How AI Will Reshape the Economy, w/ Anindya Ghose, the Director of AI at NYU Stern

What does an AI-driven economy actually look like when you zoom out far enough—and what does that mean for jobs, power, and policy?

In this episode of AI-Curious, we talk with Anindya Ghose (NYU Stern; author of Thrive) about the “AI economy blueprint”: how the modern economy starts to resemble a vertically layered tech stack—from energy and chips all the way up to consumer-facing apps—and why that stack is quietly reshaping everything from corporate strategy to the future of work.

We cover what’s changing fastest, where leaders are getting tripped up, and what skills matter most if you want to stay valuable in a world of copilots and agents.

Topics

• The AI economy as a tech stack: energy → semiconductors → data centers/cloud → LLMs → applications, and why the consumer “app layer” is just the visible tip.
• Why every company is becoming an AI company (even airlines, banks, retailers)—and how the real dependency sits beneath the apps in infrastructure and model providers.
• Consolidation and vertical integration: how a handful of companies can span multiple layers (chips, cloud, models), and what that could mean for pricing power and competition.
• Jobs and labor markets: why disruption is outpacing creation in the near term, and a provocative forecast for how “portfolio careers” could become the norm.
• Reskilling at scale: from self-learning to certificates to formal programs—and why government-led approaches may be required.
• A concrete framework from Singapore: a “Marshall Plan”-style push to fund AI upskilling and retooling.
• Agentic AI reality check: why many agent projects fail in practice—and the unglamorous workflow work companies often skip.
• Regulation, in three arenas: competition/antitrust dynamics across the stack, copyright/fair use lawsuits, and whether consumers should be told when content is AI-generated.
• Geopolitics of models: the global trade-offs between Western model ecosystems and lower-cost open-source alternatives abroad.
• The underrated career edge: not just knowing what GenAI can do—but knowing when it fails and why, and how that becomes a durable source of leverage.

About the guest

Anindya Ghose is a professor at NYU Stern and leads NYU’s MS in Business Analytics & AI program. His work focuses on AI, digital transformation, and the modern data-driven economy. He’s also the co-author of Thrive.

If you want to pressure-test your own AI strategy for 2026, this episode is a good place to start: think “stack,” not “tool.”