Lili.ai at the EIC Summit 2025: AI Beyond the Hype
It was a great honour for Lili.ai to take part in the Artificial Intelligence session at the European Innovation Council (EIC) Summit 2025.
The session, titled “AI Innovation: Beyond the Hype and Behind the Regulations”, brought together leaders from public institutions, industry, and investment to discuss the realities of deploying AI at scale: beyond promises and headlines.
Session speakers
Moderator: Hedi Karray, EIC Programme Manager for AI, European Innovation Council & SMEs Executive Agency (EISMEA)
Lucilla Sioli, Director of the AI Office, European Commission
Milie Taing, Founder & CEO, Lili.ai
Giovanni Burgio, Investment Manager, European Investment Bank (EIB)
Ioannis Arapakis, Head of Scientific Research (Discovery), Telefónica
Many thanks to the EIC team, and especially to Hedi Karray, for the invitation and the quality of the discussions.
About the EIC Summit 2025
The EIC Summit 2025 gathered:
1,400 participants
13 plenary sessions
24 workshops
100+ speakers
2 award ceremonies and 5 satellite events
The summit confirmed the central role of deeptech and applied AI in Europe’s innovation strategy.
Key Takeaways from Lili.ai
AI is already solving real problems
AI is not just a promise. While some aspects may still be overhyped, AI is already addressing long-standing, concrete challenges.
At Lili.ai, we see this clearly in complex projects: extracting factual timelines from massive volumes of emails and written communication was simply not scalable for humans. The consequence was accepted margin loss and unmanaged risk. AI changes that reality.
Trust is not optional
For AI systems to deliver real value, people must be able to trust them. Regulation is one way this trust is being enforced. While regulation is not always the preferred path, it is now part of the landscape. The challenge, therefore, is not to resist it, but to work with it; and continue to innovate within that framework.
The next wave of AI: empowering those who know
The future of AI is not about replacing people. It is about amplifying the expertise of those who understand the domain best.
To do so, AI must confront real-world constraints: large data volumes, budget limitations, operational complexity, and above all, the need for trust. Pragmatism, not abstraction, will define the next phase of AI adoption.
We are proud to contribute to these discussions and to help shape a practical, trustworthy, and impactful vision of AI for complex projects.
