What Manufacturing Leaders Need to Know About Scaling Agentic AI

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Summary

Manufacturing is further along the AI curve than most industries — but being further along doesn't mean being further ahead at scale. New primary research from Omdia/Informa TechTarget, commissioned by Snowflake, reveals a sector experimenting aggressively but converting inconsistently: 52% of manufacturers already have live AI in supply chain or operations, yet 43% cite fragmented data as the primary barrier to scale. IT, OT, and IoT data sit in separate systems, none unified for an agent to act across. 

The fix isn't a better model — it's a unified data foundation. This session unpacks what the research means for manufacturers and lays out the four-stage roadmap companies that have scaled have followed.

What you’ll learn:

• What the research reveals about manufacturing’s AI reality
  • Adoption rates, where investment is flowing, and the structural barriers blocking scale
• Why pilots succeed by scaling fails
  • The IT/OT/IoT fragmentation barrier and why agents can’t act on data they can’t see
• The four-stage roadmap to production agentic AI
  • Data foundation first, agents second

Speaker

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