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The Great Pharma Reorganisation: Building an Operating Model for the AI Era

Speaker Name

Job Title

Company Name

Reuters Events

The Great Pharma Reorganisation: Building an Operating Model for the AI Era

November 
19
, 
2026
 / 
4PM GMT / 5PM CET 
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Speaker Highlights

Iria 

Gala

head of strategic operations

ucb 

Marcus

Picconi

Product Line Manager Of data foundations

Sanofi

Jonathan

Elliott

Director of content development

Thomson reuters

Kate

Thota

Vice President,

strategic capabilities and operations

Sobi - North america

Drew Rocket

Senior director medical affairs, insights & analytics

Bayer


Hybrid. Who knew a year ago this unremarkable word would have such a large part to play in pharma’s future lexicon and strategy building?

AI is forcing pharma leaders to confront a question few organisations can confidently answer: What should the pharmaceutical company of the future actually look like?


Across the industry, companies are redesigning operating models, redefining leadership structures, and reassessing where decisions should sit between global, regional and local teams. Yet despite repeated reorganisations, many leaders admit they are still searching for the right balance between governance, agility and innovation.


As AI becomes embedded across commercial, medical, R&D and corporate functions, organisations must determine which capabilities should be centralised, which should remain local, how workforce roles will evolve, and what new skills will be required to compete successfully in the decade ahead.


This candid discussion brings together leaders at the centre of enterprise transformation to share what is working, what is failing and how pharma organisations are preparing for an AI-enabled future.


• Benchmark different operating models being adopted across pharma and identify the structures best suited to an AI-enabled future.


• Learn how leading organisations are balancing centralized governance with local innovation while evolving workforce capabilities.


• Gain unfiltered insights into the transformation challenges, failed experiments and hard-earned lessons shaping the next generation of pharma operating models.

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