ChatGPT 提供答案，自主式 AI 做出決策

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ChatGPT gives answers. Agentic AI makes decisions.

I didn’t think that difference mattered—

until organizations started losing control.

From Answers to Decisions

The shift from answers to decisions changes everything.

When AI only answers, mistakes are annoying.When AI decides, mistakes become legal problems.

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That’s the part most organizations failed to anticipate.

The Visionaries: Efficiency at Any Cost?

Jensen Huang envisions a future where every company employs billions of “digital workers.”He sees AI agents as a scalable workforce that never sleeps.

Elon Musk is betting the house on autonomous entities—from Grok to Optimus—that act independently in both physical and digital realms.

They call it autonomy.

But as a lexicographer who has tracked the language of capital for three decades, I see it differently.

Behind the curtain of autonomy lies a massive expansion of agency cost.

Everyone’s Building Agents. No One’s Ready.

Gartner predicts that nearly 40% of agentic AI projects will be abandoned by 2027.

Not because the technology fails.But because control fails.

The difference is structural:

Generative AI → an informant responding to prompts

Agentic AI → an actor decomposing goals and executing multi-step plans

When systems start acting, accountability starts disappearing.

Capital One’s 55%: Performance or Storytelling?

In early 2025, Capital One reported a 55% increase in lead conversion after deploying an AI-powered “Chat Concierge.”

It sounds impressive.

But something feels off.

No external verification.No industry benchmarks.No independent validation.

Everything is proprietary.

In AI, self-reported success is dangerously close to fiction—not because companies lie,but because no one can prove whether they’re right.

MCP: The Highway Problem

The Model Context Protocol (MCP), contributed to the Linux Foundation in December 2025, is becoming the backbone of agentic systems.

The promise is simple: seamless integration.

The reality is less comforting.

Security researchers have already flagged vulnerabilities:

prompt injection

tool permission escalation

uncontrolled agent actions

Standardization doesn’t eliminate risk.It concentrates it.

A single highway makes travel easier—and attacks scalable.

The Billion-Dollar Question

When agentic AI makes a decision that costs millions,who takes responsibility?

Engineer: “I built what I was asked to build.”

Vendor: “Our model worked as designed.”

C-suite: “We followed industry best practices.”

The model: silence.

Jensen Huang talks about “digital workers,”but he doesn’t mention who handles digital malpractice.

Elon Musk talks about “unsupervised” intelligence,but in the legal world, “unsupervised” usually means “uninsured.”

The result is predictable:

No one is responsible.

This Isn’t a Technology Problem

Agentic AI is not a technical breakthrough.

It is a liability amplifier disguised as autonomy.

Organizations aren’t failing because agents don’t work.They’re failing because no one defined who takes the fall when they do.

We didn’t just automate decisions.

We automated deniability.

About the author

Chungmoo Lee is an economic lexicographer and former financial journalist with over 30 years of experience in finance and capital markets. He explores how AI systems reshape responsibility, risk, and power through critical analysis of algorithmic behavior.

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