In our Q2 2026 Commentary, we address the main drivers behind market performance and macroeconomic developments, through five investor questions shaping today’s landscape.
1. Why do KAR portfolios have little exposure to some of the best-performing areas of the market, and how does that reflect our discipline?
Recent market leadership has been driven by semiconductors, high-beta names, and non-earning companies—businesses that typically fall outside the KAR quality-focused framework. While these companies are benefiting from near-term AI spending, we believe their dependence on the continuation of the cycle reinforces the importance of focusing on durable earnings and long-term compounding.
2. Does this environment represent a temporary dislocation or a more durable shift in market behavior?
Today’s market is defined by narrow leadership and rapid rotations across AI beneficiaries, as investors move from one perceived bottleneck to the next. At the same time, the leading platform companies are increasingly competing more directly with one another in a way they haven’t historically. The combination of shifting leadership and rising capital commitments reflects a market still evolving, rather than one with clearly established long-term leaders.
3. Does the AI investment cycle resemble past innovation cycles, or is it structurally different?
While the current AI buildout shares many characteristics of past capital cycles, a key difference is the concentration of spending in assets like advanced semiconductors that depreciate much faster than traditional infrastructure. This dynamic, combined with growing use of external funding and the potential for both large frontier models and smaller, more efficient systems, makes the durability and returns of this cycle less certain than prior capex booms.
4. Is the swing in index EPS driven by a narrow group of AI beneficiaries? What does that mean for quality?
Quality strategies have lagged in the current environment, as market leadership has been driven by a relatively small group of AI-related beneficiaries delivering exceptionally strong near-term growth. At the same time, many quality companies continue to generate solid earnings and maintain competitive positions, but have not kept pace with the magnitude or speed of gains tied to the AI buildout cycle.
5. How are companies actually using AI to improve efficiency and productivity?
Companies are already seeing tangible gains from AI, particularly in marketing efficiency, software development, and operational optimization. While less visible than infrastructure spending, these use cases represent steady, compounding drivers of long-term value creation.
You can explore these themes further in Episode 316 of our stock market podcast, Kaynecast.
