Former Google CEO Eric Schmidt said in a private lecture in 2025: "In the next decade, the most valuable human skill will not be what you can do, but what you decide AI should do."

1. When the "All-Rounder" Arrives

In January 2026, OpenAI's o3 model scored 87.5% on the ARC-AGI test, approaching human average levels. That same month, DeepSeek V4 was released as open source, matching GPT-4o across multiple benchmarks.

Six months later, both news items have gone from "shocking the tech world" to "oh, we've heard that."

But a deeper question remains unanswered: If AI can do everything, what's left for humans?

2. Three Things AI Can't Do

Don't panic just yet. Let's break down AI's capabilities and limitations.

What can AI do? Summarize, create, code, analyze data, generate images, reason... nearly all "cognitive skills" that humans have mastered.

What can't AI do? The following three things — none of today's AI models can truly do them.

1. AI Can't "Truly Question"

AI can be asked to "offer critical opinions," but its criticism is based on patterns in training data. It doesn't question a conclusion out of genuine unease.

Human questioning often comes from:

  • Intuitive dissonance ("This feels wrong, but I can't say why")
  • Experiential conflict ("I've seen this situation before, and it turned out completely differently")
  • Value discomfort ("Logically it's fine, but it just doesn't feel like the right approach")

    • These three types of "dissonance" have no equivalent in AI's training paradigm. AI always optimizes for a "correct output," but human progress often comes from dissatisfaction with "solutions that are too correct."

    2. AI Can't "Bear Consequences"

    Deloitte's 2025 State of AI in the Enterprise report found that when deploying AI, the biggest obstacle for companies isn't technical — it's "accountability." When an AI's advice leads to an error, who takes responsibility?

    Humans are trustworthy (at least in some situations) because humans:

  • Bear the consequences of their own decisions
  • Hesitate because you might suffer from their actions
  • Re-examine a plan because you say "I'm not comfortable with this approach"

    • AI doesn't. AI has no "conscience" state.

    3. AI Can't "Create Meaning"

    This is the most fundamental one.

    AI can write a poem about "loneliness," but fundamentally, it doesn't know what loneliness feels like. AI can perfectly mimic an empathetic conversation, but it has no inner state of "I truly care about you."

    All human effort and creation ultimately points to one question: What is the meaning of this?

    AI can't answer that. Not because the technology isn't advanced enough, but because "meaning" isn't something that can be trained with data.

    3. MIT's Research Provides the Answer

    MIT Sloan's Paul Daugherty and H James Wilson proposed a framework in their 2025 research: "Human Advantage" = Judgment × Relational Skill × Curiosity

    Tracking AI deployment across over 300 companies, they found:

  • Companies pursuing only automation (using AI to replace human work) saw short-term efficiency gains, but competitiveness generally declined after 12 months — because automation eliminated learning opportunities, causing team capabilities to regress.
  • Companies pursuing augmentation (using AI to amplify human capabilities) showed clear long-term compound growth advantages — every $1 invested in AI produced $3.20 in returns within 18 months.

    • This finding aligns with HBR research published in late 2025: "Augmentation beats automation — not as a value choice, but as an economic fact."

    4. So What Is Human Core Competence, Really?

    With all that said, here's a clear framework.

    In the AI era, human core competence is not "doing better than AI," but "doing what AI can't." Specifically, it's a combination of four capabilities:

    CapabilityDescriptionHow to Cultivate
    🔍 **Judgment**Making decisions with incomplete information; quality-checking AI outputsEngage with ambiguous problems, make trade-off decisions
    🤝 **Relational Skill**Building trust, collaboration, and connectionFace-to-face communication, active listening, real teamwork
    💡 **Curiosity**Asking "why," "what if," and "is there a better way"Broad reading, cross-disciplinary exchange, keep "useless hobbies"
    🎯 **Meaning-making**Knowing what matters and what's worth doingSelf-reflection, values clarification, goal alignment

    Not one of these four capabilities is a "technical skill." They won't become obsolete, they can't be replaced by AI, but they also can't be acquired quickly through "cramming" or "online courses."

    They require real practice, real trial-and-error, and real human interaction.

    5. A Question More Worth Thinking About Than "Being Replaced"

    Every time I write this kind of article, it feels like I should end with reassurance: "Don't worry, AI won't replace you."

    But I think the question truly worth asking is not "Will AI replace you?" but:

    If AI makes "being able to do it" completely worthless, what about you is worth remembering?

    People who have figured this out don't need anyone to tell them what their "core competence" is.

    Because they already have it.

    References

    1. Eric Schmidt, Private Lecture (2025). Republished across multiple tech media outlets.
    2. OpenAI (2026). o3 model scores 87.5% on ARC-AGI — Technical Blog.
    3. DeepSeek (2026). DeepSeek V4 Open Source Release — Technical Announcement.
    4. Deloitte (2025). State of AI in the Enterprise, 8th Edition.
    5. MIT Sloan — Paul Daugherty & H James Wilson (2025). Human Advantage: Judgment × Relational Skill × Curiosity.
    6. HBR (2025). Why Augmentation Beats Automation: An Economic Fact.

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