Sixty percent of enterprises are evaluating AI. Twenty percent reach pilot. Five percent deploy successfully at scale. The gap is not the model. It is the data, the architecture, and the organisational design beneath it. The 95% Problem examines why enterprise AI fails in production — and what the organisations in the 5% are doing differently. From agentic Hosted by Rıdvan Yiğit | Founder & CEO, RTC Suite rtcsuite.com · [email protected] · linkedin.com/in/yigitridvan
Latest episodes
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24 min
Series 7 - The Debate : Chain of Thought vs. Chain of Action: The Debate That Defines Whether Your AI Investme…
There are two fundamentally different things that enterprise AI can be. Understanding the difference — and having a clear view of which one your organisation is actually building —…
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22 min
Series 7 - The Critique : Agentic AI on Legacy Systems: Why Deploying Intelligence on Broken Data Architecture…
The enterprise AI market has a dominant narrative: the models are now powerful enough to handle messy, unstructured, imperfect data. The era of requiring clean data before AI can b…
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2 min
Series 7 - Deep Dive: Why Enterprise AI Fails in Production: The Complete Technical and Organisational Deep Di…
The 95% failure rate in enterprise AI deployment is not a headline. It is a diagnostic. And the diagnosis, examined in full technical and organisational depth, points to a specific…
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21 min
Series 7 - The Brief : Why 95% of Enterprise AI Projects Fail Before They Reach Production — The Brief Every E…
The numbers are not in dispute. Research consistently shows that approximately 60% of large organizations are actively evaluating enterprise AI. Around 20% progress to meaningful p…