An article written by Microsoft CEO Satya Nadella,

An article written by Microsoft CEO Satya Nadella—this is the kind of piece worth reading. Don't waste time on most of the AI-generated content pushed on Chinese social media.

Satya:

I have been thinking about the future direction of companies in an AI-driven economic environment.

This transformation is fundamentally different from any previous platform shift. In the past, we used digital systems to enhance human capital. Now, for the first time, we can establish a true cognitive loop between humans and digital systems. This is refreshing because it completely changes our understanding of work within an organization.

The key is not about certain digital tools or systems and how they are used, but rather about how organizations continue to learn, build intellectual property, differentiate themselves, and thrive in a world where AI models can continuously absorb and commoditize the expertise of individuals and organizations.

Every company must build what I call human capital and token capital. Human capital includes employees' knowledge, judgment, relationships, creativity, and pattern recognition capabilities, while token capital refers to the AI capabilities that a company builds and owns.

Importantly, as token capital grows, the value of human capital does not decrease—it only increases! I believe human initiative will be the driving force behind the growth of token capital. Humans set ambitious goals, connect information across different domains, build relationships, and identify the most important patterns. Without human guidance, computers will just spin in place.

This means the real opportunity is not in choosing the best model, but in building a model-based learning loop that allows human capital and token capital to compound. You can outsource a task, or even a job, but you can never outsource learning. The future of an enterprise lies in its ability to compound this learning between people and AI.

This requires a new architectural approach, where every business can build intelligent systems that improve over time while maintaining control over its intellectual property. Enterprises should be able to replace existing "general-purpose" models without losing the "company veteran" expertise embedded in their learning systems. This will be the key "test" of enterprise control and autonomy in the coming era.

Enterprises need to transform their workflows, domain knowledge, and accumulated judgment into AI systems, making them improve with every use. Private evaluations should capture whether the model is truly improving on outcomes critical to the business (not just external benchmarks!). Private reinforcement learning environments should allow models to continuously grow based on real data within the organization. Its knowledge base makes institutional memory queryable and improves the efficiency of token usage.

This loop will become the company's new intellectual property. I compare it to a hill-climbing machine. Unlike most assets, it has a compounding effect. Every improvement in workflow generates better training signals, accelerating the accumulation of the company's unique tacit knowledge. Companies that build this loop early will have advantages that are difficult to replicate, regardless of whatever new single-model capabilities emerge.

The last thing we want is for all industries and all companies to hand over their value to a few models that capture everything. If all value is concentrated in the hands of a few models, the political and economic system simply cannot tolerate it. Society will never allow the future of AI to hollow out entire industries.

Think about what happened in the first phase of globalization: outsourcing hollowed out entire industrial economies. On the surface, GDP numbers looked fine, but the offshoring of industries was real, and the consequences are still evident today. We must not let this pattern repeat in the AI era, where a few AI systems capture all the economic gains while entire industries watch their knowledge get commoditized and ultimately destroyed.

I believe our primary task must be to build a frontier ecosystem, not just a frontier model, so that value can flow broadly across every company, every industry, and every country. In this ecosystem, every organization can own a learning loop that encodes its institutional knowledge, thereby continuously accumulating its human capital and token capital.

I have held the belief since childhood that platforms can create additional value beyond what the platform itself can provide, and that every company can continuously innovate and create its own value.

When this happens, companies not only create value for themselves but also for the surrounding economy. Employees' expertise will be enhanced, their judgment integrated into replicable and scalable systems, and both the enterprise and the surrounding community will benefit.

This is how companies create value for themselves and the broader economy. And this is the stable equilibrium we should build together.