For those who work in AI, let me share a cautionary tale based on history. You may be getting incredibly rich right now, but there’s little point in being rich if your safety is constantly at risk.
Back in 2008, I was working in finance at Credit Suisse Group in San Francisco. There were constant protests against all financial institutions for the next three years.
The most famous slogan to come out of the global financial crisis was, “We are the 99%!” People camped out in public parks through NYC and other big cities, and anybody who worked in finance was the bad guy. And you definitely didn’t want to tell people you worked in finance out of fear of being mugged and beaten.
It was a strange time for me given I had nothing to do with folks not paying their mortgages or loan officers lending money to households they probably shouldn’t have. Further, I was losing a fortune, given ~95% of my net worth was invested in risk assets.
My friends, colleagues, and clients were getting laid off left and right. I remember counting seven rounds of layoffs at Credit Suisse over only a two-year period. The global financial crisis was a stressful and scary time as I thought I might end up losing everything. In 2005, I had bought a single family home with a huge mortgage and had no more cash after the 20% down payment.
At one point, my net worth was probably down about 40% in six months that took 10 years to accumulate.
I wanted to protest too!
The Beginning Of The End
In retrospect, the GFC began sowing the seeds of my discontent. Before the collapse, I felt proud to have had a job in finance. I was helping institutional investors better allocate their capital in the Asia region. It was also enjoyable to meet entrepreneurs and company management during their IPO roadshows to help them raise capital.
However, once the GFC hit, I lost almost all my pride and joy for the business. Not only was I getting crushed financially, I also felt bad working in finance given all the constant attacks.
And so, I began to daydream about a simple life after finance and plan my escape. First came the launch of Financial Samurai in July 2009 as a cathartic way to make sense of the chaos. Then came even more aggressive saving and investing, bumping up my saving rate to ~80% for my final 2.5 years. Finally came gaining the courage to raise my hand to get laid off and negotiate a severance package.
Yes, I missed the money. But my soul also felt lighter leaving the financial services industry.
The public had influenced my belief that I was bad, even though I worked in international equities. I had to make a decision whether grinding 60 hours a week doing something that society looked down upon was worthwhile. And my decision was no. Besides, I was already burned out.
The GFC’s Damage Was Real, But Relatively Contained
Between 2007 and 2010, there were approximately 3.8 million foreclosures. Across the full decade-long crisis, there were about 6 million completed foreclosures, roughly one out of ten households with a mortgage. Somewhere between 10% and 12% of all mortgage borrowers lost their homes. However, the vast majority of homeowners, representing 60% of Americans, never had a mortgage at risk.
The damage was devastating for those caught in the crossfire. Only a quarter of foreclosed households ever regained homeownership, taking an average of four years to do so. Even five years after foreclosure, only about half of borrowers had recovered their credit scores to pre-foreclosure levels. The despair among families and couples was vast.
But here is the important distinction: the GFC was triggered by reckless lending and borrowing decisions concentrated in a narrow slice of the financial industry, and most of the harm was eventually reversible. Home prices recovered. Equity came back. Life went on.
The same cannot be said for AI.
Working In AI Is Worse Than Working In Finance During The Global Financial Crisis
Think about this situation for a moment.
You are working at a hot AI company like Anthropic. They pay you a $400,000 base salary plus a $500,000 initial stock grant that vests over four years. Thanks to rising valuations and continued annual grants, your total compensation is now over $1 million a year. Whether you realize it or not, you are rich.
But here is the thing. The success of your AI company may also help displace millions of jobs. The richer you become, the poorer millions of other households become. It is essentially a zero sum game as the crushing of software companies in 2026 has demonstrated.
Compare that with most people who worked in finance during the Global Financial Crisis. Many had nothing to do with the mortgage industry. Further, a large number of finance workers were losing money themselves, while watching colleagues get laid off.
Unlike the mortgage lenders of 2007, you cannot claim ignorance. You know what you are building and what may happen if it succeeds. I’m sure you’re a nice person too, like most people in finance were. But the public will despise you for making them lose everything.
Your boss regularly goes on television and talks about how 50% of knowledge-worker jobs could be wiped out in a short period of time. The more the company can replace labor, the larger its total addressable market (TAM), and the more valuable its shares may become.
The Scale Of Disruption: What The Data Actually Says
On the more hopeful end for humanity, Goldman Sachs estimates that if AI use cases expand across today’s economy, roughly 2.5% of U.S. jobs could be displaced. In a more aggressive adoption scenario, that rises to 6%–7%.
They also argue the shock may be temporary, noting that each 1 percentage point gain in technology-driven productivity has historically raised unemployment by about 0.3 percentage points, with the effect typically fading within two years.
On the more alarming end, World Economic Forum’s Future of Jobs Report 2025, based on surveys of more than 1,000 employers representing 14 million workers, projects 92 million roles displaced by 2030 and 170 million new ones created, for a net gain of 78 million jobs globally.
The International Monetary Fund estimates 40% of global jobs face meaningful AI exposure, rising to 60% in advanced economies like the United States.
So which is it, manageable friction or civilizational upheaval? I’m leaning more toward the rough scenario. But the optimistic framing deserves scrutiny.
“Net job creation” is an aggregate statistic that masks individual pain. The headline may show +78 million jobs by 2030, but displacement spreads broadly while new opportunities cluster in a handful of industries and cities. The 51-year-old truck driver in rural Ohio does not benefit from a 26-year-old prompt engineer getting hired in San Francisco. Nor does my dad, who used to edit all my posts and is permanently out of a job since 2023.
Signs Everywhere AI Is Displacing Jobs
Unemployment among 20 to 30 year olds in tech-exposed occupations has risen by nearly 3 percentage points since early 2025, well above their peers in other fields, a sign that AI is hitting the very workers who were supposed to be safe from automation.
The ServiceNow CEO said the unemployment rate for college graduates could be 30% in a couple years. In 2025 alone, nearly 55,000 U.S. job cuts were directly attributed to AI, with Amazon, Microsoft, Salesforce, and Workday all explicitly citing AI as the reason for layoffs totaling tens of thousands of positions. Meta is planning on cutting another 10% (8,000) of its workforce in 2026.
For comparison: the GFC produced roughly 6 million foreclosures over a decade. That is devastating, but it was concentrated among homeowners who took on debt they could not afford, and most eventually recovered. Today, 41% of employers globally say they plan to reduce headcount in areas where AI can automate tasks within the next five years, and unlike a foreclosure, a job automated away does not come back when the market recovers.
Nobody knows exactly how big the disruption will be. What we do know is that even the optimistic scenarios involve enormous pain for real people, and that the workers building AI tools today will bear direct responsibility for that pain in a way that a junior mortgage officer in 2008 simply did not.
The Faces Behind the Numbers
Here are some examples of people who might be put out of a job due to AI.
A 28-year-old computer programmer who is included in one of the 20% laid off by Meta. His girlfriend dumps him as he has to go move back in with his parents. For revenge, he decides to stake out your home and throw Molotov cocktails over your gate in the middle of the night.
A 48-year-old lawyer with a stay-at-home spouse and two children. Without his $500,000 income, they need to sell their 4-bedroom house and rent. But they can’t find affordable rent, so they end up relocating to a lower-cost area of the country.
A 35-year-old 5th grade teacher with an underemployed husband and two children. The stress of losing a $95,000 teaching job due to AI becomes too difficult to bear for the 39-year-old husband who has been looking for full-time work for two years. He feels so guilty about not being able to provide for his family that he asks for a separation.
A 51-year-old truck driver with a stay-at-home spouse and one child. Self-driving trucks become commercialized and he loses his $160,000 a year job. The company does not provide a pension and goes under as well.
From customer service representatives to marketing managers, pharmacists to doctors, architects to accountants, no job is truly safe. And the workers in these occupations do not get to ride out the recovery the way a homeowner who kept paying their mortgage in 2009 eventually did. A job automated away does not appreciate back to full value over time.
The Moral Burden Is Heavier Because You Know
The loan officers at Countrywide and WaMu could at least claim they believed in what they were selling. Many genuinely thought housing prices only went up. There is also responsibility from the borrower to pay what is owed according to their contract they signed. Many were wrong and reckless, but delusion was a partial defense.
AI workers have no such defense. The displacement is not an unintended side effect of a bet gone wrong. It is a design feature baked into the pitch decks, the earnings calls, and the investor memos. “We will replace X% of your workforce with our platform and boost profits” is often the product’s core value proposition. Every percentage point of productivity gain is a percentage point of human labor no longer needed.
That is a heavy thing to carry home at the end of the day, no matter how many zeros are on your paycheck. What happened to using AI to cure cancer and other life-saving diseases?
When the revolution comes, and if projections are even half right it will, I suspect no AI worker will be safe. There is no way to claim innocence.
Remember, OpenAI was originally founded with a nonprofit mission focused on benefiting humanity. Over time, it adopted a capped-profit structure to raise the massive capital needed to build advanced AI systems, while the original nonprofit retained control.
The broader lesson is that idealism and incentives often collide. When enough money is at stake, financial interests can begin to outweigh original principles.
Survival Recommendations For People Who Work In AI
If you’re an AI employee or founder and you don’t want to get robbed, beat up, or worse when the uprising comes, here are my suggestions:
Never say you work in AI. If someone presses you, be vague. “I work in tech” is your new answer. “Software” works too. Practice saying it without flinching.
Scrub your digital footprint now, before the riots start. Remove the AI company from your LinkedIn, your Twitter bio, your Instagram, all of it. The internet has a long memory and so do angry people with time on their hands.
Stop doing media. Do not give interviews about how transformative your AI product is. And for the love of God, do not go on video gleefully explaining how AI will eliminate millions of jobs. Those clips will age very poorly and they will find you.
Develop a real grievance with AI. Think of one or two genuine ways AI has made your life or someone you love worse. Maybe it killed a creative project you cared about. Maybe it put a friend out of work. Find it, hold onto it, and lead with it in any conversation that gets uncomfortable. Empathy you have to perform isn’t empathy. Find the real version of it or people will see right through you.
Practice stealth wealth. Do not tell people where you live, what you make, or what you’re worth. Do not casually mention your stock grants, your last liquidity event, or that you’re “pretty well diversified.” Nobody should know.
Drive a boring car. A Mercedes, BMW, Porsche, Land Rover, and the likes is a magnet for resentment, especially once people connect your wealth to their unemployment. Get a Honda Civic or a Toyota Camry. Something gray. Something forgettable. If you must drive something nice, keep it in the garage in your vacation home far away from civilization.
Learn to act middle class. This is a skill. Study it. Know what things cost. Know what it feels like to worry about a bill. Be able to have a conversation about grocery prices without your eyes glazing over. The goal is to be invisible, not impressive.
Dress down aggressively in public. No designer anything. No logos. No watches that cost more than a used car. Wear a hat. Wear glasses. The less memorable you are, the better.
Cut the virtue signaling immediately. People can smell it from a mile away and it makes them angrier, not more sympathetic. Posting about AI safety or economic inclusion from your $15 million Pac Heights home isn’t going to save you. It’s going to infuriate people. Say less. Do more, or just say nothing.
Don’t cluster. AI workers have a bad habit of only socializing with other AI workers, living in the same neighborhoods, eating at the same restaurants, flying the same private terminals. That insularity is exactly what makes a group an easy target. Diversify your social circle before circumstances force you to.
Have an exit plan. Know where you’re going if your city starts to riot. A second home in a place nobody associates with tech money is not paranoid, it’s prudent.
Give back in ways that are visible to all, not just the tech community. Donating to an AI ethics nonprofit does nothing for the 51-year-old truck driver who lost his livelihood. Writing a check to the local workforce retraining center, coaching someone through a career transition, or quietly funding a small business in a displaced community actually means something. It also, frankly, gives you cover.
Learn a trade, at least at a hobbyist level. Know how to fix something with your hands. Being able to talk about building a deck or changing your own oil is social camouflage, yes, but it’s also a genuine reminder that not everything worth doing runs on a GPU.
The GFC bankers had it rough for a few years and then the world mostly moved on. If the projections are even half right about AI’s impact on employment, the backlash that’s coming will not be a few years of awkward cocktail parties and some chanting outside your office. Plan accordingly.
Reader Questions And Suggestions
Why do you think AI leaders are so gleeful in telling people millions of people will be out of work soon? Are they not afraid of their lives? What are some other tips for AI workers to survive the inevitable uprising?
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