According to Business Insider, the use of AI in HR is accelerating, with a 2025 survey by Sapient Insights Group of nearly 10,000 HR professionals finding 31% of organizations now use some form of the technology. Companies like Amazon and Siemens are already applying AI to tasks like resume analysis and job matching. This shift is creating brand new job titles that demand skills in data literacy, analytics, and prompt engineering. A separate 2026 report from Robert Half indicates companies are willing to pay higher salaries for these AI-related skills. Experts like Christina Giglio of Robert Half note this continues the historical trend of technology reshaping the workforce by opening doors to new roles.
The AI Adoption Manager
So, you’ve bought the fancy AI software. Now what? That’s where the AI Adoption Manager comes in. This isn’t a tech support role; it’s a bridge between the technology and the people who have to use it every day. They’re the ones training managers, redesigning workflows, and basically making sure this expensive new tool doesn’t just collect digital dust. As Lana Peters from Klaar points out, without this role, AI use happens in silos or gets done improperly. Think about it: how many times has your company rolled out a new system with a single email and then wondered why no one’s using it? This job exists to solve that exact problem for AI. It’s about change management for the algorithmic age.
The AI Trainer for HR
Here’s a reality check: AI doesn’t just “know” things. Someone has to teach it. The AI Trainer for HR is that someone. Ronni Zehavi from HiBob describes it as “part technical, part editorial, part quality control.” This person is curating and labeling the data the AI learns from, reviewing its outputs, and giving it feedback. They’re essentially the coach for your HR chatbot or analytics engine, ensuring it produces useful, unbiased, and on-brand results. It’s a fascinating hybrid role that requires you to understand both the mechanics of the machine and the nuances of human resources policy. You’re not just feeding data in; you’re shaping how the AI thinks about your company’s people.
The People Analytics Translator
Data is everywhere in HR now—performance reviews, engagement surveys, you name it. But raw data is useless to a CEO trying to make a strategic decision. Enter the People Analytics Translator. This person’s entire job is to turn that “raw people data” into clear, actionable insights for leadership. When is an employee ready for promotion? Which teams have a high flight risk? These are the questions they answer. Lauren Winans from Next Level Benefits highlights that beyond data skills, soft skills like ethical awareness and the ability to translate AI capabilities into strategy are crucial. This role proves that in the AI era, the most valuable skill might still be the very human one of interpretation and storytelling.
The AI Ethics and Governance Lead
This might be the most important job of the bunch. With great power comes great responsibility, and AI in HR has immense power over people’s careers and lives. The AI Ethics and Governance Lead sets the guardrails. They establish policies to ensure AI use is fair, transparent, and compliant with a growing web of regulations. Anthony Donnarumma notes this role is also called an AI governance and risk lead, focused on privacy protection and accuracy monitoring. Basically, they’re the conscience of the system. As companies in every sector, from manufacturing to finance, grapple with responsible AI, this function becomes critical. For businesses deploying complex systems, ensuring ethical operation isn’t optional—it’s a necessity to avoid legal and reputational disaster.
Look, the narrative around AI is always “robots are taking our jobs.” But this shows the other side of the coin. AI is creating new, often higher-value jobs that require a blend of human and technical skills. The common thread? Every single one of these new roles is fundamentally about managing the relationship between humans and machines. They’re about oversight, training, interpretation, and ethics. The machines might be doing more of the repetitive tasks, but we still need humans to steer the ship, ask the right questions, and ensure the technology actually helps people. That’s a trend worth watching, no matter what department you’re in.
