Manufacturing winners continue to deliver superior return on capital invested (ROCI) across all facets of their business by investing in data and AI strategies that build supply chain agility, promote increased operational throughput, or provide predictive insights into their supply chains. And yet, a majority of manufacturers are struggling to move their AI use cases to production, landing in "POC Purgatory'', not successfully moving into production, and consuming valuable time and resources. As a matter of fact, an Omdia study, sponsored by Databricks, found that on average half of all projects stall at the proof of concept (PoC) stage, due to budgetary concerns and a lack of data science expertise and reliable data.

Join Omdia and Databricks in this panel discussion that is beneficial to both IT and Business leaders, to discover how manufacturing professionals are addressing these concerns by adopting a more operational approach to their data architecture, one capable of surfacing new AI-driven revenue streams while increasing profitability and productivity.

Key topics that will be discussed:

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