The Age of AI Agents: Agency Belongs to Humans, Tools Are Merely Assistants

AI agents are becoming one of the hottest topics in tech. From coding assistants that complete tasks automatically to virtual assistants that can plan itineraries independently, the capability boundaries of agents keep expanding. But amid discussions of these technological advances, a more fundamental question is often overlooked: agents may be driven by AI, but agency always belongs to humans.

Agents and Agency: Two Easily Confused Concepts

In English, "agent" and "agency" share a common root but point to different things. An agent is the entity that executes tasks—it can be a piece of code, a model invocation chain, or an AI system equipped with tool-use capabilities. Agency refers to a person's ability to make choices, take action, and be responsible for outcomes.

This distinction has become blurred in current discussions. When AI agents can autonomously call APIs, write code, and schedule appointments, people easily fall into an illusion: that agents possess agency. In reality, agents execute assigned goals and constraints. The ones who truly make judgments like "whether to use it," "what to use it for," and "to what extent" are still humans.

This view resonated on social media. Some practitioners pointed out that everyone needs to actively strengthen their own agency, with tools playing a supporting role. Tools can amplify human capabilities, but they cannot replace human judgment.

In the philosophical and sociological traditions, agency refers to an actor's ability to autonomously set goals, make choices, and bear consequences, as opposed to structure and constraints; an agent, by contrast, merely refers to the execution vehicle of action. Separating these two concepts helps avoid a tendency toward technological anthropomorphism: agents can exhibit goal-directed behavior but do not possess the will to set goals autonomously. Therefore, a more rigorous framework for discussing agents is "delegation—execution," where humans set intentions and boundaries and agents act within authorized scope.

What Tools Amplify, and What They Cannot Replace

AI tools are indeed changing how work gets done. Coding agents can accelerate code generation, research agents can quickly compile materials, and automated workflows can take over repetitive operations. The value of these capabilities lies in freeing up human time so people can focus on higher-level decisions.

But the premise of tool amplification is that the person has clear goals. A person without a clear sense of the problem can only get generic results even with the most powerful agent. Conversely, a person who knows what they want can use agents as leverage to produce output far beyond individual capacity.

This is why the phrase "empower your own agency" deserves serious attention. It means that before using AI tools, ask yourself: What problem am I trying to solve? What are my judgment criteria? Which steps must I personally oversee? These questions have no standard answers, but asking them is itself an expression of agency.

Behind the "leverage" metaphor lies "cognitive offloading" in cognitive science: tools can share the burden of memory, calculation, and retrieval, but goal-setting, value prioritization, and accountability for outcomes cannot be outsourced. Particularly at the interpersonal level, using agents requires the ability to translate vague intentions into executable specifications—problem definition, acceptance criteria, and anticipation of failure modes. The stronger this "metacognitive" ability, the more significant the gains from tools, and the better one can avoid mistaking tools for the decision-making subject.

Why Human-Centered Orientation Must Not Be Diluted

As agents become increasingly automated, one risk is that the human role in the process is gradually marginalized. If all decisions are handed over to systems, humans degrade from "decision-makers" to "supervisors," then to "bystanders." Agency is quietly ceded in this process.

Maintaining a human-centered orientation is not a slogan but concrete design principles and usage habits. At the system design level, it means retaining human confirmation at key decision points rather than letting agents execute automatically all the way through. At the usage habit level, it means regularly reviewing which judgments you have handed over to tools and which remain in your own hands.

This is not about resisting automation but about distinguishing which tasks are suitable for full delegation and which require humans to retain final discretion. For example, information retrieval can be highly automated, but decisions involving value judgments, ethical trade-offs, and long-term consequences cannot omit human participation.

In engineering practice, human-centered orientation typically takes shape as two arrangements: "human-in-the-loop" and "human-on-the-loop." The former requires human confirmation at key steps; the latter has humans oversee the overall process and retain the right to intervene. Related governance frameworks such as "meaningful human control" emphasize that the higher the degree of automation, the more it should ensure that humans have sufficient information, can understand system behavior, and can effectively veto or take over. This provides operational standards for distinguishing "fully delegable" tasks from those requiring "retained discretion."

Individual Responsibility: Agency Requires Active Maintenance

Agency is not something you possess once and for all; it requires continuous maintenance. Just as muscles atrophy without use, judgment degrades without practice. As AI tools become more convenient, people easily slide into a state of passively accepting results.

Maintaining agency is not complicated: form your own preliminary judgment before using AI output, ask for the basis when adopting suggestions, and keep a habit of spot-checking in automated workflows. These practices may seem inefficient, but they are precisely what keeps human judgment online.

From a broader perspective, the development of AI agents will not stop based on whether individuals maintain their agency. But whether individuals can maintain independent judgment amid the technological wave depends on whether they actively take on this responsibility. Tools are neutral; direction is determined by humans.

A Coordinate Worth Remembering

"Agents can be AI, but agency is human." This sentence concisely brings the discussion back to people themselves. Agent capabilities will continue to strengthen, and there will be more and more products built around agents, but the coordinate system for all these discussions should be the human—human goals, human judgment, human responsibility.

For everyone using AI tools, this means not abandoning the ability to question while enjoying convenience. Tools are extensions, not replacements. The responsibility of agency can ultimately only be borne by oneself.

One-line Summary

AI agents can execute autonomously, but agency always belongs to humans—judgment must be actively maintained.

Paragraph Summary

The article distinguishes agent (the entity that executes tasks) from agency (the human ability to make choices and bear responsibility), noting that although AI agents can autonomously call tools and write code, goal-setting and final discretion still belong to humans. Tools amplify human capabilities on the premise that the person has clear goals and judgment criteria. As automation deepens, humans may degrade from decision-makers to bystanders, and agency is quietly ceded. Therefore, human-centered orientation must be implemented as concrete design principles (retain human confirmation at key decisions) and usage habits (form preliminary judgments first, ask for the basis, keep spot-checking). Agency, like a muscle, requires continuous maintenance, and individuals should actively take responsibility for maintaining independent judgment.