Looking at Microsoft's long-term logic from Nadella's interview, if you missed Google, don't miss Microsoft!

Recently, I watched an interview with Satya Nadella and increasingly felt that the most important aspect of Microsoft is not a 1 percentage point increase in Azure's growth rate in a certain quarter, nor the spectacular effect of a particular OpenAI launch event, but that Microsoft is undertaking something more long-term and fundamental:

It is re-engineering itself into the enterprise operating system for the AI era.

Over the past two years, whenever the market mentions Microsoft AI, the first reaction is OpenAI.

This is certainly correct. Microsoft is indeed one of OpenAI's most important partners, and OpenAI has significantly enhanced Microsoft's market imagination in the AI era.

However, the core signal revealed in Nadella's interview is:

Microsoft will not bet its entire future on OpenAI alone.

What Microsoft truly wants to do is not become a distributor for a specific large model, but to become the central control platform for the enterprise AI era.

In other words, in the future, enterprises using AI may not only use OpenAI, but also Anthropic, Gemini, open-source models, or even industry-specific models. But regardless of which model an enterprise uses at the backend, they need a unified, secure, controllable platform that integrates with their data, permissions, and workflows.

This is Microsoft's opportunity.

What does Microsoft have?

Windows, Office, Teams, GitHub, Azure, Dynamics, security products, enterprise identity systems, developer ecosystems, and enterprise customer relationships.

Individually, each of these is a product; but combined, they form the deepest network in the era of enterprise digitalization.

After the arrival of the AI era, what enterprises truly need is not a "chatbot," but an intelligent system that can be embedded into workflows, understand enterprise data, comply with permission systems, improve employee efficiency, help developers write code, assist sales in customer management, aid finance in handling reports, and support management in decision-making.

This is the system Microsoft aims to build.

In the AI era, what's most scarce is not just model capability.

Models are important, but there will be more and more models. OpenAI, Google, Anthropic, Meta, and the open-source community are all constantly catching up. In the long run, model capability may gradually become a basic competency.

The real challenge is:

Who can enter the core workflows of enterprises?
Who can gain the trust of enterprises?
Who can handle complex data permissions?
Who can seamlessly integrate with existing enterprise IT systems?
Who can make conservative clients like large corporations, governments, banks, healthcare, and insurance feel comfortable using it?

This is Microsoft's strength.

Many AI applications look impressive, but to truly enter large enterprises, having a good model is not enough.

Enterprises care about security, compliance, stability, permission management, data isolation, auditing, cost control, and system integration.

These are precisely the deepest moats in the enterprise market.

Microsoft has always been one of the most difficult companies to replace in the enterprise market.

The deeper AI goes into the enterprise space, the more apparent Microsoft's advantages become.

Currently, the market has significant disagreements over the AI capital expenditures of big tech companies.

On one hand, everyone knows AI requires computing power; on the other hand, there is concern that these companies are buying too many GPUs and building too many data centers, with insufficient returns in the end.

This concern is reasonable.

But Microsoft is different from some pure AI concept companies. Microsoft's investment in computing power is not just for storytelling, nor just for short-term Azure revenue, but to serve its vast enterprise ecosystem.

Azure needs computing power, OpenAI needs computing power, Copilot needs computing power, GitHub Copilot needs computing power, enterprise customers need computing power, and future Windows edge-cloud integration also needs computing power.

Therefore, Microsoft's AI capital expenditure is essentially paving the way in advance for the next generation of enterprise infrastructure.

In the short term, this will suppress free cash flow and increase market concerns about the return cycle.

But in the long term, if AI truly becomes the new entry point for enterprise software and cloud services, then today's capital expenditure is not just a cost, but part of the competitive moat for the next decade.

This is somewhat similar to the early days of cloud computing.

Back then, building data centers was also very expensive, and many doubted the returns. But in the end, cloud computing became one of the most important profit sources for tech giants.

Is it possible for AI infrastructure to repeat this process? I think it is possible.

Moreover, what's most commendable about Microsoft in recent years is not just catching the AI wave, but the strategic resilience of its management.

After Satya Nadella took over Microsoft, the company gradually shifted from a relatively closed, Windows-centric traditional software giant to cloud, subscription, open source, developers, and enterprise services, and now to AI.

This is not a simple business transformation, but a reshaping of organizational culture.

When many companies encounter new technological waves, they often face two problems:

One is reacting too slowly, clinging to old businesses;
The other is reacting too aggressively, losing their original advantages in pursuit of trends.

What's particularly noteworthy about Microsoft currently is that it hasn't abandoned its core business for the sake of AI, but has embedded AI into its existing core.

This is the most stable path.

Microsoft is not building AI applications from scratch, but integrating AI into Office, Teams, Windows, GitHub, Azure, security, and enterprise management systems.

It's not starting from scratch, but upgrading within its existing ecosystem.

This is also why I think Microsoft's long-term logic is relatively solid.

So, after watching Nadella's interview, my understanding of Microsoft has become clearer:

Microsoft is not the AI stock with the highest short-term volatility.
It won't surge by double-digit percentages in a single day like some semiconductor, storage, or AI concept stocks.
But Microsoft's advantages lie in its certainty, ecosystem depth, enterprise customer stickiness, and long-term compounding ability.

The most suitable strategy for this type of company is not to speculate on daily price movements, but to buy at a reasonable price and hold patiently.

If the market, due to concerns about AI capital expenditures, short-term Azure growth fluctuations, or changes in the OpenAI relationship, pushes Microsoft's price to a more comfortable level, that would actually be an opportunity long-term investors should focus on.

Ultimately, in the AI era, the companies truly worth holding long-term are not necessarily those that rise the most in the short term, but those that can turn technological waves into long-term cash flow and ecosystem barriers.

From this perspective, Microsoft remains one of the big tech companies I believe is most worth tracking long-term.

Personal opinion, not investment advice.