Скачать или смотреть Why Most AI Projects Fail to Move Beyond POCs and How to Fix It with Bo Gu, Director of Gen AI, 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/4nOPLNl

🎧Check out this episode on Spotify- https://bit.ly/46VOu1k

🎧Check out this episode on Apple Podcasts- https://apple.co/4nsvBJe

ProjectPro helps you tackle your AI projects with ease. Upskilling the team for specific AI projects, collaborating with experts to co-build AI solutions, or opting for end-to-end project outsourcing, ProjectPro has you covered. With ongoing 1:1 support, enterprises can overcome roadblocks and seamlessly take their projects from PoC to production. Learn more- https://bit.ly/48xkgmr

TIMESTAMPS

0:00 Bo Gu
04:44 From classical AI to GenAI
06:00 Why AI is not new
07:24 Forecasting and classical AI value
09:23 ROI as the key AI filter
10:10 Real ROI examples from Caesars and Pepsi
12:18 Why ROI must come before AI trends
13:13 Enterprise AI monetization paths
14:29 GenAI in call centers and customer service
15:49 Customer insights from call transcripts
17:23 Future of software development with AI coding
19:14 Pair coding and debugging challenges
21:14 Managing complexity in AI coding
23:34 Why most AI projects fail to scale
24:21 Governance and compliance in AI projects
26:22 Controlling costs in AI initiatives
27:47 Skills every data scientist must build
29:25 Why storytelling is key in data science
31:01 Biggest challenges for AI leaders
32:34 AT&T’s AI platform success stories
34:41 Persuading leaders with AI ROI
35:03 CTA's

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