Two surveys I wanted to share.
As the demand for artificial intelligence systems evolves, the need for specialized data labelers is becoming increasingly apparent. According to HireArt’s 2025 AI Trainer Compensation Report, generalist data labelers are being overtaken by subject-matter experts, who now command significantly higher pay rates due to their specialized skills. For instance, entry-level trainers in the United States earn between $12.50 and $15.50 per hour, while experts in fields like medicine and engineering can earn anywhere from $60 to over $180 per hour.
Automation is reshaping endpoint management for managed service providers, enabling them to shift from a reactive approach to a proactive strategy. According to the 2025 EMEA Managed Service Provider Benchmark Report by Kaseya, nearly three-quarters of providers anticipate revenue growth over the next three years, yet 45% face challenges related to staffing and skills shortages. As networks become more complex, the shift to automation is not merely a trend but a necessity, allowing providers to prevent issues before they occur and maintain service quality amidst rising expectations.
Why do we care?
Here’s the part that’s easy to miss if you’re skimming the numbers.
Those AI trainer rates aren’t about labeling clicks. They’re about turning professional judgment into infrastructure. Someone is being paid $120 an hour because a wrong label in medicine or engineering isn’t a bug—it’s a liability.
Now connect that to MSP automation.
As endpoints get more autonomous, fewer humans touch them day to day. That sounds efficient, until you realize every decision the system makes is based on yesterday’s data model. If the asset inventory is wrong, if the classification is sloppy, if the exceptions aren’t curated, automation doesn’t save you—it accelerates the mistake.
The MSP behavior that causes harm here is treating data prep and data maintenance as “included.” That’s how you end up eating hours, missing failures, and arguing with clients about why the system said everything was fine.
This matters now because customers are being sold outcomes—secure, stable, automated environments—without understanding that those outcomes depend on constant, expert data work. The provider who names that, prices it, and owns it doesn’t just reduce risk. They become indispensable.