Major tech companies are investing in their own customers, creating a self-reinforcing loop of capital that inflates demand and valuations. This dangerous practice mirrors the vendor financing tactics of the dot-com era (e.g., Nortel), which led to a systemic collapse when external capital eventually dried up.

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.

The current AI spending spree by tech giants is historically reminiscent of the railroad and fiber-optic bubbles. These eras saw massive, redundant capital investment based on technological promise, which ultimately led to a crash when it became clear customers weren't willing to pay for the resulting products.

History shows pioneers who fund massive infrastructure shifts, like railroads or the early internet, frequently lose their investment. The real profits are captured later by companies that build services on top of the now-established, de-risked platform.

After a decade of abundant "growth capex" building new infrastructure, the economic pendulum is swinging towards "maintenance capex." This creates a massive, overlooked opportunity for technologies that service existing assets, like predictive software, acoustic sensors, and remote repair robots.

Building software traditionally required minimal capital. However, advanced AI development introduces high compute costs, with users reporting spending hundreds on a single project. This trend could re-erect financial barriers to entry in software, making it a capital-intensive endeavor similar to hardware.

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.

The AI investment case might be inverted. While tech firms spend trillions on infrastructure with uncertain returns, traditional sector companies (industrials, healthcare) can leverage powerful AI services for a fraction of the cost. They capture a massive 'value gap,' gaining productivity without the huge capital outlay.

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.