Inside Exadel’s AI & Data Science Community

Building an internal engineering space that actually delivers value takes more than enthusiasm or good intentions. It should bring clarity of purpose, shared values, and a strong connection to real work.

At Exadel, the AI & Data Science community is focused on exactly that: creating a space where experimentation is encouraged, knowledge is shared openly, and innovation translates into everyday engineering practice.

In this interview, Dzmitry Dzichkouski, AI & Data Science Community Lead at Exadel, shares his vision for how this space can evolve, the principles that guide it, and the role it plays in shaping Exadel’s engineering culture in an era of rapid AI adoption.

Vision & Purpose

In your words, what should our engineering community stand for?

For me, it’s about progress through shared knowledge and experimentation. The community should be a learning environment where individuals try new things, share their experiences and knowledge with the community and grow stronger together.

How do you envision the future of our community in the next 1–2 years?

In two years, I want to see an active, self-sustaining ecosystem. A place where teams fluently share what they build, and where people come to find real solutions – not just presentations. Less theory, more doing.

What impact would you like to see this community have on Exadel’s engineering culture?

I want it to raise the bar. I want engineers to feel proud to be part of Exadel because they see peers sharing insights, experimenting with new tech, and creating value together. The community should become part of how we work, not something extra on the side.

Values & Culture

What values are most important to you when building and leading community spaces?

Openness, humility, and craftsmanship. Everyone has something to teach and something to learn. It’s about sharing what works, admitting what doesn’t, and improving together.

What behaviors or mindsets should we encourage — or discourage — in our community?

Encourage curiosity, initiative, and honest feedback. Discourage gatekeeping, ego-driven debates, and empty talk. We grow faster when we stay curious and are not afraid to jump into things and get our hands dirty!

How can we create a safe, inclusive space where engineers feel confident sharing and learning?

By focusing on respect, trust, and giving space for experimentation. Every contribution matters, regardless of title or experience. We should reward contributions and make it clear that mistakes are an acceptable and necessary part of learning.

Needs & Support

What challenges do you face as a community leader right now?

Balancing time between community work and project delivery both for the contributors and myself. It’s also a challenge to turn enthusiasm into consistent participation – people want to engage but need structure and clear value.

How can we better recognize and celebrate community contributions?

Highlight real impact. Showcase people who share knowledge, build tools, or drive initiatives. Recognition doesn’t have to be formal – just visible and sincere. Right now, we are mostly visible inside the community itself, and much less outside.

Collaboration & Communication

How can we align better with company goals while maintaining a strong community identity?

By speaking the same language as the business: show how communities improve delivery, innovation, and talent growth. But we need to maintain autonomy in how we get there. That’s what keeps the community alive.

Supporting Colleagues Through the AI Community

How can the AI Community provide real value to teams in engineering, product, design, and beyond?

By being a bridge between research and daily work. We can test AI tools, document what works, and translate complex ideas into usable workflows that teams can adopt.

What AI-related challenges or questions do your teams face that the AI Community could help address?

How to integrate AI responsibly and efficiently into existing systems. How to monitor and try new tools and techniques that are popping up by the dozen each day. How to separate real value and things that work from hype. Teams also need guidance on data privacy, model validation, and automation best practices.

Are there specific workflows or tools in your daily work that you believe AI could improve?

100%! Documentation, test automation, code review, project estimation, and data analysis. AI can reduce friction in repetitive or analytical tasks, freeing engineers to focus on design and architecture.

Which roles or departments do you think could benefit most from support or collaboration with the AI Community? (e.g., QA, Data Analysts, Designers, Project Managers)

My take is that it doesn’t really matter what department or role you are in. If the innovation pace stays the same, the contents and essence of the work we are doing now will be reimagined in 2-3 years by AI. I believe these skills will help everyone to stay relevant in any new or existing roles.

What AI topics or technologies are your colleagues curious about but don’t yet fully understand or apply?

Context engineering, automation agents, data governance, and AI-assisted software development. People hear about them and start using them, but the adoption level and effective usage are still far from ideal or complete.

How can we make AI feel more accessible and practical to non-technical teams?

Speak their language. Show simple, real use cases. Don’t start with the solution – start with the problem and add tools and complexity in layers, demonstrate how it’s done, and what the benefits are.

What would make the AI Community feel like a go-to resource instead of just a knowledge-sharing group?

Visibility. Delivering real results. Build prototypes, share reusable tools, and help teams solve real problems. Once people see outcomes, they’ll come to us first. We can show a couple of examples already (Automated AI Scouting report, n8n learning course), and that is just a start.

AI and data are reshaping how engineering work is done.

But tools alone don’t create progress. People do.

By creating a space grounded in experimentation, shared learning, and real outcomes, Exadel is building an environment where engineers can grow, adapt, and stay relevant as the pace of innovation accelerates.

As Dzmitry’s perspective shows, when curiosity is encouraged, practice is valued, and results are made visible, progress becomes part of everyday work — not something extra on the side.