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AI Readiness Ep 11: Getting AI Done. Engineering, Enablement, and the Execution Gap

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Manage episode 494318744 series 3593165
Content provided by Daniel Thornton. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Daniel Thornton or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In this episode, Andy Davis is joined by Andy McMahon, Principal Engineer for AI & MLOps at Barclays, to unpack what AI transformation really takes inside large organisations.

They dig into the realities behind the GenAI hype, including the tough conversations around data readiness, process redesign, and the cultural ingredients needed to deliver value at scale. From proof-of-value pitfalls to bridging the POC-to-production “chasm,” this is a brutally honest take on why most AI efforts stall — and how to avoid the same fate.

Whether you're leading technical teams or shaping data strategy, this conversation is full of hard-won lessons from the frontline of enterprise AI.

  continue reading

17 episodes

Artwork
iconShare
 
Manage episode 494318744 series 3593165
Content provided by Daniel Thornton. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Daniel Thornton or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In this episode, Andy Davis is joined by Andy McMahon, Principal Engineer for AI & MLOps at Barclays, to unpack what AI transformation really takes inside large organisations.

They dig into the realities behind the GenAI hype, including the tough conversations around data readiness, process redesign, and the cultural ingredients needed to deliver value at scale. From proof-of-value pitfalls to bridging the POC-to-production “chasm,” this is a brutally honest take on why most AI efforts stall — and how to avoid the same fate.

Whether you're leading technical teams or shaping data strategy, this conversation is full of hard-won lessons from the frontline of enterprise AI.

  continue reading

17 episodes

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