhunen, Data Solutions Architect in EGI Foundation

Presentations

Inspirational Speeches – General Slides

AI Governance in HTO – Ioannis Tsiliras