Podcast Summary: AI Exchanges: How Tech Giants Are Navigating the AI Landscape

Podcast: Exchanges
Host: Goldman Sachs (Allison Nathan and George Lee)
Guest: Eric Sheridan (Co-business Unit Leader, Technology, Media & Telecommunications, Goldman Sachs Research)
Date: May 7, 2025

Overview

This episode delves into how major US technology companies are adapting to and investing in the accelerating rise of artificial intelligence (AI). Hosts Allison Nathan and George Lee, together with guest Eric Sheridan, provide a research-driven tour of the current AI landscape—highlighting capital expenditure trends, the evolution from infrastructure to application layers in AI, investor sentiment, the impact of tariffs, and the competitive dynamics among tech giants. The discussion draws on recent earnings reports and market data, aiming to contextualize today's rapid AI advances and their implications for stakeholders.

Key Discussion Points and Insights

1. The Current Status of Tech Giants in AI

[00:27–02:24]

• Recent earnings calls reveal tech giants (Meta, Alphabet, Amazon) are doubling down on AI capital expenditure, showing commitment at least through 2025. They are largely "supply constrained"—demand for AI massively outpaces their capacity.
• Quote:
  “Andy Jassy...asked what inning are we in in this whole thing? And he said we are first batter, second strike of the first inning. ...a commentary on the novelty of this wave, the amount of territory ahead of us.” —George Lee [00:42]

2. Framework: The Three Layers of Generative AI Evolution

[02:24–04:40]

• Sheridan outlines a three-phase framework, marking this as the third major computing shift (after desktop and mobile) now termed "Web 3.0."
  • Infrastructure Layer: Building and scaling large language models.
  • Platform Layer: Platforms leveraging trained models.
  • Application Layer: End-user products in personal and enterprise spheres.
• AI model improvements are rapid but AGI (Artificial General Intelligence) remains distant. Practical consumer applications (e.g., Gemini, ChatGPT) have evolved significantly in short order.
• Quote:
  “We're in the very early innings of this Web 3.0 phenomenon...” —Eric Sheridan [02:24]

3. Acceleration and Time Dilation of Change

[04:40–05:39]

• Unlike prior shifts that took years to mature, AI adoption is happening much faster; e.g., ChatGPT reached 800M users in 2.5 years, with Gemini pre-installed on Samsung phones globally.
• Quote:
  “This time dilation phenomenon of how change seems to be accelerating in this way versus many of the others...” —George Lee [05:39]

4. Capital Expenditure (CapEx) Trends and Duration

[05:39–07:56]

• Tech companies are at peak capital intensity; Meta's capex is ~40% of revenue. Expect high growth this year, tapering to mid-teen percentages next year. Future capex depends on proof of value in AI applications.
• Capex planning is resilient; companies learned from the financial crisis not to pull back during downturns. Capex is protected longer than other costs (like headcount/marketing), even in a volatile macro environment.
• Quote:
  “Given the sheer number of players investing both offensively and defensively at AI, I think this spend will get protected for a little longer than the macro environment might influence it.” —Eric Sheridan [07:56]

5. Tariffs—Impact and Nuances

[07:40–09:25]

• Tariffs can increase costs for hardware components, affecting capex without necessarily altering spend plans.
• Quote:
  “Parts and widgets...coming from other places of the world that have to be shipped here...would be subject to tariffs. Even if you don't change the rate of spend or the capacity...the input cost can go up.” —Eric Sheridan [09:25]

6. AI as a Competitive Edge—Internal Productivity & Customer Value

[09:45–11:33]

• AI is driving internal productivity and user engagement more than is often recognized. At Meta, the first four of five strategic pillars focus on internal efficiency, automation, and adoption acceleration via AI. Google sees similar internal benefits.
• AI-driven advertising automation yields measurable efficiency, boosting return on ad spend.
• Quote:
  “Advertising is becoming more efficient, return on ad spend is going up and then there's more dollars to spend...” —Eric Sheridan [10:10]

7. The Future of Search and Chatbots

[11:33–13:41]

• Despite fears that chatbots would cannibalize search (and hence Google), actual search volumes remain robust; user queries to computers are at all-time highs. Human behavior is slow to change at scale.
• Quote:
  “The number one thing that has happened since ChatGPT emerged...is, is human beings are querying computers at a higher rate than they ever have. ...The monetization...still resides predominantly with Google.” —Eric Sheridan [12:07]
• Consumer habits change slowly—most users upgrade devices only every few years, not at the pace of industry hype.

8. Investor Sentiment: Cycles and Current Focus

[14:23–17:13]

• The narrative has shifted through phases: initial AI euphoria, skepticism, new questions about the sustainability and ROI of capex, and now, distraction due to tariff concerns.
• Recent investor focus is on the enterprise/cloud AI segment (AWS, Google Cloud, Azure) rather than end-user applications, since cloud revenue growth is visible and directly attributable to AI investment.
• Quote:
  “The workloads and the enterprise dynamic is where investor focus has heavily skewed. ...the broader AI narrative has been disrupted by the tariff talk in the market.” —Eric Sheridan [14:53]

9. Key Lessons from Prior Technology Cycles

[17:17–19:54]

• Differences:
  • Tech leaders are trading at reasonable or even below-market multiples—unusual during a tech revolution.
  • Incumbents are not being displaced; rather, their financial scale funds ongoing, massive investment ($250B+ annually across Amazon, Alphabet, Meta).
• The tension: Investors remain impatient—few think long-term, most focus on changes over the next few quarters.
• Quote:
  “The biggest companies almost living in fear of being disrupted and deploying capital to play as much offense as they're playing defense...” —Eric Sheridan [17:44]

10. What’s Next—Fine Print for Investors

[19:54–20:50]

• The next frontier is which application-layer products will succeed. Foundational models and platforms are mostly set; unique, outsized returns will likely stem from unforeseen AI applications, much like Uber and Airbnb previously upended their markets.
• Quote:
  “Sometimes the application layer is where the most outsized return and the most unique differentiation of change of behavior actually takes place.” —Eric Sheridan [20:00]

Notable Quotes & Memorable Moments

| Timestamp | Speaker | Quote | |-----------|---------|-------| | 00:42 | George Lee | "We are first batter, second strike of the first inning." (Andy Jassy) | | 02:24 | Eric Sheridan | "We're in the very early innings of this Web 3.0 phenomenon." | | 05:39 | George Lee | "This time dilation phenomenon of how change seems to be accelerating..." | | 07:56 | Eric Sheridan | "Given the sheer number of players...I think this spend will get protected for a little longer..." | | 09:25 | Eric Sheridan | "Parts and widgets...would be subject to tariffs...the input cost can go up." | | 10:10 | Eric Sheridan | "Advertising is becoming more efficient, return on ad spend is going up..." | | 12:07 | Eric Sheridan | "The number one thing...since ChatGPT emerged is, is human beings are querying computers at a higher rate..." | | 17:44 | Eric Sheridan | "The biggest companies almost living in fear of being disrupted and deploying capital to play as much offense as they're playing defense..." | | 20:00 | Eric Sheridan | "Sometimes the application layer is where the most outsized return and the most unique differentiation of change of behavior actually takes place." |

Structured Timestamps (for Navigation)

• [00:27] — State of tech giants, investor perspectives
• [02:24] — Generative AI layers and where we are now
• [04:40] — Rapid pace of AI adoption vs. previous shifts
• [05:39] — CapEx, investment cycle, and durability
• [07:40] — Tariffs: immediate vs. input costs
• [09:45] — Internal productivity and ad automation
• [11:33] — Google, the future of search, and chatbots
• [14:23] — Investor sentiment, phases, and priorities
• [17:44] — How today’s cycle compares to history, incumbent dominance
• [19:54] — The application layer as the site of breakthrough value

Takeaways

• Capex remains a strategic priority for tech giants, even amid macro and trade volatility.
• Application-layer breakthroughs will determine the long-term winners of the AI age.
• Investor focus has shifted from foundational models to cloud/enterprise revenues; turbulence in sentiment is shaped by both tech progress and policy headlines.
• Incumbents are evolving, not retreating, harnessing scale to defend and extend their positions—contrasting with past tech revolutions where newcomers displaced leaders.
• Consumer behavior is sticky, not easily disrupted, and actual behavioral changes will take years, not months.

This episode offers a grounded, tactical look at how the tech titans are investing, deploying, and thinking strategically about AI, blending a data-driven approach with a long-term perspective on industry transformation.