Meet Ewa
Attorney at Law | Tech Counsel
Shaping business‑aligned decisions on AI governance, privacy and regulatory strategy
EU-qualified attorney working for Octave, a leading software provider for critical industries, with prior experience across digital products and healthcare R&D
Contributor to United Nations AI governance initiatives, former parliamentary legal advisor
Experienced with AI Act, GDPR, NIS2, DSA/DMA, ISO 14001 and broader EU and international AI, data protection and digital frameworks
What I help with:
Designing operational AI governance structures and processes
Advising on the development of AI-embedded products and services
Identifying and managing regulatory and operational risks
Data protection in complex, regulated environments
Cybersecurity and incident response
Insights
Find practical guides for decision-makers turning AI governance and compliance into business value.
Through use cases and concrete solutions, I translate real-world data protection challenges into actionable strategies that work in practice.
Occasionally sharing perspectives from UN AI governance initiatives to broaden the context. Read more
For business leaders, founders, strategists and tech professionals balancing innovation, risk and responsibility.
Selected Insights
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Industrial AI: the most important AI systems don’t live in popular chatbots – they run industry. This article focuses on 4 practical things industrial AI vendors and buyers should get right: industrial bias, meaningful documentation, trainings on buyer’s data and real human oversight. Not theory, but workable solutions.
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From UN negotiations to ITU standards, these processes can turn global AI experience into practical guardrails for human oversight, procurement and cybersecurity that scale from small organisations to complex systems. I am proud to contribute to this work and share behind-the-scenes insights here.
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Whether you’re developing large or small AI models, or adapting existing systems for your business needs, understanding the legal landscape of training data is essential. This article explores six common data sources, providing practical guidance for using data in an evolving regulatory environment.
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Trust in AI isn’t automatic – it’s earned through responsibility, transparency, and ethics. Whether it’s consumer apps or enterprise systems, people increasingly choose solutions that make data usage understandable, AI behavior explainable and security safeguards visible. Companies that take this seriously can turn “the Responsible AI” into a powerful business asset.
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Most companies buy AI rather than build it, but they remain responsible for the risks it creates. Through a practical use case, this article explains why a well-governed MVP, clear ownership, user involvement, and effective monitoring matter more than ambitious policies or technical promises.
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What do business clients expect from AI solutions? Not just intelligence, but also responsibility and compliance. I ran a workshop with AI faculty students where we explored exactly that. Their insights left me genuinely inspired and I want to share a few key takeaways that every AI developer should hear.