In this episode of The Macro AI Podcast, Gary Sloper and Scott Bryan break down why Amazon’s Trainium chip is not just a hardware announcement, but a signal that the economics of AI are fundamentally changing.

They explore how Amazon Web Services is using custom silicon like Trainium to shift enterprises from renting AI to building and owning it—and why that strategy only works when customers go deeper into the AWS ecosystem. This isn’t about winning benchmark battles; it’s about creating economic gravity around where AI gets built.

The conversation also tackles the question every executive is asking: How does this compare to Nvidia? While NVIDIA continues to dominate AI innovation and experimentation, AWS is focused on industrial-scale economics—making large, repeatable training workloads cheaper, more predictable, and easier to operationalize inside its cloud.

Gary and Scott then connect the dots to real enterprise strategy, including:

• Why AI infrastructure decisions are becoming long-term financial commitments
• How custom chips influence cloud pricing power and cost curves
• The rise of multi-cloud strategies that separate AI innovation from AI economics, including the role of Oracle Cloud Infrastructure as a cost-efficient execution layer
• Why FinOps is becoming essential as AI training, retraining, and inference costs compound over time

The key takeaway for business leaders: AI advantage won’t come from simply adopting the latest models. It will come from who controls the economics of building, scaling, and evolving AI over the next decade.

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

In this episode of The Macro AI Podcast, Gary Sloper and Scott Bryan unpack one of the most consequential—but quietly introduced—AI launches to date: ChatGPT Health.

Rather than focusing on hype, the conversation starts with fundamentals. What does ChatGPT Health actually do? What systems can it connect to? How does it stay current with your health information? And how is it architected to operate safely inside one of the most regulated domains in the world?

From there, Gary and Scott explore how OpenAI has deliberately framed ChatGPT Health as a grounded, trust-first intelligence layer, designed to interpret and explain verified health data—rather than replace clinicians or generate unbounded medical advice. They discuss the technical architecture behind the platform, including interoperability, real-time contextual data assembly, and the “health sandbox” model that keeps personal data isolated and protected.

The conversation then zooms out to examine the macro implications: the end of “Dr. Google,” the shifting role of patients and clinicians, the redistribution of cognitive labor in healthcare, and the emerging governance questions around data sovereignty and AI-mediated decision-making.

Finally, the episode connects these lessons to a broader business audience—explaining why ChatGPT Health isn’t just a healthcare story, but a blueprint for how AI will move into the interpretation layer of complex, high-stakes industries everywhere.

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

As artificial intelligence moves from experimentation to large-scale deployment, the conversation about jobs is finally shifting—from speculation to evidence.

In this episode of the Macro AI Podcast, Gary and Scott unpack the most important recent research on AI and labor markets, including Vanguard’s 2025–2026 “Job Growth Paradox,” the IMF’s AI preparedness and global stability warnings, and the Roosevelt Institute’s analysis of who really captures AI-driven productivity gains.

Rather than asking whether AI will eliminate jobs, this discussion explores a more nuanced—and more urgent—set of questions:

• Why are some of the most AI-exposed roles seeing higher wages and increased hiring?
• How does AI change demand, productivity, and firm-level growth?
• Why could AI widen global and organizational inequality if leaders aren’t intentional?
• What does the shift from task execution to direction and orchestration mean for leadership, talent, and career paths?

Gary and Scott examine how AI is reshaping work at the task level, why demographics and labor scarcity matter more than most headlines suggest, and how agentic AI systems are accelerating the move toward an “economy of direction.”

The episode closes with clear, practical guidance for executives on how to think about AI not as a cost-cutting tool—but as a capacity-expansion strategy that demands new leadership choices.

If you’re a business leader trying to understand what AI really means for jobs, growth, and competitiveness in 2026, this is a conversation you won’t want to miss.

Send a Text to the AI Guides on the show!

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog