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AI Role Distribution Explorer

Explore ESTIMATED AI role distribution by company size & industry with the AI Role Distribution Explorer. Benchmark salaries, demand, and growth trends for top AI jobs.

Data Explorer
Showing rows ★ Estimates only — see methodology below
AI Role Company Size Min (Employees) Company Size Max (Employees) Industry Median Salary (ESTIMATE) Open Roles (ESTIMATE) Growth Rate (ESTIMATE)

The AI Role Distribution Explorer is your go-to resource for understanding how AI talent is distributed across different company sizes and industries. As the AI job market evolves rapidly, professionals and employers alike need insights into where demand for specific AI roles is highest and how salaries vary depending on organizational scale. This tool leverages ESTIMATED data from LinkedIn Talent Insights, Levels.fyi, Glassdoor, and Bureau of Labor Statistics reports to provide a comprehensive view of AI role distribution, helping you benchmark career opportunities or hiring strategies.

Whether you're a job seeker evaluating opportunities, a recruiter identifying talent pools, or a hiring manager planning workforce expansion, the AI Role Distribution Explorer delivers actionable insights. For instance, Machine Learning Engineers are heavily concentrated in technology firms with 200+ employees, while Data Scientists see broader demand across finance and healthcare sectors. Smaller startups often prioritize versatile AI roles like AI Product Managers or AI Sales Engineers, while enterprise companies invest in specialized positions like AI Research Scientists or AI Solutions Architects.

The data presented here is an ESTIMATE based on aggregated hiring trends, salary surveys, and job postings from the past 12 months. Salary ranges reflect total compensation (base + bonuses), and growth rates indicate year-over-year increases in job postings and hiring activity. Use this tool to explore how AI roles scale with company size, compare industries, and identify emerging niche roles like AI Ethics Specialists or AI UX Designers that are gaining traction in regulated or user-centric fields.

How It Works

The AI Role Distribution Explorer aggregates and visualizes ESTIMATED data on AI role prevalence, median salaries, and growth trends across industries and company sizes. Use the filters at the top of the table to narrow down results by industry, company size, or role type. For example, select "Technology" and "200-1000 employees" to see which AI roles are most common in mid-sized tech firms, along with their estimated salary ranges and growth rates.

Click on any column header to sort the table by that metric—such as sorting by "Growth Rate (ESTIMATE)" to identify high-demand roles, or by "Median Salary (ESTIMATE)" to compare compensation. The "Open Roles (ESTIMATE)" column provides a rough indication of job market liquidity, helping you assess which roles have more opportunities available.

Methodology Note

All numeric data in this tool is labeled as an ESTIMATE and is derived from a combination of public sources, including LinkedIn Talent Insights, Levels.fyi compensation surveys, Glassdoor salary reports, and Bureau of Labor Statistics employment trends. The estimates reflect median values, and actual figures may vary based on geographic location, company-specific policies, and market conditions.

Open roles and growth rates are calculated based on job posting volume trends over the past year, normalized by industry and company size. Salary data includes base compensation and bonuses but excludes equity or long-term incentives. Company size ranges are aligned with standard industry classifications (e.g., 10-50 employees = small; 200-1000 = mid-sized; 10,000+ = enterprise).

Frequently Asked Questions

How accurate are the salary and open roles estimates?
The salary and open roles estimates are based on aggregated data from LinkedIn Talent Insights, Glassdoor, Levels.fyi, and Bureau of Labor Statistics. While we aim to provide realistic ranges, these figures are ESTIMATES and may not reflect exact numbers due to regional differences, company-specific policies, or rapid market changes. Always cross-reference with multiple sources for precise job market insights.
Why do some industries have fewer AI roles listed?
Industries like manufacturing or education may show fewer AI roles because adoption is still emerging compared to technology or finance. The tool reflects ESTIMATED distribution based on current hiring trends, but demand is growing across sectors. For example, AI in healthcare focuses more on product roles, while manufacturing prioritizes robotics engineers.
Can I use this tool to find salary benchmarks for a specific city?
This tool provides national-level ESTIMATES. For city-specific benchmarks, combine these insights with local salary reports from platforms like LinkedIn Salary Insights or Payscale. Cost-of-living adjustments and regional demand variations (e.g., Silicon Valley vs. Midwest) significantly impact actual salaries.
How often is the data updated?
The underlying data sources (LinkedIn, Levels.fyi, etc.) update quarterly or annually. We refresh the tool’s estimates biannually or when major market shifts occur. For real-time job postings, check LinkedIn or Indeed directly.
What’s the difference between an AI Research Scientist and a Machine Learning Engineer?
AI Research Scientists typically focus on cutting-edge model development (e.g., novel algorithms) and require advanced degrees, often working in academia or large tech R&D labs. Machine Learning Engineers build and deploy scalable models into products (e.g., recommendation systems), requiring software engineering skills. This tool highlights salary and demand differences between these roles.
How can recruiters use this tool?
Recruiters can identify which AI roles are most in demand for their industry/company size, benchmark salary offers, and prioritize hiring pipelines. For example, mid-sized tech firms may need more Machine Learning Engineers, while enterprises may seek AI Solutions Architects.
Does the tool account for remote work trends?
The ESTIMATES assume a mix of remote and in-office roles but don’t break down remote-specific data. Remote work prevalence varies by role (e.g., AI Research is often hybrid/remote; Robotics Engineers may require on-site work). Check job postings for actual flexibility.
Are there roles in this tool that didn’t exist 5 years ago?
Yes! Roles like AI Ethics Specialist, AI UX Designer, and AI Solutions Architect have emerged or grown significantly in the past 3-5 years as industries focus on responsible AI, user-centric design, and enterprise-scale deployment. The growth rates for these roles reflect their recent adoption.
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