Many organizations experiment with AI through chatbots and isolated pilots but struggle to scale impact in innovation. This session shows how the Innovation Lab of ZF’s Commercial Vehicle Division moves from ad-hoc AI use to orchestrated, agent-based systems supporting the full innovation process. Participants learn the maturity path from simple GPT usage to agent orchestration and AI-native innovation, and how this enables faster, more consistent, and better-governed innovation decisions.

Manufacturing organizations are built on processes refined over decades. While AI promises efficiency and automation, introducing it into such environments often creates friction — confusion, resistance, and loss of trust among employees. In this session, I will share how AI can be introduced into a mature manufacturing organization without disrupting existing workflows, and how thoughtful AI adoption can improve day-to-day work for employees rather than complicate it. Drawing on real-world experience leading AI transformation in a global manufacturing company, this talk focuses on integrating AI into established processes in a way that feels natural, supportive, and reliable. Instead of replacing people or redesigning everything from scratch, the approach emphasizes augmenting existing roles, reducing cognitive and operational load, and building trust through transparency and gradual adoption. I will walk through how AI solutions were embedded into daily operations, how employee concerns were addressed, and how adoption was driven through practical value rather than top-down mandates. Key takeaways: - How to introduce AI into long-established processes without creating resistance - Why employee trust is critical for successful AI adoption - How AI can improve individual productivity while strengthening the overall system - Practical lessons from integrating AI into real manufacturing operations

What happens when an AI learns to design? Raven, our AI-driven CAD tool, revealed unexpected possibilities and limitations in how machines interpret space, intent, and creativity. In this talk, I will share the story behind Raven’s development, the challenges of teaching design principles to an algorithm, and the surprising ways humans respond to an intelligent design partner. You’ll see how Raven accelerates exploration, elevates decision-making, and reshapes the early stages of architectural work. This presentation invites you to imagine a future where designers and AI collaborate to unlock ideas once out of reach.

Problem:‍

In sensitive application domains such as legal AI, impressive demos are easy to produce — reliable systems are not. What matters is the ability to systematically measure, compare, and control model performance. Without transparent statements about precision, error rates, and limitations, GenAI in real-world workflows remains opaque and risk-prone.

Approach:‍

The talk shows why high-stakes AI requires a clearly defined gold standard: structured data, annotated samples, and systematic benchmarking of model performance against human experts. With the emergence of agentic AI, many control steps can be significantly accelerated and partially automated as operational human intervention is reduced. The core principle remains unchanged: transparency about output quality. Model precision and error rates must be measurable and clearly communicated.

Key takeaways:

‍• Why demos fail as a proxy for real AI performance?
• Why human benchmarking remains essential even with agentic systems?
• How agentic AI increases speed without removing responsibility for output quality?

Generative AI is beginning to reshape how news is created, translated, verified, and delivered — but for a global news organization like Reuters, innovation must go hand in hand with trust. In this talk, I will share how Reuters is approaching generative AI as both a powerful technological enabler and a responsibility‑critical capability.
Drawing on practical experience, the session explores how generative AI is being applied across the news lifecycle, including support for journalists and editors, workflow efficiency, multilingual content, and product experiences. The focus is not on experimentation for its own sake, but on real deployment decisions in a high‑stakes environment where accuracy, independence, and transparency are essential.
The talk will highlight key design choices and trade‑offs: where generative AI delivers clear value, where it must be constrained, and how human editorial judgment remains central. I will also discuss governance, risk management, and cultural adoption challenges when introducing generative AI into a trusted media organization.
The session concludes with practical lessons for media leaders and technologists navigating generative AI in environments where credibility is the product.

Generative AI adoption is accelerating across industries as organizations integrate it into everyday workflows to improve productivity and decision‑making. At Sonova, we are on the same journey within Hearing Aid R&D. This talk shares Sonova’s experience of adopting Generative AI in R&D workflows, starting with grassroots initiatives in software development and expanding into a broader set of use cases. A central focus of the journey has been responsible adoption. Introducing GenAI in medical‑device R&D requires careful consideration of security, quality, safety, and intellectual property. The session concludes with concrete lessons learned from our adoption journey to date and a practical overview of how GenAI is being applied in Hearing Aid R&D today.

In a world of fragmented data, slow decisions, and organizational silos, true intelligence doesn’t come from bigger models, but from smarter, domain‑aware ones. Instead of building massive models, the real breakthrough is weaving meaning into the systems we already use. This talk shows how domain‑optimized Small Language Models harmonize data, processes, and decisions across complex architectures. From semantic extraction to real‑time conflict detection, learn how SLMs evolve into intelligent agents that strengthen architecture, reduce rework, and drive coherence at scale. Discover how a semantic fabric turns complexity into clarity, enabling real‑time understanding, seamless collaboration, and intelligent governance as organizations move toward a truly cognitive future.

Zurich Airport is exploring how AI-driven and autonomous solutions can be introduced responsibly in a complex and highly regulated environment. While the potential is significant, moving from experimentation to operational use requires more than new technology — it requires careful preparation and clear structures. This talk shares how Zurich Airport is approaching this journey. We will outline the steps taken to strengthen digital foundations, clarify governance responsibilities, and ensure compliance, safety, and transparency when evaluating AI use cases. Rather than presenting large-scale transformation, the session focuses on practical progress, lessons learned, and the realities of implementation. Examples from the aviation context will illustrate where AI shows tangible value today, where limitations remain, and how expectations are managed internally. The emphasis is on building understanding, aligning stakeholders, and creating conditions that allow innovation to develop in a controlled and responsible way. The session offers a realistic perspective on what it means for an airport to move from isolated experiments toward a more structured approach to AI — acknowledging both opportunities and constraints along the way.

Traditional executive search and recruitment remain largely relationship-driven and under-digitised, with limited transparency into how candidates are evaluated and shortlisted. Data and AI are still rarely used in a structured way for leadership decisions. Tagliabue & Partners, a specialist executive search firm, partnered with thirty3, an AI solutions company, to rethink this model. Together, they built a platform that brings structure, transparency, and scalability to the hiring workflow. In this talk, we will showcase the system that automates batch CV screening and generates client-ready longlist decks with structured, evidence-based candidate evaluations — demonstrating how Generative AI can transform high-stakes talent decisions.

"The $10M Question: Why Is Nobody Using Your AI Tools?" You've invested. The tools are deployed. The licenses are running. But only 15% of your employees actually use AI productively. 74% of companies see zero ROI from their AI investments – not because the technology fails, but because they're ignoring the critical 70%: people and processes. In this talk, I'll show you: Why the AI Adoption Gap is widening in 2025, not closing What the 5% leader companies do differently (Spoiler: They invest 70% in enablement, not tools) How our Parnters went from 15% to 85% adoption – in under 6 months. With concrete numbers, measurable results, and a playbook you can implement the next day. For everyone tired of burning millions on unused AI.

"Move fast and break things". At the International Committee of the Red Cross, breaking things means putting the lives of the most vulnerable at high risk. In this talk, the audience will learn how this 160 years old humanitarian organisation has developed its Artificial Intelligence policy. How it found ways to take into account complex working environments: wars, autonomous weapons systems, polarization, politization of aid, hate speech, scarce resources and data, people who have lose their house or family members. How it embedded its fundamental principles of humanity, impartiality, neutrality and independence that are critical to allow access to communities affected by armed conflicts. But how in the meantime, it wanted to foster innovation in an accountable, responsible and fair manner.

Imagine you're into playing instruments, singing, and producing music, but you’re lacking the decades of practice. Still, you write great lyrics and just "want to make music". As a personal project/side quest, I bridged that gap leveraging GenAI, my production skills, and professional post-production tools.

The result is Windlereye, a fictional alternative rock band with over 100 songs. Some of them are even good!

In this talk, I’ll demystify the "one-click" misconception by sharing details on my hybrid workflow and the workarounds I used to jump the biggest GenAI hurdles (vocal consistency, artifacts, instability). I'll explain how GenAI made me a better lyricist, and how I made my first whooping $0,000,001.12 in royalties.

Finally, I'll touch on my non-expert opinion on ethics and legal matters of this new frontier.

The Problem: Generative AI has shifted from a technological novelty to a critical organizational challenge. However, for SMEs and agencies, the reality isn't about infinite R&D budgets or massive teams—it is about limited resources, short ROI expectations, and a "fully booked" workforce that struggles to find time for innovation. How do you move from "doing the right thing" to "doing things right"? The Approach: As the AI Lead at Webrepublic, I will share how we kill the buzz to focus on functionality that brings immediate value today. We view AI not just as a new tool, but as a "second chance" to fix essential data structures and define processes. This talk explores how we navigate the difficult balance of scaling with a small AI core team while managing diverse stakeholder fears regarding job security and business model disruption. Key Takeaways Organizational Shift: Strategies to push participation and adoption across departments, even when teams are at capacity. Smart Scaling: How to secure internal budgets, build vendor partnerships, and track adoption with limited manpower. Real Impact: Methods to moderate innovation conversations and prove the direct value of integrated AI to clients.

Biased GenAI products stifle innovation, from flawed data to homogenous teams missing real-world blind spots. How do you build diverse teams that catch biases early and deliver superior products? What rituals and skills ensure ethical, inclusive development from ideation to production? Join Priska Burkard to discover why diverse teams are your edge in GenAI success.