Speakers

As AI technologies rapidly evolve, leaders face a critical inflection point: how to integrate AI into the workplace ethically while maintaining trust, equity, and human agency. This presentation explores the practical implications of ethical AI for the future of work, highlighting the risks of bias, opacity, and displacement—and the opportunities for innovation, inclusion, and resilience.

The challenge lies not in the technology itself, but in the decisions surrounding its deployment. Many organizations lack clear governance structures, workforce training, or ethical oversight, leaving them vulnerable to reputational and operational risks. This talk offers a pragmatic approach: embedding ethical principles into AI design, fostering cross-functional accountability, and equipping teams with the skills to navigate change.

We will explore some takeaways on: how to assess AI readiness across your organization, build ethical guardrails without stifling innovation, and create a culture where responsible AI is a shared priority—not just a compliance checkbox. The future of work will be shaped not just by what AI can do, but by how we choose to use it.

Large language models (LLMs) are powerful, but their out-of-the-box performance often doesn't meet specific business requirements. This gap can make it difficult to use them in real products.

This talk explains our method for optimizing LLM performance for specific business needs. We start by establishing clear metrics and evaluation systems to test against key business specifications, such as safety and usefulness. Based on these measurements, we then develop and refine prompts in a cycle of continuous testing. We will show how this structured process helps us meet high standards for model behavior.

The key takeaway is that reliable AI performance comes from a structured process rooted in measurement. Attendees will learn how a focus on evaluation, which then informs prompt engineering, can turn a general model into a specialized and effective business tool.

In this talk, I will share how we, at AstraZeneca are applying agentic approaches to accelerate scientific R&D, highlighting specific examples. Along the way, I will also highlight the practical lessons learned from building agentic systems in real R&D settings, the challenges of aligning agents with expert workflows, and the opportunities for collaboration between humans and agents. The session will also look ahead to broader applications, illustrating how agentic AI can reshape the way we discover, design, and deliver innovation in Healthcare.

The broad opportunities for Gen AI in Legal and how Opus 2 has been solving it. What are the challenges still facing the industry and how Gen AI can solve it.

Since the release of Stable Diffusion XL in 2023, image generation models have moved beyond popular imagination to become practical tools in architectural design offices. As these models scale in both size and capability, their increasing ability to precisely render images expands the scope of their application – opening new opportunities for design exploration and workflow innovation. How may we best implement these ever-evolving workflows through the sustained collaboration between developers and designers?

As GenAI systems evolve into multi-step, reasoning agents, evaluation becomes the hardest part to get right. Traditional benchmarks measure single responses, but they fail to capture whether an agent can plan, act, and deliver a correct end result. This talk presents a practical framework for evaluating agentic workflows, combining goal-completion metrics, step-level validation, regression testing, and failure simulation, to help teams move from demo-ready to production-ready systems.

Dr. Oren Dinai will also discuss evolving techniques such as LLM-as-judge scoring, rubric calibration, and human oversight, showing how they can make evaluation faster yet more reliable. The session emphasizes one key idea: evaluation should not be an afterthought, but a built-in part of design, ensuring GenAI systems are measurable, reproducible, and trustworthy at scale.

Imagine a world where you could access the voice of your customer at any moment.

Well... now you can.

What it means to be a truly customer-centric business has changed. Traditional customer research and a needs-based lens remain critical, but now, they're only one side of the equation.

This session will expose the unprecedented opportunities that come with harnessing synthetic audiences. With digital representations of your target customer and key stakeholders, businesses can now embrace continuous collaboration, more rigorous interrogation, and a deeper, more dynamic understanding of customer needs.

Join me as we uncover the future of customer-centricity through dialogue with data.

A tidal wave of regulations has his hit M&A deals and it keeps getting bigger. Companies can have to comply with hundreds of regulatory regimes when they look to acquire other businesses. If they get it wrong their deals can be blocked, they can be fined and directors can go to jail. But it's difficult to comply with an ever-growing list of complex regulations when the key facts are buried in thousands of documents. We've translated our Magic Circle legal experience into AI-powered software to dramatically improve the process for lawyers and the companies they advise.

In today’s rapidly evolving technological landscape, the intersection of organizational transformation and individual innovation is more critical than ever. This speech explores the journey of driving innovation within a dynamic corporate environment, highlighting how structural and operational changes shaped this path. It delves into the balance between a company’s need to adapt swiftly to external shifts and the individual’s role in fostering innovation, emphasizing how one influences the other.

Key themes include the importance of agility, continuous learning, and cross-unit collaboration. Initiatives like the AI Circle and AI Community played pivotal roles in fostering cultural change, enhancing AI literacy, and promoting the acceptance of generative AI. Structured programs such as internal job rotations and mentorship provided the foundation for focused, entrepreneurial growth, while resilience in navigating complex, long-term projects underscored the need for adaptability and strategic decision-making. The speech also shows how the strong and supportive culture driven by management ensured alignment, success, and scalability.

Katarina Granath, as part of SIX’s strategic initiatives, exemplifies this journey. She spearheaded the development of one of the company’s first Generative AI Bots in 2023, significantly improving data mapping efficiency and aligning with SIX’s data-driven strategy. She has a background as entrepreneur, is a lecturer at HWZ Zurich, and speaker at conferences in Zurich and London.

We show how recent developments allow us to develop agentic reasoning models that both understand the patient and the clinical environment so they can act as real assistants to the clinical experts.

Drawing on more than 20 years of filmmaking experience and research in affective computing, this talk presents "Friendly Fire at the Shrink", an interactive installation built around the fictional mental health AI startup «MindFix». Our work utilizes state-of-the-art generative AI to investigate how humans respond to emotionally expressive systems, and how quickly our belief in their intelligence collapses when we experience their limitations firsthand. This presentation will also detail the project's broader applications in research and education, including workshops on conversational design, presentations at leading AI conferences like NeurIPS 2025, and ongoing neuroscientific studies at ETH Zurich's Decision Science Laboratory to further explore the installation's cognitive and societal impact.

Digital design has long empowered architects, engineers and designers to explore advanced geometries and automate CAD workflows. However, the CAD tools to do this, while powerful, present a steep learning curve. This creates a barrier between design intent and design execution, and makes design processes time-consuming, frustrating and certainly not fun.

In this talk, we’ll show how Romantic Labs' AI Copilot 'Raven' removes these barriers, making advanced digital design accessible, efficient and fun. Users can describe their design intent in plain language or with photos of their sketches. The AI interprets the intent, builds the underlying parametric graph, and connects seamlessly into existing CAD software workflows to provide the user with advanced services, like structural optimization or climate analyses.

We’ll explore how this approach harnesses the entire CAD ecosystem, automates repetitive modeling tasks, and accelerates iteration cycles — while preserving full control and editability for advanced users. Attendees will see relevant use cases and examples of natural language prompts generating complex parametric forms in seconds and automating previously tedious tasks. By merging generative AI with the parametric modeling paradigm, we are entering a new era of CAD: One where designers collaborate with intelligent agents, not just software. Romantic Labs does not only provide an incremental upgrade, but lays the foundation how humans create with computers in the AI era.

Gain the ethical edge! Learn practical strategies to weave human rights, cybersecurity, and ethics into tech solutions, driving sustainable impact even with limited resources. Empower your organization responsibly.

The rapid rise of generative AI is often framed as a technological race, but the real challenge lies in how people adopt, trust, and meaningfully use these tools. Too often, adoption strategies focus on functionality and efficiency while overlooking the cultural, psychological, and ethical dimensions that ultimately shape human behaviour. The problem is not whether generative AI can transform industries—it already can—but whether individuals feel empowered, confident, and inspired to use it in ways that create lasting value. Without this human alignment, even the most advanced AI risks remaining underutilised or misapplied.

My approach reframes AI adoption as a human-centric transformation. This means recognising that trust, inclusivity, and imagination are not soft factors but core enablers of technological progress. I will explore how organisations can move beyond transactional training and instead cultivate curiosity, resilience, and a sense of shared ownership over AI. By creating environments that encourage safe experimentation and open dialogue, we can shift from a narrative of fear and displacement to one of empowerment and possibility.

The key takeaway is clear: the future of generative AI will be defined less by what machines can do and more by what people dare to do with them. Leaders who prioritise psychological safety, equity, and culture will unlock deeper adoption and innovation. My message is that generative AI is not simply a story about technology—it is a story about people reclaiming their potential in an age of accelerating possibility.

Small business owners are overwhelmed. Juggling social media, writing email campaigns, and managing customer messages is a full-time job that drains valuable time and energy, leading to burnout and missed growth opportunities.

MATI AI provides a simple, powerful solution: a dedicated "remote AI employee." Our platform automates all your marketing tasks from one intuitive dashboard. Whether you need a week's worth of social media content, a promotional email blast, or automated WhatsApp replies, your AI employee handles it all.

By delegating these complex tasks, MATI AI gives you back your time, allowing you to focus on what truly matters—running your business. It’s your expert, scalable marketing team, available 24/7 at a fraction of the cost

In today’s complex regulatory landscape, gaining a clear view of operational and compliance risk is as critical as ever. At a systemically important financial institution, I led a transformation of risk reporting and oversight by applying AI to automate the mapping of thousands of internal controls to external regulations and internal policies. Starting with a low-cost proof-of-concept I demonstrated significant effort reduction, and ultimately improved the quality of oversight through a scaled-up solution. This session will share lessons from that journey — including the design principles that proved effective, how I mitigated common pitfalls such as false positives and SME fatigue, and how AI has been practically applied to deliver real impact for Risk Managers, the Risk Committee, and the Chief Risk Officer.

The popularity of AI art has exploded over the past few years. From its beginnings with DeepDream in 2015, AI art has moved beyond technology circles into the public eye, shaping media art, contemporary art, and digital culture. The rise of prompting, multimodal AI and AI agents have expanded creative possibilities, while concerns over AI slop and copyright continue to fuel critical discourse. As generative AI tools become widely accessible, artists are exploring new forms of collaboration, aesthetics, and authorship. This talk will give an overview of how artists and technologists use and think about AI, its creative potential, and societal impact.

This talk explores how today's creative AI and machine learning movement (both as production methods and as an expressive medium) connects to its roots in older traditions in computational art, specifically procedural graphics and generative practices that existed for decades before neural networks became mainstream. These earlier approaches established many of the core concepts now resurfacing in AI-driven creativity.

Understanding this evolution matters because it provides a clearer picture of what generative systems can actually do, beyond the current hype. By tracing how these ideas developed over time, we can better assess both the genuine capabilities of modern approaches and where they might realistically go next.

Since the author works primarily with visual media, the presentation will be illustrated with visual examples, including work from both generative art history and the author's own practice. These pieces demonstrate how concepts and techniques have evolved from basic algorithmic approaches to contemporary AI methods.

The talk is designed for both business and technical audiences looking to understand generative systems with better historical grounding and context.

In recent years, Artificial-Intelligence (AI) has emerged as a significant driver of digital disruption across various industries. Among its many applications, AI art stands out as a particularly intriguing and transformative field. This lecture explores AI as a force of digital disruption, with a specific focus on AI video art as redefining traditional artistic boundaries, challenging established norms, and opening new possibilities for imagination, creativity and cultural expression.

As AI adoption accelerates, organizations face a common challenge: moving beyound flashy demos to building, production-grade systems.In this talk we will introduce LLM4S, a framework designed to bring structure, reliability, and scalability to AI applications. We will explore how features such as retrieval-augmented generation (RAG), model-context protocol (MCP) and other GenAI techniques can be applied in practice, and why building on a strong, complete toolkit matters for long-term success. This session is designed for engineers, data professionals, and business leaders alike, blending technical insight with real-world applications. Attendees will leave with a deeper understanding of what it takes to transform large language models into dependable AI systems.