AI is rapidly becoming a baseline expectation in hiring, showing up across job listings far beyond engineering and IT. Employers are adding language about artificial intelligence to job postings across industries, from sales and marketing to finance and operations.
New research from Indeed’s Hiring Lab shows AI references spreading rapidly across job listings, including roles where the technology is not yet central to the day-to-day work. The trend suggests AI is becoming a default qualification in job listings, despite lingering uncertainty about how roles will use it. Specifically, the data reveals that while overall hiring has cooled, AI mentions have surged 134% since 2020 to reach a high of 4.2% of all postings, with AI-related tech roles now sitting 45% above pre-pandemic levels.
White-collar roles drive most of the AI hiring language
White-collar roles are driving much of the AI language now appearing in job postings, according to Indeed’s analysis from late 2025. The concentration is strongest in office-based positions, where employers are folding AI references into roles built around software, data, and digital workflows.
The wording itself is often broad. Many listings rely on broad labels like “AI” or “GenAI,” while only a small share references specific tools such as ChatGPT or large language models (LLMs). This suggests how employers have expectations around familiarity rather than spelling out technical requirements.
For certain roles, AI enters the picture through recruitment platforms and automated hiring processes, not through the job’s core tasks.
“Employers are clearly signaling that they’re interested in what AI can do,” said Cory Stahle, an economist at Indeed’s Hiring Lab, speaking to Axios. “But a lot don’t necessarily know what they want to do with AI.”
Fluency over specialization
Employers appear to be screening for comfort with AI instead of hiring for narrowly defined AI roles.
Research from McKinsey revealed that more than 70% of skills used in today’s jobs overlap between work that can and cannot be automated, explaining why AI expectations cut across so many positions without fundamentally redefining them.
The same McKinsey report found that roughly 72% of workplace skills are shared between humans and AI. Separate research from Microsoft and LinkedIn showed 66% of leaders say they would not hire a candidate without AI skills. In hiring, AI skills now function as an early screen applied across roles.
AI on the page, gaps on the ground
While AI language is expanding in job postings, companies are still confronting workforce gaps that limit internal adoption. A Slalom survey found that 93% of companies face workforce challenges that slow AI adoption, led by skills gaps.
These findings align with the Indeed research. As skills gaps constrain adoption, employers are screening candidates for AI fluency earlier in the hiring process. Hiring language, in that sense, has become one of the fastest ways companies try to close the gap.
Davos conversations this year showed how unprepared many economies remain for AI’s impact on workers.