AI Job Losses, Big Tech Layoffs, and the Rise of the Problem-Solving Class
The Great Reordering of Work
In the span of a single year, artificial intelligence has gone from a technological talking point to an economic earthquake.
Across Silicon Valley and beyond, automation is not just augmenting workers—it’s replacing them.
From Amazon and Google to Meta and Salesforce, tens of thousands of high-skilled employees have been laid off in 2025. Many of these jobs aren’t coming back. Despite the official statements that cite “organizational restructuring” or “over-hiring,” the truth is clear: AI is fundamentally redefining how work gets done—and who does it.
In my recent appearance on Next Gen Investing on the Schwab Network, I shared a perspective that echoes one of the central theses of my book Generation AI:
“The spoils will go to those who can identify the problems that need to be solved—not those who wait to be told what to do.”
We are entering what I call the era of the problem-solving class—a new creative and analytical elite defined not by credentials, but by adaptability, critical thinking, and courage.
The rise of AI doesn’t mark the end of human work. It marks the end of deterministic work—the kind of predictable, instruction-based labor that machines now perform faster, cheaper, and more accurately than we ever could.
Automation Has a Center of Gravity
The idea that “the future is already here, just not evenly distributed” has never been more relevant.
The gravitational center of automation is currently Big Tech—the companies best positioned to both build and deploy AI at scale.
Amazon, for example, has cut over 50,000 jobs in the last 18 months—many in middle management, data operations, and customer service. While the company’s leadership framed these decisions as structural efficiency moves, the underlying driver is unmistakable: AI is eliminating layers of human mediation.
“When Amazon’s CEO Andy Jassy said the layoffs were about reducing layers, he was right,” I told Schwab Network. “AI is what reduces layers.”
For decades, companies depended on hierarchy to manage complexity. AI collapses those hierarchies.
Decisions once made by teams of analysts are now made in seconds by intelligent agents. Tasks once distributed across departments are automated end-to-end. In a world of instant pattern recognition, the middle of the org chart becomes expendable.
And Big Tech is merely the first domino.
The same logic will soon extend to financial services, consumer goods, healthcare, and manufacturing—any sector where repetitive or rules-based processes dominate.
This isn’t cyclical disruption; it’s structural. The next decade won’t just be about “adapting” to AI. It will be about completely rethinking what human contribution means inside a business.
The Capital Rotation: From Labor to Intelligence
Economists have long tracked capital rotations between sectors—energy to tech, hardware to software, emerging markets to developed economies.
But we are now witnessing something far more profound: a rotation of capital from human labor to machine intelligence.
Corporate balance sheets are quietly shifting their biggest line items.
Instead of spending on salaries and benefits, companies are investing in AI models, compute infrastructure, and proprietary data.
Instead of hiring more people, they’re building digital workforces.
This is not just a cost-saving move—it’s a profitability revolution.
AI allows companies to scale without hiring, to personalize without people, and to automate without permission.
That changes everything from corporate strategy to Wall Street valuation models.
But it also raises a critical question: what happens when machines become the new middle class?
The answer depends on whether leaders—and workers—are bold enough to reinvent themselves.
Bold Leadership in the Age of Agents
When I speak to executives across Fortune 500 boardrooms, I often sense a quiet paralysis.
Everyone recognizes that AI is rewriting the rules. But very few leaders are willing to act before the transformation is forced upon them.
“Too many corporate leaders are managing to not get fired,” I said during the Schwab interview. “They’re trying to survive long enough to collect a golden parachute rather than reinvent their company for the future.”
That fear-based leadership model is the single greatest risk facing corporate America.
The boldness we saw during the digital revolution—the willingness to disrupt one’s own business—has largely disappeared from legacy organizations.
There are exceptions. Salesforce CEO Marc Benioff, for example, has staked his company’s future on “Agentforce”—its vision for an AI-driven business ecosystem.
Benioff isn’t waiting for AI to prove itself in the market. He’s betting the company on it.
That kind of courage will define the next generation of corporate winners.
The leaders who understand that “waiting to be told what to do” is no longer a strategy—it's an extinction plan.
Workers at the Crossroads: Deterministic vs. Creative Labor
At the employee level, the workforce split is equally stark.
We are dividing into two broad categories: deterministic workers and creative problem solvers.
A deterministic job is one where the output can be defined in advance: process this form, enter that data, respond to that inquiry, follow that template.
AI thrives on determinism.
Conversely, a creative problem solver identifies the right questions, not just the right answers. They see patterns where others see noise. They know how to use AI not as a crutch, but as a catalyst.
“If you walk into work every day waiting to be told what to do, you’re at risk,” I explained during the interview. “But if you know how to define the problems and deploy AI to solve them, your value is about to 10x.”
This divide will widen dramatically over the next five years.
In 2025, roughly 40% of all workforce tasks in the U.S. can already be automated, according to McKinsey. By 2030, that number could exceed 60%.
But automation doesn’t mean elimination. It means reallocation.
The most valuable professionals of the AI era won’t be coders or prompt engineers—they’ll be strategic integrators. People who understand how to combine technology, data, and human insight to produce exponential results.
Adobe, Google, and the Innovator’s Dilemma
One of the most telling examples of this transition is playing out at Adobe.
Long considered an untouchable giant of creative software, Adobe suddenly finds itself in a knife fight between its legacy business model and a wave of AI-native competitors.
Adobe’s AI-powered “Firefly” platform is its boldest bet yet—a tool that democratizes design by allowing anyone to generate visuals with a simple prompt.
The upside? It expands the total addressable market for creativity.
The risk? It could cannibalize the professional designers who built Adobe’s empire.
Meanwhile, upstarts like Canva have leveraged AI to scale faster, cheaper, and with a more intuitive user experience.
That’s the innovator’s dilemma on full display: the incumbent must disrupt itself before someone else does.
Google faces a similar existential question.
When I ask audiences at my keynotes how many people have used ChatGPT or Perplexity instead of Google for a search, 80% of hands go up.
That’s an astonishing signal.
Google, a company that has monetized algorithmic search for over two decades, now faces the choice between protecting its core business or reinventing it entirely for an AI-first world.
The tension is universal: adapt or be automated away.
Automation and the New Corporate Stack
Automation isn’t just changing individual roles; it’s reconstructing the corporate stack from the ground up.
The traditional hierarchy—executives, middle managers, operators, assistants—is being flattened into three layers:
Strategic decision-makers (vision, direction, ethics)
AI systems and autonomous agents (execution and optimization)
Human collaborators (creative, relational, and interpretive tasks)
In this new architecture, middle management as we know it becomes largely obsolete.
AI handles the coordination, scheduling, and reporting functions that managers once owned.
Even the concept of “departments” begins to blur as cross-functional teams collaborate with shared AI systems instead of siloed workflows.
This flattening doesn’t just make companies faster; it makes them smarter—but only if leaders can manage the transition without losing their human culture along the way.
The future of management isn’t about controlling people; it’s about orchestrating intelligence, both human and artificial.
A Requiem for Routine: Why “Safe” Jobs Aren’t Safe
There was a time when safety in the workplace meant predictability.
If your role was stable, structured, and routine, you were safe.
AI has inverted that equation.
The most “secure” jobs are now the most susceptible to automation.
Data analysts, financial controllers, paralegals, and even software testers—once considered white-collar fortresses—are being quietly replaced by large language models and AI-driven agents.
Meanwhile, professions once seen as soft or peripheral—creatives, strategists, storytellers, educators, therapists—are becoming central to economic value because they rely on context, empathy, and synthesis, not repetition.
AI is teaching us an uncomfortable truth: The only sustainable skill is the ability to learn new skills.
Education’s Role in Reprogramming the Workforce
This transformation demands a corresponding shift in education.
For decades, we’ve trained workers to memorize and regurgitate—a model that made sense in the industrial and digital eras but collapses in the age of AI.
When information is abundant and accessible, memorization becomes irrelevant.
What matters now are higher-order capabilities:
Problem framing
Creative ideation
Ethical reasoning
Collaboration across human–machine teams
As I wrote in Generation AI, education must evolve from “teaching answers” to “teaching questions.”
The classroom of the future isn’t a place to download knowledge—it’s a laboratory for experimentation.
If we fail to make that shift, we’ll produce generations of workers perfectly trained for jobs that no longer exist.
The Human Advantage
Despite the fear and anxiety surrounding AI, we still hold one irreplaceable advantage: consciousness.
AI can simulate empathy, but it can’t feel it.
It can analyze values, but it can’t choose them.
Our ability to interpret nuance, manage relationships, and make moral judgments gives us a permanent strategic edge—if we choose to cultivate it.
The winners of the AI economy will be those who combine human intuition with machine precision.
The future won’t be man versus machine—it will be man with machine.
The creative director who uses AI to prototype ideas in seconds.
The marketer who uses predictive models to understand consumers better.
The entrepreneur who uses AI agents to test, iterate, and launch a new business in weeks.
These are the archetypes of the new workforce—humans amplified by intelligence, not replaced by it.
Preparing for the 2030 Workforce
Looking ahead to 2030, the World Economic Forum projects that 83 million jobs will be displaced by automation—but 69 million new ones will be created.
The difference will depend entirely on whether organizations and individuals can evolve quickly enough to capture those new opportunities.
The most in-demand skills won’t be technical. They’ll be behavioral: curiosity, adaptability, emotional intelligence, and resilience.
Every business and every worker will have to answer a simple question:
Am I using AI, or is AI using me?
For workers, that means continuously learning how to partner with AI tools instead of competing against them.
For employers, it means rethinking hiring and training to focus on mindset over mastery.
And for leaders, it means embracing discomfort as the new normal.
A Call for Fearless Reinvention
History rewards the bold.
During the industrial revolution, those who resisted mechanization vanished. Those who embraced it built the modern economy.
We are living through an equally seismic shift—and the stakes are just as high.
The leaders who treat AI as a threat will watch their organizations shrink.
Those who see it as a force multiplier will build the next generation of global enterprises.
As I said on Schwab Network, the fearless will win.
Fearless leaders will experiment publicly, make hard cuts when necessary, and bet big on the tools of the future.
Fearless workers will challenge old career narratives and reinvent themselves as hybrid operators—half human, half algorithm.
And fearless societies will invest in education, regulation, and ethics not to slow AI down, but to guide it toward progress.
The AI revolution doesn’t ask for permission. It demands participation.
Conclusion: The Work of Tomorrow Is Here Today
Artificial intelligence is not coming for your job tomorrow. It already came yesterday.
The question is whether you noticed.
The companies that survive this decade will be those that harness AI to multiply human creativity, not erase it.
The individuals who thrive will be those who learn to navigate ambiguity and turn technology into leverage.
This is not the end of work—it’s the beginning of better work.
Work that rewards imagination over instruction.
Work that values courage over compliance.
Work that uses machines to make humans more human.
As we move deeper into this AI-driven decade, one truth stands out: progress belongs to the problem solvers.
And those who refuse to adapt will soon find themselves automated out of relevance.
The future of work isn’t being written in code—it’s being written by those brave enough to lead.
