Jack Ma, AI, and the Lost Art of Problem Solving

I recently stumbled upon an old video of Jack Ma offering advice to fresh graduates (watch here). One part resonated deeply with me:

Young professionals, he said, face two broad career paths when starting out. One is to join a small company, where you learn many functions and — more importantly — how they connect, how systems work, and how to innovate and build new ones. The other is to join a large, established company where systems and processes are already in place. There, your role is to help ensure the machine runs smoothly, often without fully understanding why it runs the way it does.

Jack urged young people to choose the first path — exposure, learning, adaptability — over the allure of higher pay and status in the second. Watching this now, in my fifties, running my own data consulting firm and helping clients navigate the fast-moving world of AI, this message hit me harder than ever.

Let me explain why.

The Value of Building and Breaking Systems

I started my career in construction — the ultimate playground for problem solving. Each project was different. Every day brought new challenges. To succeed, you couldn’t just follow SOPs. You had to build new systems, break old ones, and innovate constantly.

It wasn’t glamorous, and it certainly didn’t pay as much as the MNC roles my peers went into. But it taught me something they rarely had to learn: how to think globally, how to connect the dots across different parts of a business, and how to solve problems when things went sideways — as they often did.

Later, I too entered a large MNC, this time in HR. There, I saw a different reality. Success came not from building new systems, but from navigating existing ones. You advanced by optimizing your part of the machine, sometimes at the expense of the bigger picture. And yes, learning to play nice and be politically astute mattered as much — if not more — than true problem-solving ability.

An Uncomfortable Truth: How Innovation is Often Handled

One pattern I’ve observed — and experienced — time and again is this:

When you’re the one trying to fix problems that haven’t been solved before, or when you try to introduce something new, failure is part of the process. You’ll likely run into multiple failed attempts before eventually succeeding. That’s the nature of innovation.

But in many large organizations, those sitting in secure positions — running stable systems — often find it safer to poke holes in the innovator’s ideas, highlight flaws, or claim "it won’t work." Ironically, they remain ready to take (or share) credit when the innovator finally pulls it off.

And it’s easy to look sharp when you haven’t been trying.

Now, I’m not trying to put specialists down — they play an essential role in any complex organization. But this dynamic is also a well-worn management tactic to protect one’s position and advance at the expense of the true problem solvers and builders. It’s worth calling out, because as AI transforms the nature of work, this behavior may become even more counterproductive.

How We’ve Been Optimizing for the Wrong Things

Over the past few decades, this preference for specialization and optimization within silos has only deepened.

Companies favor talent that can keep the system stable. We reward specialists, not generalists. We

promote those who can point to certifications and degrees, not those whose skills come from experience and trial-and-error.

The result? We’ve built organizations filled with people who know how to operate systems, but fewer who know how to build or redesign them. We’ve told entire generations that stability is success, and that the messiness of innovation and problem solving is best left to others.

Enter AI: The Great Disruptor

Now, AI is changing the game.

Tasks that are repetitive, consistent, and rule-based — many of the things we’ve trained generations to excel at — are being automated faster than most people can imagine. According to a recent McKinsey report, over 60% of current work activities could be automated in varying degrees by 2030 (source).

But what AI can’t easily do is this:

• Redesign workflows to incorporate AI itself

• Troubleshoot and problem-solve when AI breaks or misbehaves (and it does)

• Reconfigure processes when the landscape shifts, as it surely will

These are human skills. And they happen to be the very ones we’ve inadvertently devalued for years.

Why Jack Ma’s Advice Matters More Than Ever

As we stand on the brink of an AI-driven economy, Jack Ma’s advice is even more relevant today than it was a decade ago.

We urgently need professionals who can:

✅ Understand how entire systems work, not just their part of it

✅ Spot when a process no longer fits and redesign it

✅ Connect insights across different functions

✅ Thrive in ambiguity and change

These skills aren’t typically built in large companies where the message is “keep your part running.” They come from messy experiences — like my early days as a dirty site engineer, or working in small businesses where you have to wear many hats and think holistically.

A Wake-Up Call for Individuals and Organizations

For individuals: if you’re early in your career, be wary of the easy allure of the big brand name. Seek roles that give you exposure across functions and force you to build real-world problem-solving skills.

For organizations: it’s time to rethink how we hire and reward talent. We need to elevate the value of systems thinkers, problem solvers, and builders — not just those who can operate within the machine.

And for society at large: let’s stop underestimating experience-based learning. The next wave of progress will require people who know how to rebuild, reimagine, and rethink. AI will make the stable and repetitive obsolete. But it will make adaptable problem solvers more valuable than ever.

As someone who has lived both sides of this story — from dirty site engineer to MNC executive to entrepreneur — I’m convinced: in the age of AI, Jack Ma’s advice may be one of the most important career lessons we can pass on.