Have you ever seen this?

The company sent thirty people to learn AI. After they returned, only two actually used it — one used AI to calculate their market value and asked for a raise; the other used it to help their boss write a resignation letter.

Sixty laughs below — all from fellow managers, wry smiles.

Have you noticed the shift in the air lately?

Everyone is diving into AI training — learning to code, learning prompts, learning new tools. Managers worry "will my job be replaced?" Employees whisper "is the company planning layoffs?" Team morale that was once decent has plunged like an elevator with cut cables.

✧ Data You Can't Ignore

The World Economic Forum's Future of Jobs Report 2025 predicts that by 2030, about 39% of workers' core skills will be fundamentally transformed or disrupted. Meanwhile, demand for AI and big data skills is expected to grow by over 87%.

Even more concerning is another set of numbers. McKinsey's 2025 survey shows that while 88% of organizations are using AI in at least one business function, only 39% are seeing real financial impact. BCG similarly finds that 74% of companies have yet to demonstrate tangible value from AI usage.

McKinsey's State of Organizations 2026 reveals another critical gap: 86% of leaders believe their organization is not prepared for AI adoption in daily operations.

You think you're investing in the future — you might just be "burning money."

✧ A Real-Life Scenario That Stings

A CEO once told me: "We implemented a state-of-the-art AI system — spent millions. Six months later I asked how it was going, and they said 'it's good, just a bit complex.'"

He checked the backend — only IT logged in daily. The business was still using Excel.

He asked the CIO: "Why isn't the business using it?" CIO: "They're used to the old ways — they don't want to learn."

He asked the business head: "Why aren't you using the new system?" Business head: "IT chose it — it doesn't fit our business processes."

You spent millions on a system no one uses.

This isn't a technology problem — it's a "managers don't know how to use it" problem.

✧ A Perspective-Shifting Insight

You think you're investing in AI. You're actually investing in "whether managers know how to use AI."

Gartner predicts that by the end of 2025, at least 30% of generative AI projects will be abandoned after proof-of-concept — due to poor data quality, insufficient risk control, rising costs, and unclear business value.

The issue has never been whether AI is powerful enough — it's whether managers know how to use it.

What's truly dangerous isn't that you don't know how to use AI — it's that you're still organizing people, setting roles, and running processes the old way, while thinking you're already using AI.

AI is a sailor. You must be the captain. A captain who doesn't know where they're going will just drift, no matter how favorable the winds.

You don't need to be an AI expert. You just need to be "a manager who knows how to use AI."

✧ Three Questions to Reframe AI's Value

If you also want your AI investments to yield returns, ask yourself:

1. Is your AI "helping people work" or "making decisions for people"? — The former is a tool; the latter is replacement. Have you thought this through?

2. Do your managers know how to use AI? — If managers can't use it themselves, why expect the team to?

3. Are you "buying systems" or "changing minds"? — Systems can be bought. "Changing minds" can't.

✧ This Article Is Just an Introduction

What you just read is the opening of Chapter 14 of Catalytic Leap: "AI and Management: You Won't Be Replaced by AI, But You'll Be Surpassed by Managers Who Use AI."

How does AI amplify Insight and Drive? How do you use AI to free yourself from low-value work? How does each Change Quotient Quadrant accelerate with AI? How can managers use AI to transform meetings, communication, data analysis, and five other high-value scenarios?

These answers are in the book.

Catalytic Leap will take you through Diagnosis, Methods, Enablement, Internalization, and Practice — when your AI investments become an expensive "performance," this book will become your "human-AI collaboration guide."

If you also want to evolve from "AI worrier" to "human-AI collaboration catalyst" —

① Get a free sample of Catalytic Leap (includes complete Diagnosis section + Change Agility Assessment)

② Visit www.jameschin.sg for the Manager AI Application Self-Assessment

③ Book a 30-minute free consultation for a direct conversation with the author

This article draws from Chapter 14 of Catalytic Leap. Want to know how to evolve from "AI worrier" to "human-AI collaboration catalyst"? The full answers are in the book.