Scaling AI Adoption in Life Sciences Manufacturing & Operations

In this Straight from the Source episode, Inna Ben-Anat, AVP, Global Head of Smart Factories, Manufacturing and Supply at Sanofi sits down with Daniel R. Matlis to explore what separates AI activity from meaningful AI adoption and what organizations need to achieve value at scale.

Source: Axendia, Inc.

Drawing on real-world experience in life sciences manufacturing and operations, they discuss lessons that extend across the organization: starting with the right business problem, defining value early, establishing trusted data and strong governance, preparing the workforce, and designing for scale from the start.

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In this conversation, they share:

  • How to move from AI experimentation to measurable value
  • What separates scalable AI adoption from isolated pilots
  • Why trusted, AI-ready data is foundational
  • How governance, validation, and human oversight support responsible AI
  • Why people, skills, and adoption are critical to success
  • What it means to build for scale from the start

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The opinions and analysis expressed in this post reflect the judgment of Axendia at the time of publication and are subject to change without notice. Information contained in this post is current as of publication date. Information cited is not warranted by Axendia but has been obtained through a valid research methodology. This post is not intended to endorse any company or product and should not be attributed as such.

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