Goldman Sachs: AI Funding Fears Overstated, Model Volatility Expected

AI Funding Landscape

• 💡 The aggregate spend needed for AI over the next couple of years is estimated between $700 billion to $1 trillion.
• 🎯 A significant 90% of this spend is funded by operating cash flows, with only about 10% coming from debt.
• 🔑 Most of the debt issued is by entities like Meta, which has a better credit rating than the US government.
• ⚠️ Concerns about companies like Coreweave and Oracle represent a small fraction of the overall funding picture, potentially drowning out the larger, stable funding story.

Demand and Supply Chain Issues

• 🚀 Companies like Coreweave and Oracle are not facing a demand issue for their AI infrastructure.
• 🚚 Instead, they are experiencing supply chain backup issues, which is contributing to current concerns.

Frontier Model Volatility

• 🧠 The AI market is experiencing model volatility, with leadership perceptions changing rapidly.
• 📈 Initially, Meta's Llama was seen as dominant, followed by OpenAI.
• 📊 More recently, Google's Gemini has gained significant traction, leading to a substantial market cap increase for Google.
• ⚠️ This volatility is expected to persist, especially with new AI models trained on Blackwell hardware set to launch in Q1 2026.
• 📌 Companies heavily leveraged to OpenAI's ecosystem may face increased scrutiny and potential pressure.