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Sam Khalil

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Sam Khalil

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Co-Founder & Managing Director ekona.ai

Sam Khalil is a healthcare leader and digital innovator with over 15 years of experience in the pharmaceutical industry, now co-founder and Managing Director of ekona, a Swiss AI engineering boutique launched in 2025.

Drawing on a career spanning technology, clinical development, and business strategy, Sam helps organizations harness AI and data to solve complex challenges and accelerate innovation.

Before co-founding ekona, Sam served as Vice President and Head of the FounData AI platform at Novo Nordisk, where he led the development of advanced AI-powered systems to transform clinical data into actionable insights.

Prior to that, at Novartis, he spearheaded the creation of data42, one of the industry’s first platforms providing enterprise-wide access to curated data from over 2,900 clinical trials. His earlier roles involved launching blockbuster drugs, leading global medical affairs teams and managing large-scale preclinical and clinical research programs. Sam is also a strong advocate for responsible AI, with deep experience designing ethical, transparent, and scalable AI systems for healthcare.

Bio from: Big Data LDN 2025

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Agents Among Us: Trust, Transformation & Accountability in the Age of Agentic AI

2025-09-24 · Big Data LDN 2025
Face To Face
with Sam Khalil (ekona.ai) , Kshitij Kumar (Data-Hat AI) , David Reed (DataIQ) , Jane Smith (ThoughtSpot) , Dr. Joe Perez (NC Dept of Health & Human Services) , Anusha Adige (EY)
AI/ML LLM

As AI agents become embedded in everyday workflows — from healthcare diagnostics to financial services chatbots — the line between human and machine continues to blur. This panel brings together industry leaders to tackle the tough questions:

• How do we trust AI agents in high-risk environments?

• What are the new rules of ownership and accountability when autonomous systems act on data?

• Is AI replacing or enhancing the human workforce — and how do we keep the balance right?

We'll unpack how AI agents are evolving across sectors, debate whether the current LLM paradigm is enough, and explore the new guardrails needed to futureproof agentic AI — without losing control.