THE FUTURE OF AI - Day 2

Identify, capture, and leverage high-impact data from open data using AI

Every year, millions of public datasets are created or updated around the world—some containing information with significant strategic potential: lead generation, marketing analytics, data-driven R&D projects, and much more.
But due to the diversity of sources and the breakneck pace of their production, this valuable data too often goes unnoticed. Using new AI tools, we’ll show you how to identify them—whether when you need them or as soon as they’re published—so you never miss an opportunity related to their strategic value.

Romain Dupin (DataScoot)

 

 

 

Post-mortem AI: learning from failure to build success

Get a behind-the-scenes look at AI projects that didn’t go as planned. In this candid session, technical and strategic experts share the mistakes they wouldn’t make again… and the successful approaches they adopted afterward. A rare moment of authenticity, designed for anyone who wants to turn failures into drivers of success.

Olivier Mamavi (Management & Data Science), Guilhaume Leroy-Meline (IBM), Baptiste Detombe (Human Technology Foundation), Claire Vacher Arnal (WOMEN IN TECH), Robin Ferriere (Orange)

Creating with generative AI: opening up future technologies to women

This session highlights concrete initiatives to make AI accessible to everyone: demonstrations of AI agents created using no-code tools, and tips on how to learn about generative AI and machine learning so that everyone can join the ongoing technological revolution.

Léa El Samarji (Women in AI France)

 

 

AI for Tomorrow: decarbonizing, controlling energy and innovating without technosolutionism

Can artificial intelligence contribute to decarbonization without succumbing to empty promises? To start, take a look at some key figures from the 2025 Barometer of Eco-Responsible Digital Service Providers: how tech companies view AI, its benefits, and its limitations.

Emmanuelle Olivié-Paul (AdVaes), Loubna Sallak SALLAK (Cap Digital), Samy Jousset (Paris Region / Île-de-France Region), Pierre Monget (Hub France IA)

AI: regulatory strategy and widespread adoption - use case from the banking and finance sector

As AI develops on an industrial scale, the regulations governing it are also extending further up the value chain to encompass decision-making and the ways in which it is used.
A leading center for artificial intelligence will necessarily be one in which a collective awareness of the risks and legal issues accompanies this technological transformation.
The banking and financial sector, which is already facing increased regulatory pressure, must actively prepare for this by reinventing some of its operational processes, complying with new rules, and implementing best practices—all of which are necessary to integrate these new technologies with its regulated services.

Franck Guiader (Gide)