In 2022, investors punished Meta's stock for its Reality Labs CapEx. Today, the market applauds even larger AI-related spending (66% of MAG-5's operating cash flow). This signals a fundamental belief that AI investments translate directly to tangible near-term earnings, unlike speculative bets like the Metaverse.

While high capex is often seen as a negative, for giants like Alphabet and Microsoft, it functions as a powerful moat in the AI race. The sheer scale of spending—tens of billions annually—is something most companies cannot afford, effectively limiting the field of viable competitors.

Tech giants are shifting from asset-light models to massive capital expenditures, resembling utility companies. This is a red flag, as historical data shows that heavy investment in physical assets—unlike intangible assets—tends to predict future stock underperformance.

Eclipse Ventures founder Lior Susan shares a quote from Sam Altman that flips a long-held venture assumption on its head. The massive compute and talent costs for foundational AI models mean that software—specifically AI—has become more capital-intensive than traditional hardware businesses, altering investment theses.

Unlike prior tech revolutions funded mainly by equity, the AI infrastructure build-out is increasingly reliant on debt. This blurs the line between speculative growth capital (equity) and financing for predictable cash flows (debt), magnifying potential losses and increasing systemic failure risk if the AI boom falters.

Major tech companies view the AI race as a life-or-death struggle. This 'existential crisis' mindset explains their willingness to spend astronomical sums on infrastructure, prioritizing survival over short-term profitability. Their spending is a defensive moat-building exercise, not just a rational pursuit of new revenue.

For the first time in years, leading-edge tech is incredibly expensive. This requires structured finance and massive capital, bringing Wall Street back to the table after being sidelined by cash-rich tech giants. The chaos and expense of AI create a new, lucrative playground for financiers.

A new risk is entering the AI capital stack: leverage. Entities are being created with high-debt financing (80% debt, 20% equity), creating 'leverage upon leverage.' This structure, combined with circular investments between major players, echoes the telecom bust of the late 90s and requires close monitoring.

Massive AI capital expenditures by firms like Google and Meta are driven by a game-theoretic need to not fall behind. While rational for any single company to protect its turf, this dynamic forces all to invest, eroding collective profitability for shareholders across the sector.