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Leonardo
D'Ambrosi
Principal Data Scientist
Bayer
Leonardo Dā€™Ambrosi is a Principal Data Scientist where he leads the development of advanced agentic AI and machine learning systems to speed up Real-World Science (RWS) and optimize the use of Real-World Data (RWD) in evidence generation. His work focuses on building high-impact agentic AI solutions that accelerate critical decisions and provides scientists with deeper, more accessible insights. With over 15 years of experience in data science, healthcare analytics, and innovation, Leonardo combines strong technical expertise with strategic leadership to drive the adoption of AI within Pharma. Before joining Bayer, he led teams in several fast-paced technology startups, developing data-driven products for real-time decision support, predictive modeling, and automation. His recent research includes three peer-reviewed publications advancing the use of large language models for analyzing Real-World Data. Leonardo holds a Masterā€™s degree in Computer Science from the University of Turin, Italy.
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15 September 2026 12:00 - 12:30
Panel | Why do agent systems break in production? The gap between design and reality
Agent systems are hitting real production limits - unreliable tool calls, broken workflows, context loss, unpredictable decision-making, and systems that become difficult to debug once autonomy increases. As enterprises push agents beyond prototypes and into live environments, many are discovering that orchestration, observability, permissions, and reliability become significantly harder at scale. This panel explores the gap between agent design and production reality, unpacking the operational and architectural challenges emerging as autonomous systems move into enterprise deployment.