Generative AI is not the panacea we’ve been promised | Eric Siegel for Big Think+

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Oct 19, 2025

Eric Siegel, CEO of Goodr AI and author of The AI Playbook, discusses the misconceptions surrounding generative AI. While it's capable of impressive tasks, Siegel warns that it requires human oversight and isn't a standalone solution. He highlights the value of predictive AI, which provides concrete benefits like fraud detection and logistics optimization. Using UPS as an example, he explains how predictive modeling saved $350M by forecasting deliveries. Ultimately, it's about leveraging AI for practical, actionable insights.

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INSIGHT

Generative Hype Versus Practical Power

Generative AI is impressive but overhyped and won't run the world for you.
Predictive AI remains the practical engine with untapped enterprise value.

INSIGHT

Fluency Isn’t Reliability

Generative models often appear human-like because they stitch correct words at a low level.
That surface fluency doesn't guarantee reliability or autonomous trustworthiness.

ADVICE

Apply Predictive Models To Core Operations

Use predictive AI to improve and automate high-volume enterprise decisions.
Deploy models to prioritize actions like marketing, fraud detection, inspections, and patient triage.

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There's an illusion around generative AI. 🤖 Headlines promise it’ll revolutionize everything, solve business problems, and displace workers. But that’s hype.

Generative AI is *impressive*, yes — capable of first drafts, conversations, and mimicking human language. But it isn’t magic. It's not autonomous. You still need to proofread, verify, and correct it. ✍️

Meanwhile, **predictive AI** — the older cousin — quietly delivers real, measurable value. It improves operations by making **data-driven predictions** that inform decisions:

- Who to market to 🛒

- Which transaction is likely fraud 💳

- Which train wheel or building might fail 🚂🔥

- Which patient might be readmitted 🏥

These predictions help prioritize and triage at scale — fast, autonomously, and effectively.

Timestamps:

0:00 - The Generative AI illusion

1:05 - Generative AI’s function

3:13 - Generative vs. Predictive

4:21 - The Predictive AI process

6:57 - Moving towards AGI?

I’m Eric Siegel — CEO of Goodr AI and author of *The AI Playbook*. I’ve watched AI hype evolve since the '80s, and I believe **value lies in action**. Predictive AI is the real engine behind enterprise optimization.

Take UPS, for example. 📦 They use predictive AI to forecast tomorrow’s deliveries — even before all packages arrive — allowing for optimized routes and loading. The result? $350M saved yearly, and major emissions cuts. ♻️

It’s not about perfection. It’s about probability, scale, and deployment.

Generative AI is amazing to watch — but if you're chasing **Artificial General Intelligence** (AGI), you're buying into a sci-fi dream. The real power of AI today? Concrete, credible, enterprise use cases. 🚀

Forget the hype. Focus on **what improves operations now** — and deploy it.

About Eric Siegel:

Eric Siegel is a leading consultant and former Columbia University and UVA Darden professor. He is the founder of the long-running Machine Learning Week conference series, a frequent keynote speaker, and author of "The AI Playbook: Mastering the Rare Art of Machine Learning Deployment," as well as the bestselling "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die."

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