Investors Weigh AI's Momentum Amid Tech Sector Turbulence and Capex Concerns

The recent turbulence in the tech sector has shifted investor focus on whether the AI theme, epitomized by companies such as NVIDIA, still retains its upward momentum. As the U.S. equities enter a phase of volatility following a rapid rebound, there is growing speculation about the sustainability of AI-related investment benefits in light of anticipated capital expenditure (Capex) growth peaking by 2026.

Concerns have been rising over the past fortnight about the potential plateauing of AI-related Capex by 2026. This concern is fueled by factors such as the uncertain return on investment from AI deployment, doubts over companies' ability to continuously fund AI Capex, and flatlining GPU sales to China by firms like NVIDIA and AMD. These concerns have been reflected in NVIDIA's lackluster stock performance post-earnings release.

Despite these apprehensions, fund managers remain optimistic about the AI investment theme. Reports suggest that hyperscale companies' AI Capex has surpassed market expectations. Still, any slowdown in growth could pose risks to stock valuations, making the upcoming third and fourth-quarter earnings seasons pivotal.

The evolution of AI investment can be mapped into four distinct stages. The first stage, 'Compute-Driven,' sees NVIDIA reaping benefits due to its GPU dominance as AI's structural engine. The second, 'Infrastructure Expansion,' stage requires tech giants and cloud providers to enhance AI data centers and compute networks, benefiting semiconductor and cloud companies along with networking equipment firms.

In the third stage, 'Revenue Enablement,' AI models gradually embed into products and services, thus creating new revenue sources for software giants and internet platforms. Although interest in this stage is currently limited, its potential for generating income is noteworthy.

Finally, the 'Productivity Release' stage highlights the democratization of AI's benefits across traditional sectors such as office collaboration and industrial automation. However, the market seems more keenly interested in the narratives of the first two stages, particularly given the historical context of September being the weakest month for U.S. stocks. In the short term, capital spending cycles and hardware demand remain the primary drivers, but the long-term impact of AI on various industries' productivity will ultimately determine its broader market and economic implications.