Hiring Managers Name the Top Five AI Jobs Growing Fastest Into 2026

AI’s next hiring wave is forming at the entry level. A new Study.com survey of US hiring managers named security, research, data science, and generative AI as the fastest-rising roles for newcomers heading into 2026.

The report detailed mounting shortages in robotics, generative AI, and AI governance, showing where early-career demand is expected to build next.

The five starter jobs moving to the front of the AI pack

Hiring managers said five early-career roles are rising fastest as companies expand their AI operations for 2026, spanning security, research, data work, creative production, and model training support.

“Study.com’s data shows that entry-level AI work is diversifying fast, with top-growing roles ranging from AI security and research support to generative-AI content and data annotation,” Stacy Redd DeMartini, director of content & services at Study.com, told eWeek in an email.

• AI security and risk analyst (49%): The most in-demand entry-level role in the study, these analysts monitor AI systems, assess risks, review compliance gaps, and support incident response as businesses embed models in more products and services.
• AI research assistant (42%): Research assistants help AI teams propel development forward by preparing datasets, running experiments, reviewing literature, prototyping models, and evaluating results across fast-moving R&D pipelines.
• Junior data scientist (34%): Junior data scientists handle foundational analytics work, including data cleaning, exploration, baseline modeling, visualization, and feature engineering, that prepares larger systems for production.
• Generative AI content creator (32%): These creators generate and refine AI-produced text, images, and audio, test prompt strategies, and collaborate with design and marketing teams as companies scale automated content pipelines.
• Data annotation specialist (27%): Annotation specialists label and review data used to train AI models, supplying the high-quality inputs that supervised systems still depend on as complexity and scale grow.

Collectively, they showed how early-career hiring is concentrating around the core engines of today’s AI systems.

Talent gaps companies expect to widen

According to the study, several AI fields are heading into 2026 with far more demand than available talent.

Robotics and automation topped the list at 70%, as companies seek professionals who can design, test, and maintain automated systems across manufacturing, logistics, and service operations. Generative AI followed at 67%, driven by the push to produce and refine AI-generated text, images, and other content at scale.

Shortages are also forming in AI governance and compliance at 52%, reflecting the growing need for staff who can navigate responsible AI use and new regulations.

Thinner pipelines in computer vision (48%), natural language processing (NLP) (37%), and applied AI in industry (26%) rounded out the areas where specialized talent remains hardest to find.

What newcomers are expected to bring to the table

Hiring managers wanted early-career candidates who can handle the fundamentals. Data preparation and analysis led the technical list at 62%, followed by hands-on experience with generative AI tools at 58%.

Cloud basics such as moving prototypes to AWS or Azure come in at 55%, and responsible AI and safety knowledge sit close behind at 51%. Low-code tools and domain-specific know-how completed the skillset managers said helps newcomers contribute quickly.

Soft skills carry almost equal weight. Adaptability came in first at 66%, alongside problem-solving and communication at 50% each. Employers also value creativity, ethical decision-making, and basic project management, traits they said help junior hires work across teams and in fast-moving development cycles.

Skill-building routes companies lean on for early-career hires

“Employers say practical skills matter most — on-the-job training and certifications now outrank traditional degrees,” DeMartini said, pointing to the survey results:

• On-the-job training or apprenticeships (67%): Real projects and direct feedback remain the most valued path for developing applied AI skillsets.
• Industry-recognized certifications (61%): Credentials from providers like Google, AWS, and Microsoft give employers confidence in a candidate’s technical grounding.
• University coursework (58%): Computer science, math, and data analytics programs still serve as solid foundations for many entry-level hires.
• Online or self-paced learning (52%): Flexible platforms help candidates build literacy in AI tools and data workflows at their own pace.
• Mentorship or coaching (46%): Guided support from experienced practitioners strengthens newcomers’ judgment and problem-solving skills.

“Nearly half of hiring managers report that portfolios carry as much weight as education, highlighting how hands-on experience is becoming essential for AI newcomers,” DeMartini added.

Separating strong applicants from the pack

When résumés start to look alike, hiring teams fall back on a few clear signals.

Industry-recognized certifications stood at the top at 49%, giving employers confidence in a candidate’s technical grounding. Personal project portfolios followed at 39%, offering visible proof of applied skills that go beyond coursework. Internships and freelance experience came in at 37%, while domain knowledge in areas like healthcare, finance, or education helped another 33% of candidates stand out.

Managers said the hiring process still comes with obstacles, such as competing offers, salary mismatches, applicants with too much theory and not enough practice, and limited diversity across candidate pools.

Most early-career recruiting happens on LinkedIn (70%) and Indeed (57%), and more than half of entry-level roles are expected to follow a hybrid work model (52%) as teams blend on-site collaboration with remote flexibility.

For jobseekers, the next year may bring clearer routes into the field, but also higher expectations as employers look for candidates who can contribute on day one.

New findings from McKinsey hint at a wider transformation ahead, estimating that as much as 50% of US jobs could be automated if businesses fully embrace AI tools and robotics.