From Connection Information to Organizational Action: The Underlying Logic of Agent Economic Growth
Intelligence has reconstructed the decision-making power of economic activities, shifting from a human-centered model to the joint participation of humans and agents: humans only need to be responsible for setting goals, defining boundaries and making key confirmations, while agents are responsible for acquiring information, comparing decisions, organizing resources and coordinating communication. As a result, the functions, structure and boundaries of the market will all change.
Over the past 20+ years, the most important contribution of the Internet is to connect information and realize efficient matching between supply and demand. It makes it easier for consumers to find goods and services, enables enterprises to reach customers more efficiently, and also gives rise to a number of enterprises with global influence.
Today, agents are pushing digitalization to a new stage. They are not only answering questions and matching information, but also understanding human intentions, breaking down tasks, invoking tools, coordinating resources, organizing actions, and completing tasks autonomously.
Looking back at all previous technological revolutions, major technological breakthroughs will spawn new business models and profoundly reshape the market structure and landscape.
Entering the agent era, reducing transaction costs remains the core of market development. What we need to think about is: when the process of value creation and value exchange shifts from being human-centered to the joint participation of humans and agents, how will the market structure and landscape change, what are the core market frictions and transaction costs that need to be addressed, how can enterprises find new role positioning and value moats, and how can technological potential be converted into economic increments and broader social welfare.
Agents Reconstruct Decision-Making Power
In the past, the Internet organized a large amount of information, but humans were still the main body of decision-making and action. Agents have reconstructed the decision-making power of economic activities, shifting from a human-centered model to the joint participation of humans and agents: humans only need to be responsible for setting goals, defining boundaries and making key confirmations, while agents are responsible for acquiring information, comparing decisions, organizing resources and coordinating communication. As a result, the functions, structure and boundaries of the market will all change.
First, the unit of commercial activities has shifted from the transaction of goods and services to task transaction, and the function of the market has shifted from organizing information to organizing actions.
In the past, to arrange a business trip, users needed to buy air tickets, book hotels and arrange transportation separately; in the future, they may only need to propose "arrange an efficient, comfortable business trip that does not exceed the budget", and the agent can coordinate multiple services to complete the task.
In enterprise operation, agents can also call data, tools and professional services around goals such as reducing supply chain costs and conducting market research, and organize a complete action process. What users buy is no longer just goods and services, but task results formed around specific goals; merchants' operations will also be further upgraded from providing individual SKUs to delivering complete solutions.
Second, the market structure has evolved from a stable two-sided market to a dynamic multi-sided action network.
Internet platforms mainly connect consumers and merchants, forming a relatively stable two-sided market. In the agent economy, a single task may connect user agents, merchant agents, model manufacturers, developers, data and tool service providers, payment institutions and other professional agents at the same time.
The objects of market transactions include not only physical goods and services, but also digital resources such as models, data, tools and professional capabilities. Different subjects are dynamically connected, divided and cooperated around specific tasks, and continuously decomposed and reorganized as tasks change. The market has transformed from a relatively stable supply-demand connection to an action network with multi-party participation.
Third, the digital boundary of the market has been further broadened, shifting from consumer Internet to a broader industrial Internet.
An important reason for the rapid development of the consumer Internet is that goods and services are relatively standardized, which is easy to display, compare, pay for and evaluate. However, industrial activities such as enterprise procurement, supply chain collaboration, legal compliance, software development and professional consulting require understanding complex backgrounds, handling multiple constraints and coordinating multiple subjects, which have long faced high digitalization thresholds.
Agents can understand natural language goals, call different systems and professional capabilities, so that complex services that were difficult to standardize in the past are gradually decomposed into discoverable, callable, combinable and verifiable action processes, promoting digitalization to further enter the in-depth scenarios of enterprise production and operation and industrial chain collaboration.
Core Market Friction Turns to the Credibility of Actions
Agents systematically reduce the costs of search, negotiation and contracting, and improve the efficiency of supply-demand matching, but also bring new problems — how to trust the actions of agents.
When more and more consumption, production and operation activities are handed over to agents for execution, the principal-agent relationship becomes the basic structure of microeconomic operation. How to make the actions of agents credible has become the most core and critical market friction that needs to be solved in the agent economy.
The potential principal-agent friction brought by agents includes two levels.
First, the principal trust between humans and agents, that is, whether humans can trust that agents accurately understand the goals and act faithfully and diligently within the scope of authorization.
When people express their needs in natural language, they can usually only describe the general goals, and it is difficult to exhaust all conditions. For example, "select the most suitable supplier" may simultaneously involve price, quality, delivery stability, compliance risk and long-term partnership behind it. Agents need to make independent judgments in places that are not clearly stated, which may lead to intention understanding deviation and independent decision-making deviation, and even exceed the real expectations of the principal in terms of budget, data usage or transaction objects.
Second, the trust problem on the action chain formed between agents.
When an agent executes a task, it may further call other agents, models, data and tools to form a continuous A2A delegation. The judgment deviation of the previous link may be continuously amplified along the task chain, and each task decomposition and permission transfer may also blur the original authorization boundary, which eventually leads to a larger synthetic deviation. Once a problem occurs, it is also difficult to determine which link or links the problem occurs in. Therefore, what the agent economy needs to solve is not only whether a single agent is credible, but also whether the entire action chain can be observed, verified and held accountable.
The principal-agent relationship extends from between humans to between humans and machines, and between machines and machines, completely changing the foundation of trust building. The traditional way of building trust relying on contract constraints, result incentives, supervision mechanisms and reputation effects is difficult to apply, because agents do not have the ability to independently assume legal responsibility, nor do they have independent personality and moral consciousness, and their high-speed operation characteristics make real-time supervision more difficult. Therefore, the credible action of agents requires a new set of governance mechanisms and rules covering pre-event, in-event and post-event stages.
Pre-event, an identity and authorization mechanism needs to be established. The identity mechanism should clarify who the agent acts for, who creates it, and who authorizes it; human natural language intentions need to be converted into permission rules that agents can execute, and through a certain authorization mechanism, it should be clarified which goods and services the agent can trade, which resources to call, how much budget to use, whether it is allowed to continue to delegate to other agents, and which key links must obtain human reconfirmation.
In-event, transaction rules and process verification mechanisms need to be established. The actions of agents cannot only rely on the autonomous judgment of the model, but should convert service conditions, delivery standards, acceptance rules and payment conditions into machine-readable and automatically executable rules. Whether the task is completed as required, whether data and tools are called as agreed, and whether the payment conditions are met, all need to form verifiable states and certificates in the action process.
Post-event, a behavior audit and correction mechanism needs to be established. When the agent deviates from the goal, exceeds the authority or triggers an abnormal transaction, the system should be able to suspend the action in a timely manner and transfer it to manual processing according to the risk level. After performance disputes or actual losses occur, it is also necessary to be able to identify the problematic links along the task and transaction records, and clarify the responsibilities of relevant subjects.
Looking forward to the future, the agent's identity system, authorization mechanism, secure payment and dispute handling will not only be the back-end capabilities of the market, but also the governance hub of the entire agent network, undertaking the function of converting economic intentions into executable transactions and supporting the operation of the agent credible action network.
Traffic Logic Weakens, Trust Logic Rises
Changes in transaction costs will not only change the core problems that the market needs to solve, but also reshape the way enterprise boundaries and scale effects are formed. The external transaction of the agent system will shift from the topology-dominated mode to the throughput-dominated mode. The coordination cost mainly increases with the growth of task execution volume, rather than the growth of the number of connected nodes, and the decline rate of external transaction cost is much faster than that of internal coordination cost. The result drives enterprises to expand in scale and move from closed integration to more open professional collaboration.
At the same time, as credible action becomes the new core market friction, the focus of enterprise competition will gradually shift from competing for traffic entrances to building connections and trust in the agent ecosystem.
First, the enterprise boundary shifts from closed integration to open invocation, and the division of labor will be further deepened. According to Coase's enterprise theory, whether a capability is provided internally by the enterprise or obtained externally through the market depends on the comparison of internal organization cost and external transaction cost.
In the Internet era, in order to reduce the communication and coordination costs across subjects, enterprises often tend to incorporate more businesses and services into their own systems, forming large platforms or super Apps. Agents can actively discover, compare and invoke external capabilities, making models, data, tools, professional knowledge and business processes become machine-identifiable and combinable market supplies.
Enterprises no longer need to independently build all the capabilities required to complete a task, but can dynamically organize external resources around specific goals; their own advantageous internal capabilities can also be encapsulated as services for other enterprises and agents to invoke.
In the future, the competitiveness of an enterprise will not only depend on how many resources it owns internally, but also on how effectively it can organize external capabilities, including how many Agents it can orchestrate, how many APIs it can invoke, and how much data and tools are available to jointly complete tasks.
Second, demand entrances are more diversified, supply is more migratable, and the advantages of super Apps are significantly weakened. In the Internet era, people need to enter specific Apps to search and select services, so platforms and enterprises compete for people's attention, stay time and traffic entrances.
In the agent era, people do not need to enter each platform to find services separately, but are represented by agents; demand does not necessarily only select specific Apps, but can be initiated from multiple ends such as mobile phone systems, intelligent terminals, enterprise office systems and various professional agents. At the same time, goods and services will gradually form machine-readable expressions, and goods, services and digital resources can be discovered and invoked by different agents.
Traffic may still be important, but traffic is no longer the only bridge connecting demand and supply. The focus of enterprise operation will gradually shift from how to keep users and services in their own system to how to make their own goods, services and professional capabilities accurately understood, actively selected and conveniently invoked by more agents.
Third, the scale effect will not disappear, but will shift from traffic scale to agent ecosystem. Every time an agent performs a complex task, it needs to carry out model reasoning, data invocation, resource coordination and result verification, and different industrial scenarios have great differences in professional knowledge, business processes and responsibility requirements.
Therefore, agent services for specific tasks do not necessarily replicate the growth mode of Internet platforms with continuously decreasing marginal costs, and the application and performance layer may present a more specialized and vertical development pattern. But at a broader ecosystem layer, the connection and collaboration between agents still have obvious network effects. The richer the agents, merchants and professional supplies that an ecosystem can connect, the more types of tasks it can support, and the greater its value to market participants.
Credible action will become the key to the ecosystem forming network effects. The value of an ecosystem not only depends on how many agents and professional supplies are connected, but also on whether these subjects can collaborate based on common identity, authorization, payment, verification and responsibility rules.
The more market subjects that accept the credible rules, the lower the cost for agents to establish connections and complete transactions; the addition of more participants will further enrich the supply, expand scenarios and enhance ecosystem value. The scale effect thus gradually shifts from user quantity and traffic accumulation to ecosystem synergy formed by agent scale, professional supply network and credible transaction rules.
The agent ecosystem should not be a new entrance closed and controlled by a few enterprises, but an open collaborative network composed of multiple demand entrances, multiple types of professional supplies and common credible rules. Different enterprises can play different roles in it: some are closer to the real intentions of users and enterprises, some have profound industrial knowledge and professional supplies, and some provide basic capabilities such as identity, payment, verification and audit.
In the future, enterprises do not necessarily have to become agent platforms, but need to find their own positions in the action network. Long-term value will depend on what irreplaceable value the enterprise can create for the entire task chain, and whether this value can be invoked by agents in a credible, open and large-scale manner.
Agent Economy Drives New Growth Momentum
The execution carrier of economic activities has expanded from humans to agents, which will not only reshape market functions and enterprise boundaries, but also eventually be reflected in macroeconomic growth. According to the neoclassical growth theory and its growth accounting framework (Cobb-Douglas production function), economic growth mainly comes from capital accumulation, the increase of effective labor supply and the improvement of total factor productivity. The agent economy acts on all three aspects at the same time, and is expected to become an important increment of the future macro economy.
First, AI demand will expand capital investment and expand the connotation of productive capital. The growth of the number of agents and the scale of task execution will continuously increase the demand for computing power, basic models, data centers and cloud computing, directly driving investment in AI infrastructure. At the same time, agents can organize scattered models, data, software tools and enterprise knowledge around specific production goals, forming production capabilities that can be continuously invoked and reused across scenarios. In the past, business experience attached to individuals can also be precipitated into knowledge bases, process rules and task templates, and converted into intelligent capital that enterprises can replicate and accumulate.
Second, agents will amplify personal capabilities and expand the effective labor supply in the economy. The labor input in growth theory not only depends on the number of workers and working hours, but also on the quantity, complexity and value of tasks that unit labor can complete. After agents enter the production process, workers will gradually shift from completing every step in person to setting goals, organizing resources, supervising processes and judging results. The effective labor in the future will be the combination of human judgment, agent invocation capability and supervision and correction capability. Individuals and small teams can also obtain professional capabilities that in the past only large institutions could provide with the help of agents, so as to expand the scope of economic activities they can participate in.
Third, agents will reduce innovation costs and improve total factor productivity. The endogenous growth theory represented by Romer emphasizes that knowledge production, technological innovation and knowledge spillover are important sources of long-term growth. Agents can enter knowledge-intensive links such as R&D, design, programming and analysis, reducing the costs of information retrieval, scheme comparison and repeated trial and error; they can also reduce the pre-threshold for enterprises to apply new technologies through natural language understanding and tool invocation, shortening the cycle from technology generation, adaptation to the formation of real productive forces. Professional knowledge can also be encapsulated as tools, interfaces or professional agents, so that the capabilities originally concentrated in a few experts and large institutions can more quickly enter the production activities of small and medium-sized enterprises and ordinary workers.
All in all, to measure whether the agent economy can become a real economic increment, we should not only look at how much new computing power, models and agents are added, but also see whether it can help every enterprise organize resources more efficiently, help every worker create higher value, especially enable small and medium-sized enterprises to obtain professional capabilities that were difficult to have in the past at lower costs, and better serve more users.
The agent economy will ultimately serve people and serve life. When technological capabilities are truly converted into business growth for merchants, capability improvement for workers and experience improvement for consumers, a technological breakthrough can be converted into sustainable economic growth and broader social welfare.
The agent economy is not a simple extension of the Internet economy, but a new direction for future economic growth and a new stage in the evolution of the digital economy. However, technological capabilities will not automatically translate into economic growth. The fact that models can understand goals and execute tasks does not mean that individuals and enterprises can already hand over all real transactions to them.
To make the agent economy truly operate, a lot of transformation on the demand and supply sides is needed, standards and rules with industry consensus should be established, and new commercial infrastructure should be formed around identity, authorization, credible transactions, etc. Only when technological capabilities, industrial scenarios and credible mechanisms are all mature, can agents evolve from smart tools to reliable productive forces, and convert technological breakthroughs into solid incremental economic activities.
The experience formed in the past relying on traffic entrances, closed ecosystems and internal integration cannot answer the new problems of the agent era. Facing the new trend of the agent economy, we should actively embrace changes and explore new innovation paths in real scenarios.
Enterprises should open up their professional capabilities