Estimated Reading Time: 9 minutes

Key Takeaways

• AI engineers top the fastest-growing jobs list, followed by AI consultants and strategists as the second-fastest-growing category.
• Non-technical AI roles (consultants, strategists) are growing rapidly, indicating demand extends beyond purely technical expertise.
• Supporting AI infrastructure roles—data annotators, MLOps experts, and data center technicians—rank prominently in the top 25 fastest-growing positions.
• The ‘founder’ job title surged 69% year-over-year and appears on the fastest-growing list for the first time, reflecting increased entrepreneurship amid tight job market conditions.
• Applicant competition has intensified significantly, with applicants per open role more than doubling since spring.
• 56% of workers surveyed recently plan to job hunt, yet approximately 75% felt unprepared to do so.
• Geographic demand clusters emerge in San Francisco, New York City, Boston, and Dallas for AI and technical roles.

Table of Contents

• Executive Summary
• Detailed Analysis
  • Background and Report Scope
  • AI and Technical Roles Dominate Growth
  • Broader Job Market Trends
  • Geographic Concentration
  • Job Market Challenges and Worker Sentiment
  • Skills Requirements and Preparation
  • Structural Labor Market Implications
  • Key Events Timeline
• Frequently Asked Questions

Executive Summary

LinkedIn’s Jobs on the Rise report identifies artificial intelligence-related positions as the fastest-growing job categories in the United States over the past three years, with AI engineers ranking first overall. Beyond technical roles, the data reveals significant demand for AI consultants and strategists, data annotators, and AI/ML researchers, reflecting broader organizational efforts to integrate AI across business functions. The report also highlights emerging trends including a surge in entrepreneurship, with ‘founder’ appearing on the fastest-growing jobs list for the first time, and persistent challenges in the job market where 56% of workers plan to job hunt despite feeling unprepared. Data shows applicant-per-role ratios have more than doubled since spring, while hiring remains 23% below pre-pandemic levels as of the recent past.

Detailed Analysis

Background and Report Scope

LinkedIn released its Jobs on the Rise report, an annual ranking of the fastest-growing job categories in the United States measured over the past three years. The report synthesizes labor market data from LinkedIn’s professional network and broader hiring trends to identify emerging employment opportunities. The data was released recently and represents one of the most comprehensive recent analyses of U.S. labor market dynamics in a period marked by significant technological disruption and economic uncertainty.

AI and Technical Roles Dominate Growth

The report definitively establishes artificial intelligence as the primary driver of job growth across multiple categories. AI engineers rank as the single fastest-growing job overall, with these professionals designing and implementing AI models for prediction and decision-making tasks. According to LinkedIn, the most commonly cited skills for AI engineers include LangChain, retrieval-augmented generation (RAG), and PyTorch. These roles concentrate in technology, IT services, and business consulting sectors, with the highest job density in San Francisco, New York City, and Dallas.

AI consultants and strategists rank as the second-fastest-growing category overall. Unlike purely technical positions, these roles focus on helping organizations plan and implement AI initiatives while aligning AI technologies with business goals. Common skills in this area include large language models, machine learning operations (MLOps), and computer vision. According to Laura Lorenzetti, a senior director at LinkedIn, the prominence of these roles reflects the reality that:

Integrating AI more deeply into the workplace will require people whose expertise isn’t solely technical.

Data annotators, who prepare datasets for AI model training by labeling and reviewing data according to detailed guidelines, ranked fourth on the list. AI and machine learning researchers, who design and test new models and algorithms, ranked fifth. These supporting roles highlight sustained demand for technical talent across the entire AI development pipeline, with particular emphasis on operational and infrastructure roles.

Broader Job Market Trends

While AI dominates the top positions, the report reveals growth in non-AI categories as well. New home sales specialists ranked third, while healthcare reimbursement specialists placed sixth. Strategic advisors and independent consultants ranked seventh, reflecting broader demand across multiple sectors. The complete top 25 list includes roles in advertising sales, venture partnerships, field marketing, fundraising, background investigation, data center operations, travel advisory, psychiatric nursing, quantitative research, finance, construction project management, legal research, public affairs, and benefits advisory.

A notable trend emerged in the entrepreneurship sector: the job title ‘founder’ appeared on the fastest-growing list for the first time, ranking ninth. LinkedIn reported that the share of U.S. users adding ‘founder’ to their profile surged 69% year-over-year. This growth reflects broader labor market pressures, with nearly one in five professionals who reported being unable to find new employment in the preceding year shifting to freelance work, consulting, or starting their own businesses.

People are seeing that as a way to own their career and own their next step.

Geographic Concentration

The data reveals clear geographic patterns in job concentration. Major technology hubs including San Francisco, New York City, Boston, and Dallas show the highest concentration of AI and related technical roles. Data center technician positions concentrate more heavily in Washington, D.C., Atlanta, and Columbus, Ohio. Quantitative researcher and analyst roles show strongest demand in New York City, Chicago, and Boston. This geographic clustering suggests uneven labor market opportunities across the United States, with significant concentration in major metropolitan areas and existing tech hubs.

Job Market Challenges and Worker Sentiment

Despite identified job growth in specific categories, the broader job market shows signs of strain. LinkedIn’s survey found that 56% of workers planned to seek new employment, yet approximately 75% felt unprepared to do so. Workers cited multiple barriers including uncertainty about how to stand out to employers, skills gaps, and difficulty understanding which roles they qualify for. More than 60% of the 2,000 survey respondents indicated that finding a job had grown more challenging over the preceding year, citing competition, skills gaps, and uncertainty.

The number of applicants per open role has, on average, more than doubled since the spring.

Quantitative data reinforces these challenges: the average number of applicants per open job role more than doubled since spring. Additionally, overall hiring remained 23% below pre-pandemic levels as of the recent past. This suggests that while specific AI-related positions show strong growth, the overall labor market remains significantly constrained compared to pre-pandemic conditions.

Skills Requirements and Preparation

LinkedIn and industry experts identified specific technical competencies as increasingly critical for career advancement. For AI roles, hands-on programming in Python, familiarity with machine learning libraries (PyTorch and TensorFlow), and skills for deploying and managing models in production environments emerged as priority skills. MLOps competencies—including model versioning, monitoring, cost optimization, and governance—are now considered minimum requirements rather than differentiators.

The most in-demand skills that employers are prioritizing include hands-on programming in Python, familiarity with modern machine learning libraries such as PyTorch and TensorFlow.

A broader observation from industry participants notes that job titles are becoming increasingly generalized and fluid. According to analysis cited in the report, ‘AI engineer’ now encompasses roles ranging from heavy API consumption to business solution consulting around AI-powered tools. This semantic shift suggests that career advancement requires investment in personal branding and clear communication of specific competencies, as traditional job title hierarchies become less reliable guides for career planning.

In reality, an AI engineer means anything from heavy API consumption to even business solution consulting around bots.

Structural Labor Market Implications

The report data indicates fundamental shifts in labor market structure. The rise of independent consultant, founder, and hybrid technical-strategy roles suggests that traditional IT job stability has become increasingly unreliable, with independence and entrepreneurship emerging as alternative long-term security strategies. Infrastructure and operations jobs—including cloud engineers, site reliability engineers, and platform engineers—remain in high demand due to increased backend complexity from AI adoption. However, even infrastructure roles are undergoing transformation, with new requirements for cloud-native infrastructure supporting GPUs, automation, and scaling.

From an HR viewpoint, there is a lack of linearity in career paths because of AI, and every IT skill is being pressed into a new shape.

The data further suggests that career path linearity has been disrupted by AI adoption, with every IT skill being “pressed into a new shape” by technological requirements. Data annotation and similar roles are becoming increasingly specialized, requiring domain knowledge, data quality expertise, and ethical considerations that extend beyond purely technical competencies.

Key Events Timeline

• Applicants per open job role began increasing from baseline; this period marks the comparison point for later growth metrics.
• A survey of workers regarding job search intentions was conducted; 56% indicated plans to seek new employment while approximately 75% reported feeling unprepared.
• Overall U.S. hiring measured at 23% below pre-pandemic levels, indicating persistent labor market slack despite sector-specific growth.
• LinkedIn reported a 69% year-over-year increase in users adding ‘founder’ to their profiles.
• LinkedIn released its Jobs on the Rise report, identifying AI engineers as the fastest-growing job category and establishing rankings for top fastest-growing roles.

Frequently Asked Questions

What specific salary ranges or compensation changes accompany these fastest-growing job categories?
The report does not provide detailed wage or compensation data for these roles.

How do these growth rates vary by industry sector beyond the identified technology, consulting, and healthcare sectors?
While technology, consulting, and healthcare are prominent, the report’s broader list hints at growth across sectors like finance, construction, and marketing.

What are the actual skill-to-role matching rates? That is, what percentage of workers who pursue training in these areas successfully transition into these jobs?
The report does not detail specific skill-to-role matching rates or successful transition percentages.

How sustainable is this growth trajectory? Are these growth patterns expected to continue, plateau, or decline in subsequent years?
The report highlights current growth but does not project future sustainability, plateauing, or decline of these trends.

What explains the significant gap between job-seeking intention (56%) and job-finding success among workers? Specific data on actual job transitions is limited.
Workers cited uncertainty, skills gaps, and difficulty understanding qualifications as barriers, contributing to this gap.

How do diversity and demographic representation vary across these fastest-growing job categories?
The report does not include data on diversity or demographic representation within these job categories.

What is the typical career progression pathway for workers entering these roles? The report notes disrupted linearity but does not provide clear advancement paths.
The report suggests disrupted career path linearity due to AI, implying less traditional advancement routes.

How many of the identified ‘founder’ growth instances represent sustainable, revenue-generating businesses versus side projects or entrepreneurial exploration?
The report indicates a surge in the ‘founder’ title but does not differentiate between sustainable businesses and other forms of entrepreneurial activity.

What role does remote work play in geographic distribution of these jobs, and does the report data reflect on-site versus remote positions?
The report outlines geographic concentrations but does not specifically detail the impact or prevalence of remote work in these roles.

How do educational requirements and credential pathways vary among these fastest-growing roles?
The report emphasizes specific technical skills but does not outline formal educational or credential pathways for each role.