AI Fear and Software Stock Volatility: Sarah Hunt on Market Risks

Market Volatility and AI Concerns

• 📈 January and February 2026 have seen more volatility than anticipated, following three strong previous years.
• ⚠️ Investors are concerned about business risks posed by AI, leading to a rotation out of software stocks.
• 💡 The fear surrounding AI disruption is significant and tends to "feed on itself", making it difficult to predict outcomes.

Earnings as a Key Indicator

• 📊 Earnings are considered the most crucial factor for markets currently, with Google's report serving as an important bellwether.
• 📉 Mixed earnings results and guidance that isn't exceptionally strong are leading to easy disappointments in the market.
• 🎯 Meeting expectations is not enough when investors are increasingly worried about AI-driven disruption.

AI's Impact on Software and Data Companies

• 🧩 While there are legitimate concerns about AI's impact on software and data companies, the "huge ecosystems" around these businesses may provide a cushion.
• ❓ It's unclear which companies will win or lose in this new era, similar to the early days of the internet disruption.
• 🔍 The ease of accessing data through AI tools raises questions about business models, though the long-term effect is not yet clear.

Understanding AI Disruption

• 🤖 The current AI disruption is not directly comparable to the internet disruption, as each technological shift has unique characteristics.
• 💬 AI tools can be used for early research and information gathering, but the quality of data and the need to verify sources remain critical.
• ⚡ AI can increase productivity by helping to weed out information and pull data from multiple sources faster.

Future Market Risks

• 📈 The primary risk for markets in 2026 is expected to be earnings, particularly any signs of a downturn or negative changes in growth rates.
• ⚠️ Even small negative shifts in earnings or revenue can trigger significant market reactions, as seen with some software companies.