In an era dominated by apocalyptic predictions about artificial intelligence destroying the workforce, Goldman Sachs CEO David Solomon said something genuinely refreshing: he predicts his company will have more employees in ten years because of AI, not fewer.

This isn't just optimistic rhetoric from an out-of-touch executive. It's an insight rooted in historical patterns, economic reality, and a deep understanding of how technology actually transforms work.

The Microfiche Moment

Solomon's most compelling point comes from his own experience. When he started his career 42 years ago, conducting financial research meant physically traveling to a library, loading up microfiche machines, and spending hours manually comparing company data. The process was laborious, time-consuming, and limited in scope.

Today, that same research can be done by speaking a query into your phone. The transformation is staggering.

But here's the critical insight: did those massive productivity gains eliminate financial analysts? Did Goldman Sachs shrink its workforce because computers made research faster?

No. The opposite happened.

Why Productivity Doesn't Equal Job Elimination

This counterintuitive reality puzzles people, but the logic is straightforward. When technology makes workers more productive, several things happen:

Markets expand. Companies don't just do the same work with fewer people. They tackle bigger problems, serve more clients, and enter new markets. Goldman didn't maintain a fixed amount of research with fewer analysts. They exponentially increased the depth and breadth of analysis they could provide.

New work emerges. Technology doesn't just make old tasks faster. It makes entirely new categories of work possible. In Solomon's early career, algorithmic trading, quantitative analysis, and real-time risk modeling weren't just difficult — they were impossible. Today they're core business functions employing thousands.

Human judgment becomes more valuable. When routine tasks get automated, the premium on strategic thinking, relationship building, and creative problem-solving increases. AI handles the grunt work, freeing humans to focus on the parts of work that actually require human insight.

The $6 Billion Bet

Goldman Sachs is investing $6 billion in technology this year. Solomon notes that one great coder with AI tools now has the capacity that used to require 10–20 people.

On the surface, this sounds like a recipe for layoffs. Dig deeper, and you see why it's actually a growth strategy.

That developer isn't replacing 10–20 people doing the exact same work. They're enabling work that was previously impossible at scale. They're building systems that create entirely new capabilities for the organization. They're solving problems that couldn't be solved when those problems required 10–20 people to address them.

This is the pattern that's played out with every major technological shift in modern history.

The Historical Pattern

The 1980s: Computers were going to eliminate office jobs. Instead, the computer revolution created entire industries. Software engineering, IT support, digital marketing, data analysis — none of these fields existed at scale before computers became ubiquitous. Office employment exploded.

The 1990s: The Internet was going to destroy traditional employment. Instead, it created e-commerce, digital media, online education, cloud computing, and countless other sectors. The number of jobs increased dramatically.

The 2000s: Automation and offshoring were going to hollow out the workforce. Instead, we saw the rise of the gig economy, mobile app development, social media management, and entire categories of work that didn't exist before.

The doomsayers have been wrong every single time. Not because technology doesn't disrupt — it absolutely does — but because human ambition and market dynamics create new opportunities faster than old ones disappear.

The Disruption Is Real, But Not What You Think

This isn't to say AI won't cause disruption. It will. Some specific roles will shrink or disappear. The transition will be uncomfortable for many people. Skills that were valuable will become less so.

But the aggregate effect — more jobs or fewer jobs overall — trends toward expansion, not contraction.

Why? Because productivity gains don't occur in a vacuum. They occur in a competitive marketplace where companies that can do more, do more. They occur in an economy where consumer expectations rise to meet new capabilities. They occur in a world where solving one problem reveals ten more problems worth solving.

When Goldman Sachs employees become more productive through AI, the company doesn't maintain a fixed scope with fewer people. It expands its scope with the same or more people who are now exponentially more capable.

The Mindset That Matters

Solomon's prediction isn't guaranteed to come true simply because historical patterns suggest it. It will come true because enough people choose to make it true.

The people who will thrive in an AI-augmented economy are those who view the technology as something happening for them, not to them. They're learning prompt engineering, experimenting with AI tools in their workflow, and actively seeking ways to amplify their capabilities.

The people who will struggle are those who resist, ignore, or wait passively for others to tell them what to do.

This isn't a moral judgment. It's an observation about how technological transitions work. The winners aren't necessarily smarter or more talented. They're the ones who engage with change earlier and more actively.

What This Means For Your Career

If you're reading this and feeling anxious about AI, that anxiety is understandable. But channel it into action, not paralysis.

Ask yourself: What's one way I can use AI to become better at what I do? Not to replace what I do, but to amplify it.

For writers, that might mean using AI for research and first drafts, freeing you to focus on voice and insight.

For analysts, it might mean automating data collection so you can spend more time on strategic interpretation.

For managers, it might mean using AI to handle routine communications so you can focus on coaching and relationship building.

The specifics don't matter as much as the approach. The people who lean in will discover opportunities. The people who lean out will find themselves increasingly irrelevant.

The Bottom Line

David Solomon isn't being naive or blindly optimistic. He's recognizing a pattern that's played out consistently throughout modern economic history.

Technology makes workers more capable. More capable workers enable companies to do more. Doing more creates opportunities for more workers.

This isn't guaranteed to work out perfectly for every individual or in every industry. But as a macro trend, it's far more reliable than the doom-and-gloom predictions that dominate current discourse.

I believe, as I always have, that GenAI will create jobs, not eliminate them. Not because I'm ignoring the disruption, but because I understand that human potential expands to fill the space that technology creates.

The question for you isn't whether AI will change your field. It will.

The question is whether you'll be among those who harness that change to become indispensable, or among those who get left behind waiting for things to go back to the way they were.

Choose wisely. The future is being built right now, and there's still time to grab your tools and help build it.