AI Skills Spread Beyond Tech as Entry-Level Hiring Tightens

Companies are hiring for artificial intelligence skills across more parts of the business, while offering fewer straightforward routes from education into permanent entry-level jobs, according to an analysis released by Draup through PR Newswire.

The study, titled Macro Labor Market Trends, examines Fortune 500 job postings and tracks changes in the roles, skills and hiring levels associated with AI. It finds that AI Builder positions have grown to represent 27% of technology demand, more than twice their share in 2021. At the same time, demand for AI capabilities is appearing in departments that were traditionally less closely associated with the technology.

The findings suggest that companies are not simply adding AI specialists. They are also changing the expectations attached to support, sales, finance, human resources and other business roles.

Early-career hiring takes a less direct route

The report identifies a marked shift away from the conventional path in which graduates move directly into full-time employment. Internships and contract positions now make up 27% of early-career hiring, approximately twice their proportion in 2020.

Those roles are also lasting longer. The average internship has expanded from 3.6 months to 9.7 months, while the typical contractor engagement has increased from 7.4 months to 12.9 months. Draup presents the change as evidence that employers are relying more heavily on temporary, extended or experience-based arrangements before making permanent hires.

For people entering the workforce, that may mean a longer period of proving capability before securing a full-time position. For employers, the pattern indicates that early-career recruitment is increasingly being used as a flexible way to assess skills and meet changing needs.

AI becomes a business-wide requirement

Technology and engineering remain the functions most heavily associated with AI requirements. The analysis places AI-skill penetration at 68% in IT and 61% in engineering research and development.

However, the figures are also rising in core business teams. AI-related skills appear in 31% of support roles, 25% of sales roles, 21% of finance roles and 20% of human resources roles. This distribution indicates that AI adoption is extending beyond the teams that build or maintain technical systems.

The capabilities employers want from workers are changing alongside that expansion. Draup lists AI literacy, collaboration between people and AI systems, human judgment and precise inference among the skills growing fastest. The pattern suggests that as software takes on more technical execution, employers are placing greater emphasis on how employees interpret results, make decisions and work effectively alongside automated tools.

That shift could affect both recruitment and internal development. Workers in non-technical functions may increasingly be expected to understand AI-enabled processes, even when they are not responsible for creating the underlying systems.

The AI Builder role is changing too

The report also describes a rapid transformation inside the specialist roles responsible for building AI systems. Skills associated with newer generative AI methods are rising sharply. Requirements for large language model fine-tuning have increased 142%, agentic orchestration has climbed 128%, and retrieval-augmented generation has grown 116%.

At the same time, some practices associated with earlier stages of AI development are becoming less prominent. Manual data labelling has fallen 44%, while on-premises graphics processing unit administration has declined 35%.

Draup interprets this as a rebuilding of the AI Builder role rather than its disappearance. The pressure is greatest for people whose experience is concentrated in manual or pre-generative-AI tasks, who may need to develop newer technical capabilities as the work changes.

Pay also varies considerably according to experience and employer type. Compensation for AI and machine-learning engineers rises by about 2.6 times between early-career positions and roles requiring more than 10 years of experience. Among senior positions, product-engineering companies can pay as much as twice the levels offered by IT-services firms for comparable work.

The broader report covers six technology role families, the worldwide distribution of AI Builder talent, compensation patterns and changes in organisational structure, including flatter organisations. Draup says its workforce transformation platform is used by more than 260 global enterprises, including five of the Fortune 10, as well as Microsoft, PepsiCo, Citizens Bank and Pfizer.