Most AI projects don't fail because the technology is wrong — they fail because nobody agreed on what success looks like before the pilot started. Hemang Upadhyay has spent 16 years watching that pattern repeat, and he's built a framework to stop it.
In this episode:
• Why Gartner's stat — only 5% of AI initiatives reach production — is a leadership problem disguised as a technology problem
• The three measurement layers every AI deployment needs: quality, operational performance, and business impact
• How to establish governance, ownership, and cross-functional alignment before a single model is selected
• What production-ready AI actually means in practice — and why a successful demo in a conference room proves almost nothing
Hemang Upadhyay is an enterprise product and AI leader with 16 years of experience spanning enterprise AI, digital commerce, product data governance, and AI-enabled customer experience. He is a TED Talk speaker, published researcher, and active open-source contributor who mentors startups and helps small and mid-sized businesses adopt AI responsibly. He shares his frameworks and thinking independently at hemangai.com.
Connect with Hemang Upadhyay:
LinkedIn: https://www.linkedin.com/in/hemangupadhyay
Website: https://www.hemangai.com
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Credits
Host: Robin Ayoub, Founder, Localization Fireside Chat
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