The Real Reason AI Projects Fail with Karina Arteaga episode artwork

EPISODE · May 15, 2026 · 36 MIN

The Real Reason AI Projects Fail with Karina Arteaga

from Get Amplified · host Amplified Group

Send us Fan MailAI feels like it should be a shortcut to productivity, yet most teams still struggle to turn pilots into real business value. We sit down with Karina Arteaga, CEO and founder of Visible Global and former operations leader at Meta Reality Labs, to unpack the uncomfortable reason: AI projects fail less because the tech is weak and more because the organisation is unclear, messy, or misaligned. If your objectives, decision-making, and workflows are broken, automation just scales the chaos.We explore what it takes to build a human AI operating model that actually works in the real world, where people have fears, incentives, and habits.Karina shares lessons from building an operating model from scratch in a high-growth, AR/VR and AI environment, and she explains why leaders should start with basics: map the workflow, clarify ownership, and decide what outcomes matter before choosing tools. The conversation moves into agentic AI and autonomous workflows, and why that shift makes human judgement more important, not less. Finally, we get practical about change management: listen to employees, solve the most painful parts of the job first, and use internal champions to drive adoption without creating a Big Brother culture. If you want AI transformation, organisational design, and leadership culture to pull in the same direction, subscribe, share this with a colleague, and leave us a review.We would love you to follow us on LinkedIn! https://www.linkedin.com/company/amplified-group/

Episode metadata supplied by the publisher feed · Published May 15, 2026

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Send us Fan Mail AI feels like it should be a shortcut to productivity, yet most teams still struggle to turn pilots into real business value. We sit down with Karina Arteaga, CEO and founder of Visible Global and former operations leader at Meta Reality Labs, to unpack the uncomfortable reason: AI projects fail less because the tech is weak and more because the organisation is unclear, messy, or misaligned. If your objectives, decision-making, and workflows are broken, automation...

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The Real Reason AI Projects Fail with Karina Arteaga

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