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The AI Blue Collar is here. Data Annotator at #4 is the factory job of the AI age. $40k/year to train the models that AI Engineers ($200k+) build.
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AI killed the 10-person startup. Founder at #9 because one person with AI agents can now do what used to require a team.
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The picks and shovels play is real. Datacenter Technician (#17) can't work from Bali, but the job isn't going anywhere.
LinkedIn says AI Engineers are #1. We yawned. Then we looked at #4.
Based on hiring data from January 2023 to July 2025, LinkedIn's Jobs on the Rise report tells a story the headlines miss. The interesting stuff isn't at the top of the list. It's buried in the middle.
The AI Blue Collar
Yes, AI roles dominate:
| Rank | Role | What It Tells Us |
|---|---|---|
| #1 | AI Engineer | Building the systems |
| #2 | AI Consultant | Calming executive panic |
| #4 | Data Annotator | The new factory floor |
| #5 | AI/ML Researcher | Pushing the frontier |
The twist sits at #4: Data Annotator.
This is the blue-collar job of the AI economy. While everyone obsesses over prompt engineering and transformer architectures, Data Annotators are doing the manual labor that makes AI work. Labeling images. Categorizing text. Teaching machines what a stop sign looks like.
Every "intelligent" model is trained on millions of data points labeled by human hands. ChatGPT didn't learn to code by reading Stack Overflow. Someone had to tell it which answers were good.
The "Fastest Growing" label hides a massive pay gap:
- AI Engineer: $180k-250k
- AI/ML Researcher: $150k-220k
- AI Consultant: $120k-180k
- Data Annotator: $35k-50k
Same industry. Same growth rate. Very different lives.
As AI deployment accelerates, demand for annotation work is exploding. This is the job that AI discourse ignores. It's not glamorous. It won't make you rich. But it's real, it's growing, and it doesn't require a CS degree.
The AI Therapists
AI Consultant at #2 sounds straightforward. Companies need help implementing AI. Consultants help them.
But here's what's actually happening: executives are terrified. They read about AI replacing 40% of jobs. They see competitors announcing AI initiatives. They have no idea what to do.
AI Consultants aren't just implementing technology. They're calming executive anxiety. They're corporate therapists with PowerPoint decks.
Not all AI roles are created equal:
- AI Consultant: ~8 years experience required
- AI Engineer: ~5 years experience required
- AI/ML Researcher: ~3 years (but PhD preferred)
- Data Annotator: Entry-level
Junior or senior? This determines your path.
The 8-year experience requirement for AI Consultants tells you something. Companies aren't hiring fresh grads to calm their AI fears. They want gray hair. They want someone who's seen technology hype cycles before and can separate signal from noise.
The One-Person Army
Three of the top 12 fastest-growing "jobs" aren't jobs at all:
- #7: Strategic Advisor/Independent Consultant
- #9: Founder
- #12: Venture Partner
Founder at #9 is the most interesting. Why are more people starting companies in an era of AI anxiety?
Because AI killed the 10-person startup.
What used to require a developer, a designer, a marketer, a salesperson, and an operations person can now be done by one person with the right AI stack. Code generation handles the engineering. AI design tools handle creative. AI writing tools handle content. AI agents handle customer support.
The barrier to starting a company hasn't just lowered. It's collapsed. You don't need funding to hire a team. You need $200/month in AI subscriptions.
Not all growth is created equal:
- AI Consultant: Working from Bali
- Founder: Working from anywhere
- Venture Partner: Working from coffee shops
- Datacenter Technician: Stuck in Virginia
The lifestyle gap between these roles is enormous.
When 56% of professionals plan to job-hunt in 2026 and 76% feel unprepared for the market (both stats from this report), betting on yourself starts looking rational. The traditional employment model feels increasingly fragile. Building your own thing feels increasingly possible.
Selling Picks and Shovels
Buried in the list:
- #11: Commissioning Manager (validates construction projects)
- #17: Datacenter Technician (installs/maintains servers)
- #22: Construction Project Lead
You know the old saying: during a gold rush, sell picks and shovels.
AI doesn't run on vibes. It runs on datacenters. Massive facilities that consume enormous amounts of power and require physical construction and maintenance. Every new AI model, every cloud deployment, every enterprise AI implementation needs somewhere to live.
Datacenter Technician is the picks-and-shovels play of the AI boom. The job isn't sexy. You won't be working remotely. But while AI hype cycles come and go, physical infrastructure needs maintenance regardless.
The AI economy runs on hardware. It's creating demand for physical labor that didn't exist at this scale five years ago.
The Weirdest Entry
Background Investigator at #15. Wait, what?
This one made us pause. Why is "person who checks if you're lying on your resume" one of the fastest-growing jobs in America?
A few theories:
Security clearances for AI defense work. As AI becomes a national security priority, more people need clearances. Someone has to verify those applications.
Gig economy trust problems. When you're hiring contractors and freelancers instead of employees, you lose the institutional trust that comes with long-term employment. Background checks fill that gap.
AI fraud detection. Ironically, as AI makes it easier to fake credentials, demand for human verification increases.
We don't know the real answer. But the presence of Background Investigator on this list suggests something interesting about trust in the AI economy.
What This Means for You
If you're in tech: The AI specialization premium is real, but the paths are different. AI Engineer requires 5+ years and pays $200k+. AI Consultant requires 8+ years and involves calming panicked executives. Pick your poison.
If you're not in tech: The AI Blue Collar is real. Data Annotator doesn't require a degree. Healthcare Reimbursement Specialist (#6) and Background Investigator (#15) are growing fast with no AI skills required.
If you're considering independence: The data supports the leap. One person with AI tools can now do what used to require a team. The founder path has never been more accessible.
If you want stability: Sell picks and shovels. Datacenter Technician, Commissioning Manager, Construction Project Lead. Someone has to build and maintain the physical infrastructure. That someone can't be replaced by software.
Our Bet
LinkedIn's report confirms AI is reshaping the labor market. But the shape is more interesting than "learn to code or get left behind."
Here's our prediction: by 2028, "AI Engineer" drops out of the top 10. "AI Operations" and "AI Systems Administrator" take its place.
We're moving from the building phase to the maintaining phase. The gold rush is ending. The picks-and-shovels economy is just getting started.
The companies that raised $100M to build AI are discovering they need to actually run it. The models need monitoring. The infrastructure needs maintenance. The data pipelines need feeding.
The glamorous jobs got us here. The unglamorous jobs will keep us going.
Data source: LinkedIn's Jobs on the Rise 2026, based on hiring trends from January 2023 to July 2025 across the United States.