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Home > News > The Job AI Can’t Kill: Why Cybersecurity Pay Is Exploding
AI is writing a flood of buggy code and learning to hack. Someone has to clean up the mess, and they’re getting paid like rock stars to do it.
Demand for cybersecurity experts has surged as AI generates a glut of new, often buggy code and as AI labs warn their models can now find and exploit software vulnerabilities. Job postings are up, search firms are turning away clients, and security executive pay packages have jumped to $7 to $8 million, making it one of the rare roles AI is creating rather than killing.
Here’s a fun twist in the AI-is-coming-for-your-job story. There’s one job AI isn’t killing. It’s supercharging it.
Headhunter Austin Cowan expected a quiet year. Instead, his firm got buried. “Roles that typically come along every 12 months, we’re seeing those roles come along every week,” he said. The job? Cybersecurity. And business has never been better.
Companies are scrambling to hire security experts, and they’re paying up to get them. Cybersecurity job postings in the first quarter were up 11% year over year, according to Glassdoor. Some executive search firms are so swamped they’re turning clients away, simply because there aren’t enough qualified people to go around.
The reason is a perfect storm of AI side effects. And it’s a great example of how a new technology doesn’t just destroy jobs. It quietly creates whole new categories of them.
Two things are driving the frenzy.
First, the “bug-pocalypse.” That’s the actual word LinkedIn’s security chief Lea Kissner used. As developers lean on AI to crank out code faster, they’re also introducing more bugs and vulnerabilities along the way. More code, written faster, means more cracks for someone to find.
Second, AI is learning to attack. Last month Anthropic unveiled a model called Mythos that’s unusually good at finding and exploiting flaws in the software running power grids, banks, and major companies. A week later OpenAI showed off similar tech. Both releases set off a global scramble, because a tool that’s brilliant at finding vulnerabilities is brilliant for defenders and attackers alike.
So you have AI making more bugs, and AI getting better at hunting bugs. Both roads lead to the same destination: hire security people, fast.
Strip away the tech and this is a classic pattern: every major technology shift creates a “cleanup economy.”
When a new tool spreads faster than the systems built to manage it, a gap opens. And gaps are where money is made. Cars created the auto insurance and repair industries. The internet created cybersecurity in the first place. Now AI is creating a second wave of it.
The smart move here isn’t just “learn to code.” It’s spotting the friction the boom leaves behind. AI is generating value at incredible speed, but speed creates mess, and mess creates demand for people who can clean it up. Whoever sits in that gap gets pricing power.
And the pricing power is real. Security executive pay packages of $7 to $8 million are becoming common, sums Cowan says “would knock someone out of their chair a few years ago.” Not AI-researcher money (those packages can hit $250 million), but a massive jump driven by a simple equation: huge demand, tiny supply. When few people have a skill the market suddenly needs, those few people set the price.
The lesson for operators and founders: don’t just ask what a new technology destroys. Ask what mess it leaves behind, and who gets paid to handle it.
Let’s keep it honest. This is one bright spot in an otherwise brutal tech labor market. The same week this hiring boom made headlines, Meta laid off about 8,000 people and Amazon cut 16,000, both redirecting money toward AI. Stripe, Snap, and Block have shed thousands too.
Security hiring, AI engineering, and AI-focused investing roles are growing, but they won’t offset cuts on that scale. And even within security, the job is changing. Engineers who wait for their “old job” to come back may wait forever.
The winners are adapting. Security engineer Brian Gaudenti struggled to find work despite a decade of experience, until he taught himself AI tools, built a portfolio with them, and landed a role on an AI startup’s security team. His take is blunt: people waiting for the old jobs to reappear “are not going to find them again.”
Two reasons. AI helps developers write more code faster, which introduces more bugs and vulnerabilities. And new AI models can now find and exploit software flaws, raising the hacking threat. Both push companies to hire security experts urgently, and there aren’t enough to go around.
Pay packages of $7 to $8 million are becoming common for top security executives, recruiters say, a steep jump from a few years ago. It’s still below elite AI researcher packages, which can reach $250 million, but it reflects fierce demand and a small talent pool.
Partly. AI is creating roles in cybersecurity, AI engineering, and investing. But these gains are unlikely to offset large layoffs elsewhere in tech. The realistic takeaway is that AI reshapes the job market, rewarding workers who adapt their skills.
Demonstrate hands-on AI skills. One security engineer landed a job after teaching himself AI tools and building a portfolio of AI projects. Recruiters say candidates who show AI fluency have strong bargaining power, while those waiting for old roles to return are struggling.
The headline fear about AI is that it eats jobs. The quieter truth is that it reshuffles them, and the reshuffling is brutal if you’re standing still and lucrative if you’re paying attention.
Cybersecurity is the clearest proof. The same technology threatening millions of jobs just made security expertise one of the hottest, best-paid skill sets in business. Not by accident, but because AI created a problem only humans can currently manage.
For founders, operators, and anyone watching their industry get disrupted: the opportunity is rarely in the shiny new technology itself. It’s in the gap the technology leaves behind. Find the mess, and you find the money.
Want more breakdowns of the strategy shifts shaping global business? Explore more on the Business Model Analyst blog.
I love understanding strategy and innovation using the business model canvas tool so much that I decided to share my analysis by creating a website focused on this topic.
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