AI and Data Tracks at Compass AI & Tech Summit: What You'll Learn, Who's Speaking, and Why They're Not Just for Specialists

Google Cloud’s 2025 DORA Report found that 90% of technology professionals now use AI at work. Only 24% say they trust it “a great deal” or “a lot.” That gap between adoption and trust is exactly where the AI and Data tracks at Compass AI & Tech Summit live. Neither track is about hype. Both are about what actually works once the AI honeymoon ends and the production bill arrives.

Compass AI & Tech Summit brings CTOs, engineering leaders, and hands-on practitioners together for two days in Budapest. The AI and Data tracks are where that gets concrete: real architecture decisions, real failure stories, and real numbers from teams that have already shipped AI into production and lived with the consequences.

What You Can Learn in the AI and Data Tracks

Between the two tracks, four themes stand out this year, and none of them are “how to prompt a chatbot.”

In the Data Track

• How the data engineering role is actually changing. Olena Kutsenko from Confluent tackles this directly. Her talk walks through a real case where AI-generated code looked correct, passed initial checks, and still quietly broke – because it missed edge cases only a human would catch. Mark Rittman takes the long view: he traces every decade since 1974 in which a new tool promised to replace the data developer, and explains why the bottleneck was never typing speed. It’s thinking speed. Both talks reach the same conclusion from different angles: AI removes the boring work, not the judgment.
• How to architect data systems for AI agents, not just dashboards. Fabiane Nardon from TOTVS walks through what happens when you put an AI agent in front of real enterprise data and why data lakes built for analysts don’t hold up under agent-driven traffic. Oleksandra Bovkun from Databricks covers a related problem: giving AI-native applications persistent memory instead of a one-off chat window. Dejan Menges from Vinted rounds this out with a talk on moving a large monolith toward an event-driven platform that serves users across continents. Elsewhere in the track, Emilie Schario from Kilo and Shachar Meir both look at where the data career itself is heading as AI takes over more of the routine work.

In the AI/ML Track

• The parts of AI adoption nobody puts in the pitch deck. Serban Petrescu from Trilogy shares a genuinely uncomfortable story: a vision-model pipeline built to protect exam integrity that kept flagging students for drinking water. Thomas in’t Veld from Tasman Analytics makes the case that culture, not tooling, is what actually separates teams that get results with AI from teams that don’t.
• Where the deep technical edge is heading. Bryce Adelstein Lelbach from NVIDIA introduces cuTile, a new way to write GPU code without wrestling with parallel programming directly. Eszter Windhager from ONEKEY shows how machine learning and LLMs are used to catch security vulnerabilities in embedded firmware most teams never think to check. Leo Sjöberg from incident.io closes the loop with a talk on building AI systems that evaluate and improve themselves in production.

How the AI and Data Tracks Connect to the Rest of the Summit

Neither track runs in isolation. Both sit alongside the Leadership, Product, and UX/UI tracks across the same two days, and several talks deliberately cross those lines. Emilie Schario’s Data track talk, for instance, looks at engineers who increasingly act as orchestrators of AI agents rather than as people who write every line themselves – a topic that overlaps directly with the Leadership track’s conversations on scaling agentic engineering across whole organizations. Shachar Meir’s Data track talk on building a high-impact data career speaks just as directly to individual contributors as it does to the hiring managers sitting two seats over.

That overlap is intentional. Compass AI & Tech Summit exists to connect the people building AI systems with the people deciding how those systems get funded, staffed, and adopted – and the AI and Data tracks supply the technical grounding that makes those conversations useful instead of theoretical.

Why the AI and Data Tracks Are Worth Attending Even If You’re Not a Specialist

Here’s the case for showing up even if data engineering or ML isn’t your job title.

McKinsey’s November 2025 State of AI survey found that 88% of organizations now use AI in at least one function, but no more than 10% are actually scaling AI agents in any given function. In other words, using AI has stopped being a differentiator. Understanding how it actually works in production has become one instead – and that understanding isn’t confined to engineers anymore.

Product managers now need enough data literacy to have a real conversation with the engineers building their AI features, not just a roadmap slide about them. UX and design teams are moving toward what Nielsen Norman Group calls the “AI-UX Generalist” – designers who understand when a model might hallucinate and how to design around that, not just how to style a chat interface. Engineering leaders, meanwhile, are the ones who decide whether a team’s platform is solid enough for AI to amplify good work instead of amplifying mistakes faster.

If you lead a product, design a workflow, or manage a budget that touches AI in any way, the AI and Data tracks hand you the technical fluency to ask sharper questions in every other conversation you have this year.

Frequently Asked Questions

What topics do the AI and Data tracks cover at Compass AI & Tech Summit? The Data track covers data engineering’s changing role and architecting data systems for AI agents. The AI/ML track covers honest accounts of what fails in AI adoption, plus deep technical talks on GPU programming and ML-driven security analysis.

Do I need a technical background to follow the AI and Data tracks? Most talks are built for engineers and technical leaders, but several – including the talks on data careers and AI adoption culture – are accessible to product, design, and leadership audiences as well.

Who are some of the speakers in the AI and Data tracks? The Data track features speakers like Olena Kutsenko (Confluent), Fabiane Nardon (TOTVS), Oleksandra Bovkun (Databricks), Dejan Menges (Vinted), and Mark Rittman (Rittman Analytics). The AI/ML track features speakers like Bryce Adelstein Lelbach (NVIDIA), Uwe Friedrichsen (codecentric AG), and Serban Petrescu (Trilogy), among others.

How do the AI and Data tracks fit with the rest of the Summit? Both run alongside the Leadership, Product, and UX/UI tracks, and several talks deliberately connect to those tracks’ themes around scaling AI adoption and engineering leadership.

Ready to Join the AI and Data Tracks?

Two days. Practitioners who’ve actually shipped AI into production, not just demoed it. See the full agenda for the AI and Data tracks and get your ticket to Compass AI & Tech Summit.

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