CNBC's TechCheck AI Scorecard: Ranking Public Companies

Developing an AI Scorecard

• 💡 A new AI scorecard has been developed to provide a more complete picture of how the AI trade is being placed, moving beyond just financial statements.
• 🎯 This scorecard integrates various signals including spending, adoption, financial performance, and market reaction to assess AI leadership.
• 📊 The methodology assigns weightings to different metrics, aiming to capture both technical capability and market conviction.

Public Company AI Rankings

• 🥇 Alphabet leads the public company rankings by a wide margin, demonstrating strong model capability, financials, adoption signals, and market confidence (measured by market cap change).
• ⚠️ Meta ranks second, showing a more polarized profile with high capex and weaker third-party model scores, but strong adoption and the highest revenue growth among the companies analyzed.
• ⚖️ Amazon and Microsoft are positioned in the middle, benefiting from AI's impact on cloud services, but lacking visible token share data for their AI models.
• 📉 Apple ranks last among the analyzed big five, investing the least in AI and showing the fewest visible adoption signals, though it could be a wildcard if AI plays out at the device level.

Methodology and Future Outlook

• 🔍 The scorecard primarily focuses on public AI players due to data availability, with plans to analyze private players at a later time.
• 📈 Key data sources include LLM Arena.ai for model technicality and token usage/monthly active users for adoption.
• 💬 This scorecard serves as a baseline to track how narrative, spending, and demand for AI evolve, with follow-up checks planned after updated numbers are released.