Kitsoft

First, it should translate principles into implementable design patterns, such as auditability, human-in-the-loop decision points, and traceable AI-supported processes. Second, it should promote common standards for interoperability, including data exchange, digital identity, and workflow orchestration, enabling systems to function across institutions and borders. Third, capacity-building must be recognized as a core pillar of governance, ensuring that governments can design, deploy, and maintain systems independently. Fourth, the Dialogue should support the adoption of open and reusable building blocks, reducing duplication and increasing transparency. Ultimately, success would mean shifting from dependency-based models to sovereign capability.

• Open-source software, open data and open AI models
• Transparency, accountability, and human oversight
• Safe, secure and trustworthy AI
• Interoperability of governance approaches

Public services require systems that are not only reliable, but also explainable and auditable. Interoperability of governance approaches is critical, as AI systems in government rarely operate in isolation. Without common standards for data exchange and system interaction, governance frameworks remain difficult to implement at scale. We also emphasize (and lead by example) open-source software as enablers of transparency and long-term sustainability. Open approaches allow governments to better understand, verify, and evolve their systems while reducing dependency on vendors.

Instead of treating legislation as static text interpreted manually, regulatory requirements can be formalized into executable logic, for example: - eligibility rules encoded in service workflows - compliance checks enforced automatically during processing - audit trails generated by design. This concept is called "Law as a code". Addressing it would enable more consistent, transparent, and scalable implementation of AI governance, and help bridge the gap between regulatory intent and real-world system behavior.

Ukraine demonstrates how rapid digital transformation can successfully coexist with evolving AI governance. The country has built large-scale, trusted digital public services, such as the Diia ecosystem, delivered with contributions from companies like Kitsoft - serving millions of users and embodying a "state in the smartphone" vision. At the same time, coordination across ministries is still developing, and a broader mindset shift is needed to consistently translate governance principles into system-level implementation. Ukraine's experience shows that even under conditions of forced innovation, it is possible to build resilient, scalable systems, while highlighting the importance of making governance frameworks operational in practice.

It can promote the adoption of common building blocks and architectural approaches already proven in digitally advanced countries such as Estonia, Ukraine, Denmark, and the UK. Sharing these practical models helps reduce fragmentation and accelerates adoption across regions. The Dialogue can act as a platform to highlight success stories and scalable digital public goods, enabling countries to learn from real deployments rather than abstract frameworks.

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Stakeholders should contribute through clearly structured, role-based engagement formats that connect policy, technology, and implementation. Governments can provide policy direction and real use cases; private sector and GovTech actors can demonstrate practical solutions; academia can support with research and evaluation; and civil society can ensure inclusivity and accountability. To make the Dialogue effective, the structure should combine: - showcase sessions highlighting proven open-source and scalable GovTech solutions - thematic roundtables focused on concrete approaches such as interoperability, capacity-building, and law-as-code - hands-on workshops and live demonstrations, where participants collaboratively design and build simplified digital public services using no-code or low-code tools

Women remain underrepresented in global AI governance discussions, particularly in technical and decision-making roles. Yet their perspectives are essential, especially in public service design, where attention to inclusivity, accessibility, and vulnerable user groups is critical. To better include these voices, targeted capacity-building initiatives should be expanded, creating safe and supportive environments where women can develop, test, and apply their expertise. This includes hands-on programs, mentorship, and opportunities to contribute to real system design (by women for women). Strengthening these pathways will help ensure that AI governance frameworks are more human-centered and reflective of diverse societal needs.

More effective engagement can be achieved by shifting from discussion to demonstration and co-creation. Formats as live service-building demonstrations, step-by-step walkthroughs of digital public service creation, and hands-on, hackathon-style workshops allow participants to directly experience how governance principles translate into real systems.