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Anastasiia
Stefanska
Lead of Data Team
TUI
Anastasiia is a data professional with experience in analytics and consulting, specializing in data, storytelling and machine learning to unlock the data value. Bringing hands-on expertise in data architecture and enablement. She thrives at the intersection of data, business strategy, and community. Anastasiia is a Snowflake Data Superhero recognized for her contributions to data community. Sh is also a Lead of Data Team within Technology Analytics at TUI, where I design tools, programs, enablement paths, and events to empower data-driven culture.
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15 September 2026 13:30 - 14:00
Raising AI: Thoughts on culture, values and companions we build
This talk explores AI not as a product to be shipped, but as a being shaped by the environment, values and habits of the people who build and use it. Drawing on the experience of creating agentic AI platforms at TUI, we argue that AI systems are not born intelligent. They inherit their character from the culture that surrounds them. Corporate AI emerges from years of deliberate work on data literacy, shared language and analytical responsibility. When AI enters that ecosystem, it absorbs those norms or exposes their absence. Our agentic AI platform lets employees query and interact with enterprise data across multiple systems - without deep technical expertise. But making it work was never primarily a technical problem. The harder work is cultural: building shared data language, trust in metrics, and organizational willingness to act on what the data actually says. Without that foundation, an agent that can query anything across your entire data landscape is just noise amplification at scale. By framing AI development as a form of upbringing, this session offers a different lens on responsible adoption: one that centers cultural readiness, moral intent and long-term stewardship over speed and novelty. Attendees will leave with a clearer sense of how organizational values shape AI behavior - and why raising a thoughtful AI companion starts long before the first model is trained.