Specialist roles grow as entry-level pathways come under pressure
Employers are increasing demand for specialised AI talent, but the bigger workforce challenge for HR may be deciding which capabilities to hire, which to develop internally and how to preserve entry-level pathways as routine work changes.
DataCamp’s State of AI Careers 2026 found AI and data job postings increased 80% over the past year after a slight decline in 2024 and relatively little movement in 2025. The rebound was concentrated in more specialised technical positions.
Job postings for AI engineers recorded the largest increase among the 25 roles analysed, rising 255% year on year, while postings for generative AI engineers grew 197%. Median base salaries for both roles exceeded US$100,000 globally, while data science managers recorded the highest median salary in the analysis at close to US$190,000.
Demand also increased for data engineers, Python developers, data architects and machine-learning engineers. By comparison, job postings for more established positions including data analysts, data scientists and business intelligence professionals grew by less than 50% year on year.
The results add to evidence that employers are placing a higher value on AI capability. AI skills command a 62% wage premium, according to PwC, while job advertisements requiring AI skills increased from about 20,000 in 2024 to 41,000 in 2025.
But technical expertise was not the only recurring requirement in DataCamp’s analysis. Communication appeared across all 25 career paths studied, alongside Python, SQL and computer science, while AI skills were identified as a core competency in 22 of the 25 roles. DataCamp said employers are increasingly seeking candidates who can combine technical capability with judgement, communication and an ability to apply insights to business decisions.
That changing skills mix presents a workforce development question for HR teams as AI alters the tasks attached to existing jobs. HRD has previously reported that entry-level roles are expected to evolve in the AI era, with separate research finding that many HR leaders expect junior employees to take on responsibilities such as validating AI decisions, interpreting outputs and escalating issues that require human judgement.
"Our new report goes under the hood of how AI is changing the jobs market to examine the myriad of different changes within this story," said Jonathan Cornelissen, co-founder and CEO at DataCamp. “AI is changing what it means to be technical and what roles are in demand, and it’s hitting younger workers hard. There’s no one narrative here, but understanding and preparing for this shift is how we put ourselves in the best place to succeed.”
The position of younger workers is one area where the data requires particular caution. DataCamp cited earlier research showing employment among workers aged 22 to 25 in AI-exposed US occupations such as customer support and accounting fell 6% between late 2022 and September 2025, while employment among older workers in the same fields increased by between 6% and 9%. The same research estimated a 16% relative employment decline among younger workers after adjusting for firm-level effects.
Since then, the Stanford Digital Economy Lab study on AI and employment has been updated with payroll data through June 2026. The researchers found employment among workers aged 22 to 25 in highly AI-exposed occupations stood 19% below where it would have been if it had kept pace with employment in less-exposed occupations. The authors also stressed that their findings are descriptive and do not by themselves establish that AI caused the difference. Overall employment remained robust, with no comparable gap among experienced workers.
Jobs and Skills Australia’s research on generative AI and the labour market has found no clear evidence so far of declining entry-level roles because of generative AI. It said displacement remained limited, with most effects involving upskilling, redeployment and changes to existing roles.
That distinction is relevant for organisations considering whether AI should reduce junior hiring or change the work allocated to junior employees. Employers have been warned against cutting early-career roles, with Gartner arguing that eliminating those positions could leave organisations more dependent on hiring experienced workers externally instead of developing talent internally.
