A radiologist staying at my Airbnb recently told me something that kept me up at night.
He was in town for a national conference on AI for radiologists. We got to talking over coffee in the kitchen—the kind of conversation that happens when two people discover they’re wrestling with the same existential questions. He was fascinated by what he was learning at the conference. So was I, but for different reasons.
“AI can read scans with greater accuracy than I can,” he said. “Than any of us can, really.”
He’d spent 13 years in training. Four years of undergraduate coursework, four years of medical school, five years of residency. The average cost of medical school alone is $235,827. When you add in undergraduate expenses, we’re talking about $371,278 total investment. Many of his colleagues carry over $200,000 in debt. And now, a machine that costs nothing to train and never gets tired can outperform them on the very task they spent over a decade mastering.
He was already planning his exit strategy. He’d built a stunning treehouse property in Costa Rica—an Airbnb perched 300 feet above the Pacific Ocean with an infinity pool and yoga platforms overlooking the water. “I’ll retire there when AI takes my job,” he said matter-of-factly. Not if. When.
What unsettled me most wasn’t his fear; it was his resignation. He was convinced there was nothing he could do about it.
That conversation stayed with me, not because it was shocking—we’ve all seen the headlines- but because I recognized something of myself in his pessimism and because I have more skin in this game than he realized.
I have a doctorate—an Ed.D. in instructional design from Teachers College, Columbia University. I earned it while pregnant with my first child, newly promoted to Director of Media and Public Relations at Montgomery College, and navigating a major family move for my husband’s job. I was facing an impossible choice: career or family? Miraculously, the college president allowed me to become the first person in the college to telecommute. It worked. That experience shaped how I think about the intersection of technology, work, and life.
I took out significant loans to earn that doctorate. The baby I carried during my telecommuting experiment is now in medical training, working his way through the long tunnel of residency and debt towards a profession that is itself in the crosshairs of AI.
My younger son is neurodivergent. He works part-time as a cashier in a grocery store while taking college classes at a pace that works for him, quietly building skills and confidence in a sector where automation is rapidly changing what “entry-level” looks like.
So when I think about AI disrupting jobs, this isn’t theoretical for me. One child has invested years and borrowed heavily for a career that may be reshaped by algorithms. The other works in one of the job categories the Bureau of Labor Statistics says will decline by 10.6% by 2033. That’s 350,000 fewer cashier jobs. His job faces an 88% automation risk.
I’d been losing sleep over AI for months before that radiologist sat in my kitchen. Refreshing news articles about the latest ChatGPT features. Watching every announcement from OpenAI, Anthropic, and Google with a mixture of fascination and dread. Every new AI capability felt like another nail in the coffin of professional relevance—not just mine, but my sons’ too.
If this could happen to radiologists—physicians who’d invested over a decade and hundreds of thousands of dollars into their specialized expertise—it could happen to anyone.
It could happen to you. It could happen to the people we love most.
The Paralysis of Productive People
I spent months in a state of low-grade panic. I’d catch myself mid-task thinking, Could AI do this better? Would I need to completely retrain? Should I go back to school? What skills would even matter in five years?
Here’s what I finally realized: I was wasting energy on worry when I should have been channeling it into fear.
That might sound like a semantic game, but the distinction changed everything for me.
Worry is anxiety about uncertain future events you can’t control. It’s mental spinning. It’s “what if” scenarios that multiply like rabbits in your brain at 3 a.m. Worry asks: “What if AI takes my job?” Worry keeps you scrolling Reddit threads about which professions will be automated next. Worry is passive. Worry is exhausting.
Fear is recognition of a present danger that demands action. It’s productive emotion. It creates urgency. Fear asks: “What do I need to do right now to protect myself?” Fear respects the danger while refusing to be paralyzed by it.
And here’s the thing that finally broke me out of my worry spiral: the debate about whether AI should replace workers is irrelevant. The market has already decided. AI isn’t coming for our jobs—it’s already here.
Americans have adopted AI at higher rates than most other countries. We’re already using it. The question of “should this be happening?” is a waste of your time because it is happening, whether we’re ready or not.
Consider the cashier. According to the U.S. Bureau of Labor Statistics, cashier employment will decline by 10.6% by 2033. That’s approximately 350,000 fewer jobs. Between 2019 and 2023, the number of cashiers in general merchandise retail decreased by 23% while total employment actually grew by 3%. We’re not talking about a distant future scenario—we’re talking about jobs that have already disappeared while we were debating whether they should.
Cashiers face an 88% automation risk. Six to seven-and-a-half million retail jobs could be automated in the coming years. These aren’t projections. They’re trends already in motion.
So yes, if you’re worried, I understand. But spending more time worrying is just burning energy you could be using to adapt.
The real question is: are you afraid? Because you should be. And I mean that in the most productive way possible.
Why Your Fear Is Justified
I have an older relative in her late eighties who has been targeted by financial scams more than four times in the past year. Six different bank accounts, two different banks.
She grew up in an analog world where answering the phone or opening the door was a gesture of trust, not a calculated security decision.
That mindset meets a digital landscape where fraud is a billion-dollar industry, and where AI can clone a voice from just a few seconds of audio – less time than it takes to say, “Hi, I need your help.” In 2023, senior citizens lost $3.4 billion to financial scams—that’s a 14% increase from the year before. Since 2024, seniors have been defrauded of over $1 billion specifically from AI-powered scams alone.
Voice-cloning and imposter scams have surged. Over 845,000 imposter scams were reported in the U.S. in 2024. More than 25% of adults surveyed said they’d been targeted by an AI voice-cloning scam in the past year alone.
But this vulnerability isn’t unique to older generations, though. We’ve all made ourselves vulnerable—we’ve just done it differently.
Think about your home right now. How many connected devices do you have? Smart locks, smart thermostats, streaming services on your Smart TV, smartwatches, fitness trackers. The average American household has over 10 connected devices. That’s 10+ entry points for bad actors to infiltrate your network.
How many of us actually change our router passwords from the factory defaults? How many use password managers instead of recycling “Fluffy2019” or our kids’ birthdays across multiple accounts? How many separate our IoT devices onto different networks to minimize exposure?
Not many, I’d argue. And that’s why security experts believe adversaries are already inside our home networks, quietly waiting for the right moment to launch a coordinated attack.
We’ve seen glimpses of what this could look like. Remember when a ransomware attack shut down the Colonial Pipeline in 2021? In just a few days, gas stations across the Southeast ran dry. Panic buying. Price gouging. A major infrastructure artery brought to its knees by digital attackers demanding payment.
Small-town hospitals without robust cybersecurity systems face this regularly now. Their patient records get locked behind ransomware. When you have a dying patient and no access to their medical history, their medications, their allergies—do you pay the ransom? Most do. Because what’s the alternative?
Here’s what keeps me up at night: we’ve embraced convenience without considering consequences. We’ve adopted tools—both at home and at work—without understanding them. We’ve assumed someone else would figure out the security part, the transition part, the “what happens to humans” part.
We’ve made the same mistake with our careers that we made with our connected devices: we’ve created vulnerabilities we don’t even know exist.
That’s not a failure on your part. It’s just reality. The pace of change has been too fast for most people to keep up with while also, you know, doing your actual jobs.
But ignorance—even innocent, understandable ignorance—won’t protect you.
From Paralysis to a Practical Plan
So yes, your fear is justified. Mine was too. The question is: what are you going to do about it?
I got angry first. Then I got strategic.
I decided to stop consuming anxiety-inducing content about AI and start creating solutions instead. I enrolled in an AI for Learning course. I started analyzing my own job with brutal honesty, asking questions I wasn’t sure I wanted the answers to: Which parts of what I do could AI do better? Which parts could AI do faster? Which parts make me irreplaceable?
The process was uncomfortable. Nobody likes examining their professional value with that level of scrutiny. But here’s what I discovered:
Job security in the age of AI isn’t about being AI-proof. It’s about being AI-augmented.
It’s about understanding what to delegate to technology and what to double down on as uniquely human. It’s about making yourself indispensable in a new way—not by competing with AI, but by partnering with it strategically.
There’s a methodology to this analysis. You can identify your “strategic moat”—the work that only you can do, the value that can’t be replicated by algorithms. You can create a partnership with AI instead of viewing it as competition.
But first, you need to know what that looks like for your specific role.
I spent the last few months creating a framework for exactly this analysis. I broke down jobs—including my own—into discrete tasks. I evaluated each task for AI augmentation potential. I identified which tasks to automate completely, which to augment with AI assistance, and which to protect as human-only territory.
The results surprised me. They’ll probably surprise you too.
Some things I thought were “safe” turned out to be highly automatable. Some things I assumed AI would replace turned out to be exactly where my strategic moat was strongest. The exercise forced me to articulate value I didn’t even realize I was creating.
What’s Coming Next
In my next post, I’ll walk you through how I did this analysis. I’ll show you how to identify your strategic moat—the work that makes you irreplaceable even as AI capabilities expand. And I’ll share a tool I’ve built to help you do this evaluation for your own role.
Because here’s the truth: your job is changing whether you like it or not. AI adoption isn’t slowing down. The automation trends aren’t reversing. The question isn’t if your role will be affected—it’s how you’ll respond when it is.
Worry is paralysis. Fear is preparation.
AI is not the enemy. Ignorance is. The most dangerous thing you can do right now is nothing.
So stop worrying about whether AI will take your job. Start fearing what happens if you don’t figure out how to evolve with it. Start planning. Start analyzing. Start acting.
Next month, I’ll show you exactly how to audit your own job for AI vulnerability and opportunity.
Until then, ask yourself this: Which parts of my job would I actually want AI to take over?
Your answer might surprise you. Mine certainly did.
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Author’s Note: I’ve spent my career creating safe spaces for people to practice high-stakes scenarios. Twenty years ago, I built virtual worlds where emergency managers could practice responding to disasters without real-world consequences. Now I’m building AI tools where professionals can practice transforming their careers without risking their livelihoods. The technology changes. The need for safe practice spaces doesn’t.