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At Spotify, 64% of experiments generate a meaningful learning. Only 12% produce a winner. Sebastian Ankargren, Senior Data Scientist at Spotify, opens Unite Summit London with a Spotify-built perspective on what experimentation is really for — not just optimising what works, but protecting product decisions from what doesn't. A grounded, data-led case for why experimentation matters more, not less, in the AI era, and why bandwidth and simplicity — not headcount — will define which teams thrive in it.

The most interesting shift in experimentation isn't AI itself. It's what happens when agents stop being individual tools and start working as a connected system — finding ideas, building variations, configuring launches, reading results, shipping winners. Most teams are still learning to use them one by one. Behind that learning curve, a different question is taking shape. Fred De Todaro (Kameleoon), James Flory and Drake Som (Gain) share what it really takes to build AI experimentation enterprise teams trust.

At Fossil Group, many good ideas used to wait in the backlog longer than the team liked because of the development time those tests required. Then PBX changed who could build a test. Marcela Gutierrez shares how Fossil rewired its experimentation programme across global brands, what AI handled, what humans still own, and how faster ideation is now reshaping the next chapter—where deciding what to test matters as much as knowing how to build it.

A fireside chat with Motorway’s co‑founder on what really happens to your beautifully prioritised experiment roadmap in a live business and where human judgment still has to lead, even as tools and AI speed everything up.

Every experimentation programme has two versions: the one on the case study deck, and the one told once the recording stops.

Makram Mansour (ID.me), Brice Koenig (Lufthansa) and Dan Deshapriya (Intuit) join Katie Green on stage to share the second version. Three leaders who have scaled experimentation inside complex enterprise organisations. How they are embedding AI into real experimentation workflows. What is actually shifting inside their teams, and what is still pure noise. The cultural moves that landed. The ones that stalled for eighteen months before something clicked.

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95% of GenAI projects fail. Linda Cereda spent 15 years at Nike turning AI into measurable business growth — scaling SNKRS into the world's largest sneaker community, driving 2x revenue contribution through AI-powered lifecycle marketing. She closes Unite Summit London with a business-first view of what separates the winners from the rest: not the tools, but how AI is wired into processes and people. Expect frameworks, hard-won lessons, and a clear-eyed look at what comes next.