Many AI programmes generate promising pilots, then stall when results meet real operating pressure. This episode examines why early success often proves possibility rather than readiness for scale.
It explores the shift from pilot activity to managed AI systems.
TLDR / At a Glance
• Pilot signals and scale risk
• Repeatability as the real test
• Workflow embedding and ownership
• Monitoring, feedback, and controls
• Reusable patterns over fragmented tools
• Leadership discipline in AI portfolios
The key takeaway is that AI scale depends on building managed systems that make repeatability operational.
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Kieran Gilmurray. Innehållet i podden är skapat av Kieran Gilmurray och inte av,
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