AI Is Restructuring Production Relations: From Human-Human to Human-Machine

AI Is Restructuring Production Relations

Since 2026, I’ve observed a profound trend: AI isn’t just boosting productivity—it’s fundamentally restructuring production relations.

If you’re an employee at a major tech company, how do you view AI coding? Will it replace your job, or help your company become more efficient with fewer people? If you’re an investor in tech stocks, how do you view layoffs in the AI era? As AI boosts productivity, it reduces the need for certain roles. If you were capital itself, how would you see AI?

What is capital? It’s wealth with self-appreciation consciousness. In the game of capital, AI represents both productivity and production relations.

I believe the perspective of capital is the most objective and authentic—because wealth doesn’t lie. Capital, capitalists, and those who hold capital all occupy core positions in production relations. So how will these upstream powerholders understand and navigate changes to production relations?

Today, we’re witnessing this historic transformation.

Theoretical Foundations of Production Relations

In Das Kapital, Marx identified three aspects of production relations: ownership of means of production, the position and mutual relations of people in production, and the distribution of products. Today we focus on the second aspect—people’s position and mutual relations in production.

In his 1937 essay The Nature of the Firm, Ronald Coase proposed that firms exist because organizing production internally reduces market transaction costs. Firms are essentially “internalized” collaboration mechanisms.

From Taylor’s scientific management to Toyota’s lean production to Google’s OKRs, organizational theory has always revolved around one core question: How to make human collaboration more efficient. But no matter how we optimize, human collaboration always involves communication costs, coordination costs, trust costs, and supervision costs. These costs constitute organizational “friction.”

Traditional Production Relations: The Complex Human Network

In traditional production relations, production activities primarily rely on complex human collaboration.

2.1 The Complex Collaboration Network

A typical enterprise organization is a complex collaboration network: product managers communicate requirements with designers, designers discuss implementation with developers, developers confirm quality standards with testers, and departments depend on and constrain each other.

This collaboration network is characterized by tight coupling and low cohesion: everyone’s work depends on others, while also needing to handle extensive cross-domain coordination.

2.2 The Hidden Burden of Collaboration Costs

Having worked at Tencent and Meituan for 15 years, I deeply understand this. A seemingly simple feature might require 3 cross-departmental meetings, 5 email confirmations, 10 instant messaging exchanges, and countless iterations. This “coordination work” often takes more time than the actual “production work.”

Statistics show that knowledge workers spend an average of 40% of their time on coordination, communication, and meetings—not on actual value creation.

Production Relations in the AI Era: Human-Machine Synergy

Now AI is changing everything.

3.1 From “Human-Human” to “Human-Machine”

AI is becoming a new subject in production activities. Increasingly, production processes no longer require direct human collaboration, but are completed through human-machine interaction.

Case 1: AI Programming Assistants Before: Developers needed to confirm requirements with product managers, consult technical solutions with architects, and understand test cases with testers. Now: A developer tells AI “help me implement a user login module” and AI generates the code directly.

Case 2: AI Content Creation Before: Editors needed to discuss topics with authors, visuals with designers, and timelines with operations. Now: One person working with AI can complete topic selection, writing, visuals, and layout.

3.2 New Production Relations: Loose Coupling, High Cohesion

This transformation brings profound changes to production relations:

Loose coupling means work no longer depends excessively on others—most collaboration can be completed through AI. High cohesion means people can focus on what they do best, leaving repetitive and coordination work to AI.

The Deep Logic Behind Diminishing Human Relations

The diminishing of human production relations has several underlying logics:

4.1 AI Reduces “Coordination Costs”

AI is essentially an extremely low-cost collaboration partner: no meetings needed, no communication required, no rest, no emotions, always available. When AI’s coordination costs approach zero, the very foundation of traditional enterprise organizations is challenged.

4.2 AI Breaks “Information Asymmetry”

In traditional production relations, different people hold different information, leading to friction in collaboration. But AI can integrate all information, provide a global perspective, eliminate information barriers, and give everyone complete information.

4.3 AI Restructures “Value-Creation Units”

Traditional value-creation units were “teams” or “departments.” In the AI era, value-creation units are shifting toward “individual + AI.” One person plus AI can do the work of an entire team.

Changes We’re Witnessing

5.1 Flattening of Organizational Structures

More and more companies are simplifying their organizational structures and reducing middle management—because AI can handle extensive coordination, supervision, and decision support work.

5.2 The Rise of Freelancers

Data from platforms like Upwork and Fiverr shows that the number of freelancers has grown by 200% over the past five years. One person plus AI can provide services that previously required an entire company.

5.3 Transformation of Work Methods

Remote work, asynchronous collaboration, and flexible hours are becoming the new normal—AI plays a crucial supporting role.

Future Outlook: Toward Human-Machine Symbiosis

We’re moving toward a production relationship of human-machine symbiosis: machines handle repetitive work, computational work, coordination work, and information processing; humans handle creative work, value judgment, strategic decisions, and human connections.

In this production relationship, direct human collaboration will decrease, but deep human connections may become even more important. We no longer collaborate to “get things done”—we connect to “create greater value.”

Summary

AI is fundamentally restructuring production relations: from theory to practice, this transformation is supported. The new production relations feature loose coupling and high cohesion, and human production relations are gradually diminishing.

This isn’t about AI replacing humans—it’s about AI becoming humanity’s most powerful partner. As Peter Drucker said: “The essence of management is to unlock human goodness and potential.” AI brings us one step closer to this goal.

About Me

I’ve worked at NetEase Games, Baidu, Tencent (8 years), and Meituan (nearly 7 years), leading large R&D projects and managing teams of over 100 engineers.

I’m currently building a startup in AI.

Why? Because the world runs on uncertainty—staying in corporate roles too long breeds addiction to certainty. AI entrepreneurship is like setting sail into uncharted waters.

Feel free to reach out: HummingbirdLabs@outlook.com.