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.

Unlike cloud or mobile, which incumbents initially ignored, AI adoption is consensus. Startups can't rely on incumbents being slow. The new 'white space' for disruption exists in niche markets large companies still deem too small to enter.

Satya Nadella predicts that SaaS disruption from AI will hit "high ARPU, low usage" companies hardest. He argues that products like Microsoft 365, with their high usage and low average revenue per user (ARPU), create a constant stream of data. This data graph is crucial for grounding AI agents, creating a defensive moat.

Despite attempts to articulate an AI strategy, the telecom sector is largely seen as a non-participant in the current AI boom. From a stock market perspective, investors are selling positions in telcos to finance investments in high-growth AI companies, effectively making the telecom industry an involuntary funding source for the trend.

AI is making core software functionality nearly free, creating an existential crisis for traditional SaaS companies. The old model of 90%+ gross margins is disappearing. The future will be dominated by a few large AI players with lower margins, alongside a strategic shift towards monetizing high-value services.

AI favors incumbents more than startups. While everyone builds on similar models, true network effects come from proprietary data and consumer distribution, both of which incumbents own. Startups are left with narrow problems, but high-quality incumbents are moving fast enough to capture these opportunities.

Anthropic is making its models available on AWS, Azure, and Google Cloud. This multi-cloud approach is a deliberate business strategy to position itself as a neutral infrastructure provider. Unlike competitors who might build competing apps, this signals to customers that Anthropic aims to be a partner, not a competitor.

The excitement around AI capabilities often masks the real hurdle to enterprise adoption: infrastructure. Success is not determined by the model's sophistication, but by first solving foundational problems of security, cost control, and data integration. This requires a shift from an application-centric to an infrastructure-first mindset.

Microsoft's plan to train 20 million people in India is a strategic move to create a massive, captive customer base for its Azure cloud services. This transforms a passive infrastructure investment into an active market-shaping strategy, ensuring demand for the very services they are building out.