Why Most AI Projects Fail to Move Beyond POCs and How to Fix It with Bo Gu, Director of Data Science & Generative AI at AT&T

In this episode of the AI Monetisation Podcast, Co-founder, Binny interacts with Bo Gu, Director of Data Science, Chief Data Office at AT&T, to explore why so many AI projects never make it past the proof-of-concept stage and how enterprises can fix it.

About the Guest

Bo Gu leads data science and generative AI initiatives at AT&T. With a career spanning data science leadership roles at Pepsi, HMS, and Caesars Entertainment, plus entrepreneurial experience building pricing software for the hotel industry, Bo brings decades of hands-on expertise in analytics, machine learning, and enterprise AI transformation.

What’s Inside?

1. Why 90% of AI projects stall at the POC stage

2. Governance, compliance, and cost frameworks for scaling AI

3. The importance of ROI as the ultimate filter for AI initiatives

4. Lessons from classical AI that still apply in the GenAI era

5. Productivity and customer-facing opportunities where AI delivers real business value

Key Takeaways

1. Deep expertise in data science, generative AI, and advanced analytics

2. Proven track record of applying AI to real business outcomes

3. Experience leading both corporate and entrepreneurial AI initiatives

4. Skilled in bridging technical innovation with business strategy

5. Strong foundation in engineering, finance, and strategic planning

This is a must-watch for anyone building or deploying AI in finance, especially if you're focused on measurable ROI, risk mitigation, and scaling innovation responsibly.

For full show notes, visit- https://bit.ly/42bOyHw

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