Presentation · 17 Slides

PEOPLE SKILLS
AI CAN'T REPLACE

How work is changing, and the human strengths to encourage and hire

Ideas drawn from Noema Magazine

Compiled by Howie Baum and Claude AI

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Context

Why This Matters Now

101,743

US job cuts that employers blamed on AI, January to June 2026

16%

Drop in jobs for workers aged 22 to 25 in AI-exposed fields

57%

Share of Claude conversations where people thought with AI rather than handing work off

Sources: Challenger, Gray & Christmas; Stanford Digital Economy Lab; Anthropic Economic Index (cited by Friedland, Noema)

The Shift

Keyboard Work Shrinks, Judgment Grows

⬇ Shrinking

Drafting routine documents
Entering and moving data
Writing routine code
First-draft reports

⬆ Growing

Judgment when things are messy
Sorting signal from noise
Persuading and negotiating
Building trust with people

Historical Context

History's Lesson: Tools Reshape Expertise

Before 1800

Artisans

Skilled craftsmen made each item by hand

1800s–1950s

Factories

Machines created new skilled jobs: machinists, electricians, clerks

1960s–2020

Computers

Routine office jobs faded; pay rose mostly for college-educated experts

Now

AI

Could help more workers make expert decisions

Research Evidence

AI Helps Those Who Know Their Work

40%

Less time on writing tasks, and the weakest writers caught up to average

3 vs 10

Months for new customer service agents to match experienced ones

No gain

For radiologists who weren't trained to use the AI tool well

"Like a nail gun, AI helps the trained worker and endangers the beginner."

Rising Skills

The Judgment Economy: 3 Rising Skills

🤝

Bringing People Together

Persuading, building agreement, leading.

Example: A supply chain director who convinces partners to act on the AI's plan

🔍

Interpreting Information

Turning data into wise choices and risk calls.

Example: A fund manager weighing how a crisis changes a 20-year plan

🧩

Connecting Ideas

Combining insights from many fields.

Example: A transit planner blending health, climate and community needs

Human Strengths

What People Bring That AI Does Not

❤️

Lived experience We have felt grief, hunger, fear and joy

🤲

Presence We can show up and stay with someone

✅

Trust and accountability We answer for our decisions

🧭

Moral judgment We weigh right and wrong, not just odds

👁️

Reading the room We sense the unspoken and the mood

💡

Original creativity We link unlike ideas in new ways

⏳

Sense of history We know why things came to be

💬

Persuasion We negotiate and win people over

🔧

Hands-on know-how We handle the messy physical world

🎯

Purpose and caring We care how things turn out

Workplace Practice

Thinking Skills to Encourage at Work

❓

Question the output Is it accurate? What is missing? Who checked it?

🎯

Ask "so what?" Which finding actually matters for our goals?

🔗

Connect across fields What can we learn from another field or from history?

📣

Explain it plainly Can a busy director grasp it in two minutes?

🧠

Know your own thinking When should I trust the AI, and when trust myself?

Practical Framework

From AI Findings to Clear Answers: 4 Steps

1

Check

Verify facts and numbers against a trusted source

2

Choose

Pick the 2 or 3 findings that matter most

3

Translate

Say what it means in plain words

4

Advise

Suggest a next step and name the risks

Example
"The AI says visits rose 18% since spring. I checked our sign-in sheets and it's right. Most growth is seniors on Saturdays. I recommend adding two Saturday volunteers. The risk is a volunteer shortage in December."

The Research

Costly Mistake: Speed Isn't Good Thinking

AI simply added on

Doctors with AI: no more accurate
Drug sales: about 20% below no AI at all
Consultants: worse on judgment tasks

People and AI as a team

Doctors: accuracy rose from 75% to 82–85%
Drug sales: up 16%, with 40% more client meetings
Consultants: 40% better on tasks AI handles well

"Same AI. The difference was how the work was set up."

Design Principle

Keep People in the Driver's Seat

Person leads, AI assists

Judgment stays sharp and keeps growing

AI leads, person follows

People "fall asleep at the wheel" and skills fade

A Real Reversal

In 2024, Swedish company Klarna replaced hundreds of customer service staff with AI chatbots. By 2025, service had slipped and it rehired people.

Hiring & Management

Hiring for the AI Era: What to Look For

Old focus	Add this focus
Speed at typing and data entry	Good decisions under uncertainty
One narrow technical skill	Curiosity across many fields
Degree or job title	Track record of real decisions
Working alone fast	Teamwork, trust and persuasion
Knowing the answers	Asking good questions and checking AI

Interview idea: Hand over an AI summary. Ask what they would check and say.

Leadership Actions

How Leaders Encourage These Strengths

📋

Protect learning

Keep entry-level work that teaches judgment; pair new staff with mentors

🏆

Reward good decisions

Praise sound calls and lessons learned, not just volume

👥

Design teamwork with AI

Have people and AI assess separately, then compare

🎓

Train, then trust

Teach staff when to rely on AI and when to override it

Honest Concerns

Honest Risks to Watch

⬇️

Lower-paid replacement jobs

Good jobs could be refilled with poorly paid ones

1️⃣

A missing bottom rung

Fewer entry-level jobs means fewer ways to gain experience

⚖️

Gains for a few

Profits could concentrate with whoever owns the AI

🏛️

Unequal access

Broad education and training aren't available to everyone

Policy & Action

Sharing the Gains Early

The big idea

Give people skills and a stake early, not just checks after layoffs

Model: the 1944 GI Bill paid for school, homes and business loans

It helped build America's largest middle class

Help available now

Free retraining for laid-off workers through WIOA
In Ohio: local OhioMeansJobs centers
RAISE US: $500M+ effort testing wage insurance and retraining

AI can interpret my grief. It cannot grieve.

— Houda Nait El Barj

Invest in judgment, presence and trust.
They are what make AI worth using.

References

Sources

Nils Gilman, "How to Future-Proof Your Career in the Age of AI," Noema, April 9, 2026
David Autor, "AI Could Actually Help Rebuild the Middle Class," Noema, February 12, 2024
Barton Friedland, "The Devastating Mistake Employers Are Making When It Comes to AI," Noema, March 26, 2026
Saffron Huang and Sam Manning, "Here's How to Share AI's Future Wealth," Noema, April 22, 2025
Houda Nait El Barj, "How AI Will Change Us," Noema, June 25, 2026
Shannon Vallor, "The Danger of Superhuman AI Is Not What You Think," Noema, May 23, 2024
Challenger, Gray & Christmas job cuts data (2026); RAISE US coverage, Axios, June 25, 2026

PEOPLE SKILLSAI CAN'T REPLACE