AI Trade Faces Challenges, but Phase 3 Stocks Show Promise
The artificial intelligence (AI) trade is encountering a challenging year, marked by macroeconomic volatility and headwinds in the tech sector. However, amidst these difficulties, certain AI-exposed stocks are demonstrating potential, particularly those classified as “Phase 3” by industry analysts.
Phase 3 AI stocks, defined as software companies benefiting from emerging AI technology, have shown resilience in the face of market turbulence. These stocks have experienced positive sales revisions year-to-date, with expected consensus 2026 sales revised 0.3% higher. Goldman Sachs analysts suggest that Phase 3 stocks offer better risk/reward compared to their Phase 2 counterparts.
Notable Phase 3 stocks include Palantir Technologies, with a projected sales growth of 29%, Cloudflare at 26%, and SentinelOne at 25%. Other promising companies in this category are Axon Enterprise (24% projected growth), Snowflake (23%), and CrowdStrike (22%).
In contrast, Phase 2 AI stocks, which are related to AI infrastructure, have faced more significant challenges. These stocks have seen a 0.3% decrease in consensus sales revisions, impacted by concerns in China’s tech sector and valuation issues. The Philadelphia Semiconductor index has dropped nearly 15% since mid-February, reflecting the broader struggles in this segment.
Phase 4 AI stocks, expected to benefit from AI’s labor productivity gains, have also experienced a 0.3% decrease in sales revisions. However, companies like Amazon, Cognizant Technology Solutions, and Iqvia Holdings are beginning to identify productivity benefits from AI implementation.
Goldman Sachs analysts suggest that a market reversal may require washed-out positioning or improved economic data. While potential benefits from easing tariff policies exist, uncertainty remains high in the current market climate.
As the AI trade navigates these challenges, Phase 3 stocks offer a silver lining amid a difficult period for tech trades. Industry observers continue to monitor AI efficiencies and their impact on hardware demand, as the market adapts to the evolving landscape of artificial intelligence technologies.
