Financial analysts said the artificial intelligence investment boom is shifting from hardware providers toward broader AI applications and new market leaders.
This transition marks a pivotal moment for global investors as the initial surge centered on chipmakers matures. The shift suggests that the market is now looking for companies that can successfully implement AI to generate revenue rather than those that simply provide the infrastructure.
Lo Toney, managing partner at Plexo Capital, said the market is moving into the second phase of the AI trade [1]. Analysts at Goldman Sachs said the trade of the year is entering a new phase [2].
Early winners in the AI space focused heavily on hardware, particularly semiconductors. However, recent market activity suggests a diversification of interest. Jim O’Mans said Apple stock shows why the AI trade is moving beyond Nvidia [3]. This indicates a growing investor appetite for consumer-facing AI integration, and software-driven growth.
Several factors are driving this evolution. Analysts said the impact of de-globalisation and increasing energy-security concerns are forces reshaping where capital flows [2, 3]. As business models evolve, the focus is moving toward companies that can leverage AI for specific industrial or commercial gains.
Some companies are already reporting significant growth in this new environment. NIQ AI-native revenue grew 34% [4]. This growth comes as the industry explores agentic commerce products, and other advanced applications.
While the market searches for the next major leader, the scale of previous success remains a benchmark. Every AI company that has reached a $1 trillion market cap has made its investors rich [5]. Current debates among analysts now center on which firm is poised to be the next to reach that valuation milestone [5, 3].
“The market is moving into the second phase of the AI trade.”
The shift to a 'second phase' indicates a transition from the speculative infrastructure build-out to a value-realization stage. Investors are no longer satisfied with the existence of AI capabilities; they are now prioritizing proven monetization and the integration of AI into existing product ecosystems. This creates a higher risk profile for companies that cannot demonstrate clear revenue gains from their AI investments.



