The full agenda

Demo 1: Creative & Generative AI

To be Announced...

David Bennett

Panel 1 - Beyond the Pilot: Making Enterprise AI Pay Off

79% of enterprises struggle to turn AI investment into value — yet the winners report 5-10x returns. Leaders from global enterprises on what separates pilots that die from AI that pays.

Barbara Cresti, Bala Muthiah +2 more

Workshop 1: The Ultra-Scale Talk: Scaling Training to Thousands of GPUs

Training large language models demands more than raw compute. it requires a deep understanding of parallelism and architecture choices. This talk dives into the practicalities of ultra-scale training: how 5D parallelism makes it possible to stretch a single run across massive GPU clusters, how Mixture-of-Experts architectures introduce new scaling dimensions and stability challenges, and the performance tuning and communication patterns that drive throughput. Drawing from the Ultra-Scale Playbook and real-world scaling efforts, we'll cover benchmarks, hard-earned lessons, and hands-on recommendations for engineers and researchers ready to train state-of-the-art models efficiently!

Nouamane Tazi

Keynote 4: Gen AI: Myths and Reality

Despite what you might think from reading the news since late 2022, Artificial Intelligence did not appear with ChatGPT. This "Revolution" is merely the fruit of a long maturation, spanning several decades. After a brief historical review, we'll delve into these new AIs, the Generative AIs. We'll look at their limits and potential, and how they can be used for good or ill. Finally, we'll try to understand what the prospects are for us, humans, and for these technologies.

Luc JULIA

Demo 2: Satellites, Planes, Trains: Why Hardware's Cursor Moment Just Started

Claude and Cursor are already transforming how software is written: accelerating development, augmenting engineers, and collapsing the gap between idea and implementation. Hardware is next. I'd like to talk about how AI-augmented systems engineering will do for complex physical systems design (satellites, airplanes, trains) what these tools are doing for code: turning months of fragmented, document-heavy engineering work into a fluid, intelligent process. This isn't speculative: the foundations are being built now. At Systellar, we've developed Synapse™ specifically to bring AI into the core of how complex hardware programs are designed, traced, and validated. My talk will explore what this transformation looks like, why hardware has been harder to crack than software, and what the future of engineering looks like when AI becomes a genuine design partner and, eventually, completely transforms the industry into an agentic one.

Alexandre Gol i Mestre

Keynote 6: Moving beyond Productivity: How Enterprise AI Creates Organizational Impact at Scale

AI is taking hold in the enterprise — and yet many organizations are still waiting for the payoff. The tools are powerful. The potential is real. But something fundamental is missing between individual productivity and lasting organizational impact. In this session, we explore some of the challenges and dive into three concrete themes that shape the next chapter of enterprise AI: how generative UI shifts enterprise software from navigation to intent; how company memory grounds agents in organizational context; and how tabular AI democratizes business predictions. Actionable, opinionated and anchored in product truth.

Florian Kunzke

Panel 2 - Rebuilding the Org Chart: What Actually Breaks When Enterprises Restructure Around AI

Every enterprise AI rollout eventually stops being a technology project and becomes an org design problem. Job descriptions written for execution, teams built around headcount, managers measured on output that agents now produce. This panel goes at the structural rebuild: which roles get redrawn, where the reporting lines break, what upskilling actually costs, and why leadership readiness fails before the tooling does. Enterprise transformation leads and an operator scaling a company through it, on what they had to dismantle before anything worked.

Zakaria Mansour, Malgorzata Luszkiewicz +1 more

Keynote 7 - The art of the possible: Agentic AI

Concrete case studies highlighting what is viable today versus what is emerging over the next 12–18 months.

Pablo Rodriguez

Keynote 8 - Collaborative AI

The best things were never built alone. AI becomes most powerful when it helps teams think, decide, and build together. It can hold shared context, connect conversations, surface decisions, clarify ownership, and keep work moving across people and functions. Instead of living only in individual workflows, AI can become a collaborative layer for the whole team: reducing friction, preserving knowledge, and helping everyone move with the same understanding. The opportunity is not just faster work. It is better coordination, stronger alignment, and smarter collective execution. Because the future of AI at work is shared.

Yann Alexandre Petretti

Demo 3: MobileClaw: Lightweight Autonomous AI Agent for Android.

1. MobileClaw: Lightweight Autonomous AI Agent for Android. MobileClaw is my open-source project: a lightweight autonomous AI agent with a mobile-native UX, designed to run directly on Android devices. GitHub: https://github.com/Good-karma-lab/mobileclaw

Aleksandr Ostapenko

Keynote 10: Human-Centric AI: Navigating the Risks, Opportunities and Unintended Consequences

AI is transforming every industry, every profession and every aspect of society. But alongside unprecedented opportunity come profound risks and unintended consequences. This talk will explore both sides of the AI revolution... from innovation, productivity and economic growth to job displacement, existential risks, misinformation, cybersecurity threats and the future of human relevance.

Nicky Verd

Panel 3 – AI Act × AI Value Chain and Governance

Philippe Sigal, Laura Gilbert +2 more

Workshop 3 - Creative & Generative AI

To be announced...

Demo 4: I Built Autonomous GTM Engines - So Can You.

​Most companies bolt AI onto their old GTM playbook. It never gets them there. ​The modern GTM stack is one engine. Your data and your know-how feed one shared brain, the brain powers the apps your team uses every day, a human checks anything important before it goes out. Chaos in, playbooks out. ​In this live session, David Arnoux walks through how he builds this inside real companies, from B2B software scale-ups to consumer brands. What you'll take away ​What a GTM OS actually is, and why bolting AI onto the old playbook fails, ​The core components of the engine: signals, workflows, agents and reporting in one shared brain, ​How the engine progresses from reactive → proactive → autonomous ​Real builds from both worlds. A €2.5B B2B software company and consumer brands running programmatic SEO at 12,000+ pages ​What it takes to build a GTM OS inside your company in days, not months, and why roughly 80% of each new build carries over to the next.

David Arnoux

Workshop 4: Give Your Product a Voice — Build a Live AI Voice Agent in 60 Minutes

Everyone's talking about voice AI. In this room, you'll actually ship one. Roshan and Barbara will get you from a blank screen to a working, talking AI agent that can hold a real phone conversation, before the coffee break ends. You'll design its personality, wire up its brain (LLM), give it ears and a mouth (speech-to-text and text-to-speech), and connect it to a real tool so it does more than chat, it acts. Bring a laptop and an idea. Leave with a deployed agent, a live phone number, and the know-how to build the next one yourself. What you'll walk away with: • A working voice agent you built yourself, live • A mental model for the voice AI stack (STT → LLM → TTS → tools) and where the real engineering challenges hide (latency, interruption handling, tool-calling reliability) • The gap between a slick demo and something that survives a real caller — the practical lessons Vapi's forward-deployed engineers see across production deployments Best for: builders, PMs, and founders who want to stop reading about voice AI and start shipping it. No ML background required — bring curiosity and a laptop.

Roshan Manjaly, Barbara Stanelli

Keynote 12: Open Models & Fine-tuning

To be announced...

Jaime De Mora

Debate 1 — Agents: The Real Platform Shift, or 2026's Most Overhyped Demo?

Every deck in 2026 says 'agentic.' Most agents still break the moment they touch a real workflow. Side A: agents are the genuine platform shift — the jump from copilots that suggest to systems that actually do the work, and the teams already shipping them in production are pulling ahead. Side B: 'agentic' is this cycle's most oversold demo — brittle, expensive, badly governed, a thin wrapper over the same models we already had. 55 minutes, two builders, one moderator who has actually run agents in prod, and an audience vote before and after.

Maanas Mediratta, Dave Garcia

Demo 5: Scaling the AI Explosion: Why Platform Engineering is the Secret to AI Governance

Moving AI from "lab to life" is no longer a coding challenge—it’s an operational one. As enterprises deploy swarms of AI agents, they face a fragmented ecosystem of shadow AI, hidden costs, and security vulnerabilities. The solution lies at the intersection of two forces: AI and Platform Engineering. In this talk, we dive into the technical architecture of the Modern Internal Developer Platform. We will examine how to bake governance—from EU AI Act compliance to drift detection—directly into the developer workflow. Discover how to use AI to govern AI, creating a centralized "Command Center" that provides visibility into costs, security, and PII without slowing down your engineering teams. Open source demo.

Pol Fenollar

Keynote 13: Train Once, Recommend Forever: Recsys for an Ever-Growing Catalog

Modern consumer products all share one trait - their catalog never stops growing. Think streaming platforms, marketplaces, news feeds: new shows, new listings, new articles arrive every day, and users expect to see them in their recommendations right away. But recommendation systems learn exclusively from past user interactions, so anything that just arrived, with no interaction history yet, is invisible to them by design. The traditional fix is to retrain continuously - but that's exactly the trap: it couples what a system can recommend to when it was last trained. New items go unrecommended, and hidden gems stay invisible. In this talk, we discuss the paradigm shift now sweeping through recommender-systems research: decoupling the training of a recommender from what it's allowed to recommend. We explore the techniques that let Albatross and tech giants like YouTube, TikTok, and Amazon serve high-quality recommendations from ever-growing, billion-item catalogs in milliseconds. Drawing on production-scale experiments, we take a tour through the architectures making this possible: from the transformer that's the workhorse of modern discovery systems, through the generative-retrieval wave currently exciting the field, to the frontier approach we've built at Albatross - backed by comparisons and hands-on examples.

Matteo Ruffini

Panel 4 - When AI Checks In: Travel & Hospitality's Real Use Cases

Travel is quietly one of AI's biggest proving grounds — agentic trip planning, dynamic pricing, AI concierge, and the booking that happens without a human ever opening a tab. In one of Europe's most-visited cities, the people running it share what's actually live versus what's still a demo, and where AI breaks when a real traveler is involved.

Joan Salvatella

Keynote 14: Open Models & Fine-tuning

To be Announced...

Jordina Torrents Barrena

Demo 6: Robotics

Keynote 15: Startup Scaling & Fundraising

To be Announced...

Howard Wright

Demo 7: Open Models & Fine-tuning

To be announced...

Etienne Dilocker

Keynote 16 - Learning Is the New Infrastructure. Most Companies Haven't Built It Yet.

Most AI workforce transformations fail not because of the technology, but because organisations don't know how to learn at speed. Prof. Dr. Thomas Funke draws on 20 years of research and practice, from WU Vienna to building TechQuartier in Frankfurt to co-founding Tomorrow University of Applied Sciences, to argue that learning is the defining infrastructure challenge of the AI era. This session gives CHROs, L&D leaders, and CEOs a concrete framework: what a learning organisation actually looks like, why traditional training approaches are structurally broken, and what it takes to build the organisational capability to absorb AI-driven change continuously. Using Tomorrow University as a live case study, Thomas shows what AI-native learning infrastructure looks like in practice and what leaders can do immediately to start building it.

Christian Rebernik

Panel 5 - Strategic Money: How Corporates Really Invest in AI Startups

Corporate venture money isn't chasing the same thing as a fund. A strategic investor wants synergy, access, and an eventual seat at the table, not just a return. This panel puts corporate innovation and venture arms on stage to unpack how they actually pick, structure and manage AI investments and partnerships: what they're really underwriting beyond the cap table, where that clashes with how independent VCs think, and what founders get wrong pitching a corporate as if it were a fund. Built for founders courting strategic capital and for anyone trying to understand how big companies actually move on AI.

Keynote 18 - The AI Operating Model Advantage: Why Winning with AI Requires Rewiring the Organization

AI is everywhere, but enterprise-wide impact remains elusive. The reason is increasingly clear: most companies are putting powerful new technology into organizations designed for a pre-AI world. They automate tasks, add copilots and deploy agents, while leaving the underlying workflows, decision rights and management structures largely untouched. The next wave of AI value will come from changing that. For industrial companies in particular, AI creates an opportunity to rethink not only individual tasks, but how expertise, decisions and work flow across the enterprise. This session will explore why AI winners are moving beyond productivity to redesign their operating models around AI: concentrating on the few domains where AI can create strategic advantage, rewiring end-to-end workflows rather than bolting AI onto existing processes, and building organizations in which humans and AI agents work together at a fundamentally different speed and scale.

Steffen Fuchs

Demo 8: Responsible AI

To be announced...

Somdip Dey

Keynote 20 - The Port of Barcelona: A Toolbox to Develop Your AI Projects

The Port of Barcelona, as one of the most innovative ports in Europe, has put in place a series of tools that will help you to develop your innovative projects. Such tools include:  Open data research  5G standalone net  Sandbox  Agreements with BSC and AI factory  …. Learn how your company and your project can benefit from such an infrastructure which is there to help you scale your business faster and further. Learn about the latest AI projects that The Port of Barcelona is undertaking.

David Serral

Demo 9: MLOps

To be announced...

Alex Shershebnev

Panel 6 - Physical AI: Humanoids, Robot Fleets & Europe's Hardware Gap

Physical AI is 2026's breakout story: humanoids leaving the lab, LLM-driven robot fleets, and a hardware race Europe is losing to China. Can the EU build, not just regulate?

Limor Schweitzer, Carl Strathearn +1 more

Workshop 5: ESG Standards Mapping with Claude

Stop Manual ESG Reporting Work: Build Your Al Assistant with Claude: - Learn how to build an ESG Standards Mapping Agent to save hours of manual work. - Instantly analyze ESG reports for framework interoperability mapping (ESRS, IFRS, SBTi). - Navigate interactive analysis artifacts, and learn to generate shareable dashboards to present critical insights and data-driven gaps to your stakeholders.

Javo Granda, Antonio Morales

Workshop 6: The Human Side of AI Transformation

Everyone is talking about what AI can do. Nobody is asking what humans need to become. This workshop introduces Human Literacy — the missing half of every AI strategy. Drawing from original research, senior tech leader interviews, and 15 years decoding human behaviour in the attention economy. Because the organizations that win the AI era won't have the best models. They'll have the most human-literate people running them. The future of AI is human.

Roberta Scrofani

Keynote 22: Fighting Back Against Intelligent Fraud with AI Agents

AI is foundational to how businesses operate and a critical connection between people and companies, making AI-assisted fraud prevention a core business priority. As organizations deploy intelligent agents to drive speed and efficiency, attackers are deploying their own AI to mimic real people and exploit trust at scale. The result: a new, largely unprotected frontline where identity is fluid and traditional safeguards fall short. In this keynote, Phenom CEO and co-founder Mahe Bayireddi outlines how leading companies are responding by embedding fraud detection across critical workflows, coordinating networks of AI agents to identify risk signals in real time, and reinforcing automation with human oversight. The goal is not to slow innovation, but to ensure that speed, security and trust are built together from the start.

Mahe Bayireddi

Use Case 1: Product Discovery is finally solved: Introducing Perception Models

Large marketplaces and ecommerce have a discovery problem that traditional recommendation systems were not built to solve: every item is unique, catalogs change rapidly, and metadata is inconsistent. Hundreds of thousands of new listings enter the catalog every day with no impressions or interaction history - effectively invisible to legacy systems. The result is a discovery experience that remains static as users browse, click, and refine their interests, while newly listed items can take days to surface. Albatross has solved this problem with perception models. This new class of AI learns from live user behavior, understands user intent in real time, and reshapes discovery as each session unfolds - while every new unique item becomes immediately discoverable. In this talk, we will also explore live deployments and in particular our partnership with Wallapop, one of the first C2C marketplaces globally to move toward in-session, adaptive discovery that understands user intent as it unfolds, and advancing user engagement and seller visibility at unprecedented scale.

Rodrigo Aramayo, Kevin Kahn

Keynote 23: AI made it easy. Who decides what's good?

As AI rapidly generates designs, code, content, and recommendations, many organizations are focused on speed and efficiency. But when outputs are cheap and abundant, speed alone is no longer a competitive advantage. The real challenge becomes defining what good work actually looks like. This talk reframes “good” in the AI era as outcomes, not outputs. Drawing on Sense & Respond thinking, it treats AI-generated artifacts as a new class of assumptions—powerful, persuasive, and requiring validation. AI doesn’t eliminate uncertainty; it accelerates our ability to create hypotheses. The work of teams is still to decide which assumptions matter and how to test them. Attendees will learn why managing to outcomes becomes more critical as AI increases throughput, and how AI tools can be used to generate, test, and invalidate ideas faster—strengthening learning loops rather than replacing judgment. “Good” in the AI era is not about adopting tools. It’s about building organizations that learn faster than their assumptions.

Jeff Gothelf

Use Case 2 - Neo4j x Astrazeneca

Antonio Fabregat, Jesús Barrasa

Demo 10: Demo of AI co-Workers to augment pharma commercial teams

AVATIA builds AI co-workers for pharma commercial teams. Pharma spends around 100 billion dollars a year engaging doctors and pharmacists, but human-only models no longer scale. We are building an AI-native agentic layer that helps reps work 10 times faster, increases HCP engagement 5 times, and gives doctors and pharmacists trusted 24/7 access to pharma companies.

David Masó

Keynote 24: A Brief History of Artificial Intelligence

Discover the fascinating evolution of artificial intelligence, from its theoretical foundations in the 1940s to the generative AI revolution of 2026. This session explores the key breakthroughs, milestones, and paradigm shifts that transformed AI from an academic dream into one of the most impactful technologies of our time.

Guillaume Saint-Cirgue

Panel 7 - Healing or Hooking? AI's Double Edge on Mental Health & Wellbeing

Same AI, two opposite stories. On one side: AI therapy companions making mental health support 24/7 and accessible, mood-tracking that catches a crisis early, mindfulness coaches in your pocket, generative tools that help people process trauma. On the other: recommendation systems wired to maximise screen time, dopamine engineering disguised as engagement, attention economies that reward outrage, and AI companions that quietly replace human connection. Where does the line sit between AI helping us thrive and AI hooking us into something that costs more than it gives? Builders, clinicians and behavioural scientists argue out what 'wellbeing' should actually mean in an algorithmic world — and who pays the bill when it goes wrong.

Katya de Freedericksz, Marvyn Halfon +1 more

Use Case 3 - AI Voice Agents: From Pilot to Production

Voice AI has left the lab. Enterprises are putting AI voice agents in front of real customers, and the gap between a promising pilot and a production deployment is where many projects stall. Drawing on deployments across multiple industries, we'll examine what it takes to run voice agents at enterprise scale: the barriers that most often derail adoption, the technical foundations production demands (real-time latency, accuracy on real-world audio, predictable cost), and the operational groundwork that separates a compelling demo from a system customers rely on. Attendees will leave with a clear view of how leading companies moved from proof of concept to production, the mistakes that cost them time, and a practical framework for deploying voice AI that holds up in live customer conversations.

Miguel Arroja

Keynote 25: Gravity Always Wins: Why Profitable Efficient Growth is the Path to Victory, Especially In The Era of AI

A practical session on how founders and GTM leaders can define what “winning” actually looks like in an AI-native world. Sam will break down the milestones, KPIs, and decision points that matter most as companies scale beyond early traction, helping leaders understand where to focus, what signals to trust, and how to make smarter growth decisions in rapidly changing markets.

Sam Jacobs

Keynote 26: AI & Education

To be announced...

Daniel Traça

Use Case 4: The Human Side of AI

To be announced...

Panel 8 - Retail Rewired: AI from Storefront to Checkout

From demand forecasting and dynamic pricing to AI stylists, smart inventory, and a checkout that knows you before you reach it — retail is being rebuilt aisle by aisle. And now agents are starting to shop on the customer's behalf, forcing brands to rethink who they're really selling to. Retail and e-commerce operators on what AI is already changing on the shop floor and online, and what breaks when real customers and real margins are on the line.

Bhavishya Ramchander, Maxim Khalilov

Demo 12: When anyone can build, the person who decides WHAT to build becomes the bottleneck

Engineering output has exploded. At leading AI companies, a five-person team now ships what fifteen used to. At Bricks, an AI proptech startup I shipped 10+ production AI agents in 3 months. Alone with Claude Code as my unfair advantage. But the part of product work that actually decides whether you build the right thing — getting six people in a room to agree hasn't gotten any faster because it can't. Alignment lives in Slack threads and kickoff meetings and then evaporates. There's nowhere for an LLM to automate it. The result: a compressed PM-to-engineering ratio where the bottleneck has quietly moved from "can we build it" to "do we know what to build, and does everyone agree." This talk is about what breaks when that compression hits, what I got wrong shipping solo at Bricks, and 4 shifts/changes builders need to make now whether you're a PM, an engineer, or a founder watching your team try to figure out who owns what.

Nicolas Léonard

Workshop 7: Token Compression and Routing, how to control agentic coding costs

First, you make it work. Then you make it efficient. We've spent the last two years proving that LLMs can write code, run agents, and orchestrate complex workflows. Today, Claude Code, Codex, OpenClaw, and others are the modern platforms for executing computational tasks, and tokens represent their new bandwidth. Token compression is about using that bandwidth wisely and accounting for costs from an engineering perspective. This is a hands-on session on the key techniques and a framework for reasoning about this as a fundamental property of the systems you ship, not an afterthought. Attendees will leave with concrete actions they can implement this week, and a mental model for thinking about token efficiency as a compounding infrastructure advantage rather than a line-item cost.

Sacha Morard

Keynote 27 - The era of useful, secure AI business software

2026 was the era of shiny demos and prototypes. 2027 will be the era of useful, secure business software that powers your business operations. This talk unveils how the next generation of business apps will be built by non-technical teams - not because we simplified code, but because we simplified creation.

Mariam Hakobyan

Demo 13: Cursed Apps: Building (and Breaking) the ChatGPT × Claude Ecosystem

ChatGPT Apps and Claude Connectors are quietly becoming a new app layer built on top of AI assistants — but almost nobody has stress-tested what these platforms can actually do, or where they break. This talk opens with a live build: crafting a working app from scratch on Skybridge, an open-source framework for shipping apps that run inside both ecosystems. From there it gets weird. Drawing on a set of deliberately useless experiments built to probe the limits of the MCP App ecosystem, the talk walks through what happens when ChatGPT users and Claude users fight for territory on a shared pixel canvas; rival AI models get dropped into one group call together; a cadavre exquis has players each draw one section of a picture without ever seeing the whole; a game of telephone pictionary degrades — beautifully — across LLM sessions; and independent AI agents try to coordinate through pheromone trails, ant-colony style. None of these are products. They're stress tests — and what breaks, and what doesn't, says more about where this ecosystem actually stands than any roadmap slide could.

Frédéric Barthelet

Debate 2 — Future of Work: Will AI Replace Half of Knowledge Workers by 2030?

Tobi Lütke told Shopify managers: don't hire unless you can prove AI can't do the job. Goldman called it a $7-trillion labor shift. Wall Street is pricing in the productivity surge. So is this the great unbundling of the knowledge economy — or the latest in a 30-year history of tech-replaces-work predictions that never came true? Two debaters fight it out: one sees a near-future where the white-collar middle is hollowed out, the other sees AI as the most powerful augmentation tool we've ever built, with employment levels intact. 55 minutes, bell-to-bell.

Magda Kufrej, Anna Thomas +1 more

Panel 9 - Women Who Lead the Room: Closing AI's Leadership Gap

AI is rewriting who gets heard, funded and promoted. Founders and leaders on building inclusive AI leadership pipelines — and why visibility is the new currency.

Sarah Anto, Faith Ruto MBA +2 more

Use Case 6: When Every AI Company Sounds the Same: How to Build and Prove Real Differentiation

In an AI market where nearly every company makes similar claims, genuine differentiation is increasingly difficult to articulate and even harder to prove. Using Maisa’s experience as the central case study, David Villalón and Manu Romero will discuss how founders can build a defensible position through fundamental technology choices, measurable customer outcomes and the ability to meet the highest standards of trust, security and accountability. The session will explore what distinguishes a compelling narrative from a truly differentiated company, particularly when selling into some of the world’s most regulated industries.

David Villalón, Manuel Romero

Demo 14: The Hiring Debt Nobody Talks About

How people infrastructure debt accumulates silently in the early stage, and what it actually costs founders when it catches up with them.

Ebony James

From Dating Fatigue to AI Saturation: Why People Are Coming Back to Real Life

Dating apps removed rejection, not loneliness. AI removed friction, not the need to be known. Maxime Barbier built Timeleft on the opposite bet: put strangers around a dinner table in 200 cities worldwide, and make the awkward part the point. In this fireside he argues that friction is a feature, that restaurants have become the last piece of social infrastructure we have left, and that the harder an experience is to outsource to a model, the more it is worth doing yourself. Booking gives you a room. Skyscanner gives you a flight. Timeleft gives you a human. A deliberately contrarian counterweight to the rest of the AI for Good track, on loneliness, third places, and what we quietly lose to LLMs.

Max Barbier

Panel 10 - Place Your Bets: AI in Gaming, Gambling & Live Entertainment

Gambling, gaming, streaming, live events — AI is rewriting the entire entertainment stack. From iGaming algorithms predicting your next bet, to recommendation engines deciding what 200M people watch tonight, to computer vision and robotics changing how live shows feel — this is one of AI's biggest, fastest-moving playgrounds. We bring operators, builders and regulators together to debate where the line sits between hyper-personalization and manipulation, what AI means for fair play and responsible design, and how Europe can build the next generation of entertainment with AI at the core.

Xavier Simó, Alejandro Mowszet +2 more

Fireside 2 - Finance & Banking

To be announced...

Sophie Cornay

Demo 16: AI in High-Stakes Environments: A Practitioner's Framework for Responsible, Explainable, and Secure Deployment

Most AI governance conversations happen at the policy level. I want to bring them to the production level, where the decisions are harder and the consequences are real. I'll walk through how we built and deployed an AI governance framework inside a regulated healthcare technology platform: what alignment with the EU AI Act, Cyber Resilience Act, and ISO 42001 actually looks like in code, architecture, and process, not on paper. What broke. What we had to rebuild. And why "responsible AI" means something very different when a wrong output affects a patient in behavioral health.

Dr. Martin Ignatovski

Fireside 3: AI Business Models & Monetization

To be announced...

Tim Beck

Keynote 28 - Open Models & Fine-tuning

To be announced...

Oleg Kovpak

Fireside chat with Artavazd Mehrabyan

Artavazd Mehrabyan

Keynote 29 - GTM Strategies

To be announced...

Demo 17: Healthcare

To be Announced...

Astel Allame

Workshop 11: Agentic AI

To be Announced...

Jakub Sadowski

Panel 11 - Creativity at Machine Speed: GenAI in Film, Media & Design

Video models broke through — now what? Leaders from film, broadcast and design on hybrid AI workflows, creator compensation, and where human craft still wins.

Martin LeBlanc, Greg Kozakiewicz +2 more

Keynote 32: EU AI Act

To be Announced...

Luana Lo Piccolo

Keynote 31: From the AI Era to a Change of Era: The Sunrise of AI Agents

This talk we'll explore the implications of a new reality where humans will work with new colleages called AI Agents. The rule games have changed forever so individuals and enterprises will need to re-adapt to be competitive. AI Agents don't replace work, they intensify it so I'll give a positive view about the new opportunities and how to leverage those ones.

Eduardo Ordax

Workshop 12: AI for Clarity: Turning Technical Complexity into Stories People Act On

It’s a practical session showing how AI tools (ChatGPT, Gemini, Copilot, etc.) can help professionals remove complexity and create accurate decision narratives. It includes a live demo so people can see the transformation happening in real time. Given the mix of technical and business audiences at the summit last year, I think this will work well with: • data and analytics teams that want bigger impact with their insights • AI technical teams that need to remove jargon when communicating with business colleagues • business leaders trying to get better engagement from their presentations

Iñigo Antolín, Andy Storch

Keynote 34: Responsible AI

To be Announced...

Laurence Nguyen

Keynote 33: MLOps

To be Announced...

Demo 18: Neurotech

To be announced...

Thorsten O. Zander

Keynote 36: Creative and Generative AI

To be Announced...

Ferdi Alici

Panel 12 - From Scan to Startup: AI Healthcare in the Real World

AI already reads scans, catches cancers earlier and reshapes drug discovery — but it learned from biased data. Clinicians, founders and investors on what works today and what we must fix.

Ariadna Maso

Keynote 38: Future of Work

To be Announced...

Constance Nevoret

Keynote 37: How to Build a Product That Sells Itself in the AI Era

AI is raising the bar for product experiences. Users are no longer willing to tolerate friction unless there’s no better alternative. In this session, Wes Bush introduces a practical framework for building products that feel intuitive, deliver value instantly, and drive their own adoption. You’ll see how leading companies are shifting toward AI-native experiences, along with real examples of what actually changed in their product, onboarding, and growth model. Rather than focusing on step-by-step tactics, this session will help you understand the underlying forces that make products “sell themselves” and how to apply those principles to your own business. Attendees will walk away with a clear mental model for diagnosing friction, improving activation, and creating a more self-serve, product-led growth engine in the AI era.

Wes Bush

Demo 19: From Reactive to Proactive: Building AI Agents that Anticipate Customer Needs

We’re collecting more data than ever, building powerful chatbots, designing complex workflows but users still just want ONE thing: to get what they need with as little effort as possible. In this talk, we’ll explore how AI agents can help bridge that gap: not by asking users to give more, but by leveraging what we already know to deliver faster, smarter, and more intuitive experiences. In the live demo of an agentic assistant we will see a shift from reactive to proactive behavior. We will discuss common pitfalls when building agentic systems and tap into their evaluation for large scale solutions.

Nensi Hakobjanyan

Keynote 39: MLOps

To be announced...

Andreas Horn

Keynote 40: Cybersecurity

To be Announced...

Eduard Singer

Panel 13 - Energy Resilience & AI Climate Adaptation

Alejandro Martí, Rocío Alcocer +2 more

Workshop 14: Can AI Replace Your Buyer Interviews? Building Robust Synthetic Personas

B2B market research has always been the industry's hardest nut to crack: small sample sizes, gatekept buyers, slow timelines, and insights that go stale before you can act on them. In this talk, Kate Busby breaks down how AI-generated synthetic personas are changing the equation, not as a shortcut, but as a rigorous, repeatable process. Kate walks through the full methodology: how to construct synthetic personas that actually reflect real buyer behavior, the data fidelity checks that separate a useful model from a hallucinated one, and the validation loops needed to trust the output enough to act on it. She'll share hard-won lessons from running this process against real B2B audiences, where it holds up, where it breaks, and how to know the difference. Attendees will leave with a practical framework for building synthetic personas that go beyond guesswork, giving growth and marketing teams faster, cheaper, and more reliable access to the qualitative insight B2B research has always struggled to deliver at scale.

Kate Busby

Demo 20: Inside the architecture: Building a production-ready AI venture

What does it actually take to move from AI prototype to production-grade product? In this technical deep dive, Michael van Lier unpacks the architecture behind one of Builders’ AI ventures — from model selection and orchestration layers to data pipelines, infra decisions, and governance. Rather than theory, this session explores real design trade-offs, scalability challenges, and the hard calls that shaped the product. Ideal for technical founders, product leaders, and engineers who want to understand what breaks, what scales, and what matters when building AI systems in the real world.

Michael van Lier

Keynote 42: SaaSApocalypse in the era of AI Agent

AI agents are rewriting the rules for the entire SaaS industry. Tools we paid monthly subscriptions for can now be recreated by an agent in minutes — and increasingly, users don't want to click through an interface at all; they just want to issue a command. Is this the end of SaaS as we know it? In this talk I'll show why the classic "feature-for-subscription" model is running out of road, and what that means for anyone building software today. I'll speak as a practitioner — drawing on lessons from running my own SaaS products — about shifting our thinking from "ship more features" to "build value an agent can't replicate." A central theme will be sovereignty: in a world where your product talks to AI agents and your data flows through models you don't own, who actually controls the customer relationship, the data, and the value? I'll argue that digital and data sovereignty become the real moat — the thing that separates companies that get commoditized by agents from those that own their future. You'll leave with a concrete map: which business models are most exposed, where new opportunities are opening up, and how to prepare your product today for a world where the first user of your app is an AI agent, not a human.

Mike Korba

Demo 21: From Dashboards to Decisions: Building AI-Powered Analytics on Top of Modern Data Platforms

AI is transforming how businesses interact with data, but successful AI initiatives start long before an LLM is introduced. Without reliable data foundations, even the most advanced models become expensive sources of incorrect answers. This session explores how modern analytics platforms can evolve from traditional dashboards into AI-powered decision-support systems. Using a real-world architecture journey, we compare fragmented reporting environments with a centralized data platform built around a data warehouse, semantic layer, and self-service analytics. We will discuss why data architecture determines the practical limits of AI adoption, how to design data flows that create trust in analytical results, and how agent-based interfaces can make data more accessible to business users. Rather than replacing analysts, AI agents act as a natural interface between people and data—automating routine investigations, accelerating insight discovery, and helping organizations answer questions such as “Why did sales decline last month?” in seconds instead of hours. The session concludes with a live demonstration of an LLM-powered analytics agent working on top of a governed data platform.

VIKTORIIA KNIAZEVA

Debate 3 — Sovereign AI or Surrender? Should Europe Stop Outsourcing Its AI Future?

Europe is building 13 AI Factories, funding Mistral and Aleph Alpha, demanding open weights, and writing the world's strictest AI law. Yet 90% of European AI compute still runs on AWS, Azure and GCP, and the foundation model leaderboards are American and Chinese. So is sovereign AI the project of the decade for European strategic autonomy — or an expensive industrial-policy fantasy that taxes EU founders without producing winners? One debater says Europe must stop renting its future. The other says we already lost — partner up and accept it.

Oscar Lepoeter, Justin Strharsky

Panel 14 - Money, Reinvented: AI Agents, Stablecoins & the Future of Finance

Agents that pay, tokenized rails, banks racing fintechs to deploy AI under the world's strictest rules. The people building the future of money on what's real and what's next.

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Aurora Kapo, Anya Nova +3 more

Keynote 44: Forward Deployment at OpenAI

Ilyass El Mansouri

Demo 22: Leverage AI to Build MVPs fast

Compress your time-to-market by building and shipping functional MVPs in days using AI coding assistants, code generation, and rapid prototyping pipelines. Focus on validating demand early and iterating fast while adopting AI-native execution to automate development workflows and significantly increase output. At the same time, design with scalability in mind from day one so your product can grow without rework. This is an end-to-end approach to build, test, and scale products at startup speed.

Enrique Calvo

Keynote 45 - Responsible AI

To be announced...

Laura Tissot

Panel 15 - Who's Really Deciding? Human Agency in the Age of AI

An algorithm nudges what your kid reads before bed. A hiring filter decides who a recruiter never sees. A health app flags what's wrong before your doctor does. None of this is speculative — it's this year's default UX. As AI mediates more of daily life — work, health, relationships, money, parenting — how much control do people actually keep, and how much do they just assume they still have? Voices from product, psychology, and policy separate where human agency genuinely holds from where it's already quietly gone. 40 minutes.

AP

Laura Sibony, Don Kilburg +1 more

Keynote 49: Tokens, Latency, Sovereignty: The Physics Pulling AI to the Edge

John Roche

Keynote 50: AI in Retail - Danone

Nicolas Cosqueric

Panel 16 - The New Gatekeepers: Brand Visibility in the Age of AI Search

Zero-click search is here: customers ask AI, not Google. How GEO is replacing SEO, what happens to your website when agents do the browsing, and who wins when LLMs decide what gets seen.

Daniel Espejo, Antoine Heftler +2 more

Workshop 16: Enterprise AI

To Be Announced...

David Lahoz Martín

Workshop 15: Open Models and Fine-tuning

To Be Announced...

Pedro Cuenca

Demo 25: Shifting Gears: A Practical Guide to Adopting Spec-Driven Development

As AI coding agents become mainstream, engineering teams are discovering a new problem: freestyle AI generates code without traceability. When the AI writes the code directly from a prompt, how do you answer, "Why was this built this way?" In this session, we will explore Nuvolar's pragmatic journey to Spec-Driven Development (SDD) using the OpenSpec framework. By placing a structured layer of documentation between human requirements and AI output, we transformed our engineering workflow. We will walk through our customized open-spec lifecycle. Most importantly, we will highlight how to keep humans in the driver's seat. You will learn how we implemented mandatory gates to ensure engineers own the architecture and mitigate risks, while the AI agent handles the boilerplate. Finally, we will share our hard-won lessons on what didn’t work, what did and where do we go to now!

Pere Martí, Gerard Auguets Pulido

Keynote 53: Responsible AI

To be announced...

Alia Zafar

Demo 26: The AI-First Founder: Growing Without a Team

Most founders think growth means hiring. This session challenges that assumption. Drawing from the experience of launching multiple AI-first companies over the past year, discover how AI can replace your sales and marketing engine and whether you'll ever need to build one at all.

Vincent Jong

Keynote 54: AI & Education

To be announced...

Dr. Rajesh Kumar K V

Panel 17 - AI vs AI: Deepfakes, Fraud & the New Cyber Battlefield

Voice clones empty bank accounts, deepfakes pass KYC checks, and attackers now automate with agents. The people defending banks, newsrooms and infrastructure on fighting AI with AI.

Caroline De Cock, Quentin Cozette +2 more

Use Case 11 - Amplitude x Autentic AI

Bruno Barbagli, Dani Diestre Tomas

Keynote 55: Why most AI GTM fails (and what's converting instead)

Many AI products impress in demos but stall in adoption. This talk explores the gap between technical possibility and commercial traction: the buyer signals that matter, the pricing and positioning shifts that unlock budget, and the product traps that quietly kill deals. A grounded, operator-level view on AI go-to-market in 2026.

Sharon Klaver

Demo 27: Future of healthcare AI

Matěj Misař is one of the leading voices driving the real-world implementation of artificial intelligence in healthcare across Central and Eastern Europe. While many still view CEE as a “catch-up region,” the reality may surprise you. Some countries in the region have already achieved up to 89% AI penetration across radiology departments. Others are launching national AI tenders across hospital networks, building reimbursement frameworks, and turning AI from innovation into standard clinical practice. Behind this momentum stand local heroes: healthtech companies from CEE now deploying AI solutions in hospitals across Europe, Asia, and the Middle East. Who is driving this transformation, and what can the rest of Europe learn from it? Matěj Misař, healthcare AI advisor to multiple ministries, chairman of the healthcare group of the Czech Association of Artificial Intelligence, and CEO of Carebot, the most widely deployed clinical AI platform in CEE, will reveal why the future of healthcare AI may be built faster in Prague, Warsaw, Budapest, or Sofia than many expect.

Matej Misar

Keynote 56: Future of Work

To be announced...

Myriam Ben Farhat

Panel 18 - The BlueTechPort and the Blue Economy Industry

Barcelona's port is becoming a working testbed for the blue economy. This panel brings together projects building inside the BlueTechPort to examine what proximity to the harbour community actually changes. Has being embedded in the port unlocked capabilities these teams could not have built alone? Has it accelerated their roadmaps? And where is AI now doing real work inside their innovation projects, rather than sitting in a pitch deck? The session closes as an open invitation to join the community.

Workshop 18: Coming of Age 2040

Orsi Nagy

Workshop 17 - Bizaway

Tyler Foster

Use Case 12: Pigment x Uberall

To be Announced...

Anselme Vignon, Jose Ramon Iglesias

Demo 28: How to reach 10M€ ARR in 5 years self funded with a family business ?

Leexi was founded in late 2021 by Xavier Lombard, his wife and two sons, born from a simple frustration: the value created in professional meetings disappears without a trace. In five years, the company reached 10M€ ARR entirely self-funded, refusing multiple VC offers — including a 15M€ valuation from Volta Ventures — to preserve independence, culture and long-term decision-making. The formula: obsessive product depth (350+ features), European data sovereignty as a structural moat, zero churn culture (one resignation in four years), and a discipline that turned every euro of revenue into the next hire. The lesson is not about family — it's about alignment: when founders share the same values, the same roof and the same long-term vision, they move faster, decide better, and build something that lasts.

Xavier Lombard

Keynote 57: Finance & Banking

To be announced...

Shalini Goyal

Debate 4 — The 2027 Crash: Is AI the New Dot-Com Bubble?

$500 billion in AI capex this year alone. NVIDIA at a $4-trillion market cap. Startups raising $1 billion before product. And a chorus of investors, economists and former bulls now whispering the b-word. Is AI the most important infrastructure build of the century — worth every dollar — or the largest mispricing of risk since 1999, with the 2027 hangover already booked? The closing debate of AI Summit Barcelona puts a believer and a sceptic in the ring while the audience decides whether to ride the wave or run for cash.

Oleg Chervonnyi, Patricia Pastor +2 more

Demo 29: How AI Is Rebuilding Modern Sales Teams

AI is not just a tool. It is changing how B2B sales teams are built and scaled. In this session, I will show how companies use AI, automation, and AI agents to identify buying signals, define precise ICPs, automate outreach, and structure their CRM into a predictable sales engine. You will learn how to let AI handle research, data, qualification, and workflows, while your team focuses on conversations, trust, and closing. This is practical, system-driven, and based on real implementations. If you want to grow your revenue and win more B2B clients without hiring a large sales team, this session is for you.

Sami Ghozzi

Panel 19 - From BSC to Brussels: Europe's Supercomputing Bet on AI

Frontier AI runs on supercomputers — and right now, Europe is on a building spree. The AI Factories initiative is wiring 13 supercomputers across the continent. Barcelona's MareNostrum 5 already sits in the global top tier. National centres are competing for GPUs, talent and political backing, on the bet that sovereign compute means sovereign AI. But does it? We bring together the people running Europe's biggest AI compute infrastructure, the policymakers funding the push, and the startups and researchers actually trying to use this hardware — to ask whether Europe is building real industrial capacity or expensive symbolism, who gets access, how it stacks up against the hyperscalers, and what the next five years of European AI infrastructure actually look like.

RA

Gerald Mullally, Milos Mastník +2 more

Demo 30: Deeptech

Wolf Boone

Use Case 14: Conforama

Xavier Papiol

Panel 20 - Fair, Explainable, Accountable: Building Responsible AI in Production

Every company claims their AI is responsible — few can show the audit trail. Bias testing that catches real bias, explainability that survives a regulator's questions, and the governance structures that hold up when a customer, a journalist, or a lawsuit comes asking. Builders and compliance leads on what responsible AI looks like once it's not just a slide in the deck. 40 minutes.

Nathan Bonnet, Don Kilburg +2 more

Demo 31 - Mediktor

Oscar García-Esquirol

Use Case 15: AI‑Driven SDLC

In this session I’ll share how we are redesigning the software development lifecycle at dLocal around AI to build mission‑critical payment systems. I’ll walk through where AI adds real value across the SDLC and what has not worked in a heavily regulated, high‑availability environment. I’ll cover our tooling choices, guardrails, and change‑management approach, along with concrete examples and early impact on lead time, quality, and developer productivity. Attendees will leave with pragmatic patterns to safely introduce AI into their own SDLC.

Alberto Almeida

Fireside chat with Ricard Garriga

Ricard Garriga

Use Case 16: Beyond the bot ... what makes a voice agent worth talking to

Most voice agents are built to be useful. Very few are built to be good to talk to. There's a difference and it matters more than we think. In this talk, we map the spectrum of what AI voice conversations can actually be. I draw on three real experiments from my own world: a Second Brain agent designed to surface knowledge in a 10-minute walk, a Carl Jung-inspired philosophical companion built on ElevenLabs, exploring what depth and genuine curiosity feel like in a machine; and a real-world onboarding case that tested what happens when voice agents meet high-stakes human moments. Together, these cases build a framework for thinking about conversation quality not just accuracy or speed, but presence, specificity, and the feeling that something actually understood you.

Anna Bohonek, Alan Záruba

Demo 32: AI Visibility: How Buyers Find You Without Searching

Tanya Van Gastel

Fireside 10 - Barcelona: A Place Where Innovation Flourishes

Barcelona is not just a city — it is a European innovation hub with a strategy. The BlueTechPort brings together the city's Blue Economy ambitions, startup energy, and institutional backing into one living ecosystem. Two of its architects explain how Barcelona's innovation identity is being built, why the harbour is at its centre, and what it means for companies looking to grow here.

Ana Majo, Emma Cobos