There have been numerous recent pieces documenting the fierce battles between firms in their quest for the top-AI talent. It’s not just the traditional tech giants playing in the AI space, AI startups and other new enterprises, like Elon Musk’s xAI, have also been aggressively pursuing those with AI skills and experience. According to a JLL article, businesses are becoming hyper-focused on finding AI talent, but 87% of executives say their businesses are struggling to find people with the necessary skillsets.
Ultimately, businesses looking to expand or create new AI capabilities need to be very strategic with where they locate their AI operations, especially if they want to limit remote work. While AI talent is hard to come by, some areas have better talent supply conditions.
But where are these locations? Using resume and job postings data in Chmura’s JobsEQ® labor market information software, we get the following metrics for each Metropolitan Statistical Area (MSA) in the United States. See for yourself below.
The size of the circles indicates the number of active job ads over the last 12 months for AI positions.[1] The blue circles indicate MSAs in which online public profiles are equal to or greater than the number of active job ads over the past 12 months (and vice versa for the orange circles). This means that companies hiring for AI talent in the orange MSAs may have a harder time finding and attracting adequate talent.
Large MSAs like Washington D.C. and Dallas-Fort Worth have large supply gaps for AI talent, with their resume-to-postings ratios (“supply-demand ratios”) both below 0.4. San Francisco and Seattle, on the other hand, are two of the larger MSAs with supply to demand ratios above 1.0.
Best cities for employers and workers in AI
Employers want to locate AI operations in MSAs with sufficient supply so to be able to pick from a larger talent pool and, potentially, avoid tough wage competition. Workers, on the other hand, would aim for areas in which AI jobs are plentiful and salaries are high.
Large metropolitan areas lead the way, but AI skill supply varies
Top 10 MSAs with the most AI job ads
Starting from the workers’ perspective, the top 10 MSAs for number of opportunities based on job postings are listed above with median wage and supply-demand ratio detailed for each. Perhaps surprisingly, New York City MSA tops the list even over “tech hubs” like San Francisco.
Another peculiar trend exemplified by New York is its top employers. The employer with the most AI job ads in the MSA is not a technology firm, nor is it a technology consultant. It is, instead, a traditional bank – JP Morgan Chase & Co. In fact, nationwide, of the top ten companies for AI job postings according to JobsEQ data, there are six technology firms[2], two consulting firms[3] and two banks – JP Morgan and Capital One.
Extending the search to the top 100, you will find firms like Walmart, AT&T, Bristol-Myers Squibb, and Disney. As traditional businesses (not just tech firms) continue to demand more AI talent, this will only further increase competition intensity.
Smaller college towns also dominate
Top 10 MSAs where supply of AI skills outstrip demand
On the employers’ side, the top ten MSAs for supply-demand ratios are mostly smaller college towns (see above table). This makes sense as large universities with software development programs will have plenty of students working towards their degrees listing AI skills in their profiles. These college towns could serve as a prime source for new talent attraction efforts of large firms.
Cities focused on AI is a mix between tech hubs and other emerging areas
Top medium & large cities for AI supply-to-demand ratios
When looking specifically at larger employment centers (with populations over 500,000) we see a much different list of MSAs. The top ten in this scenario now includes tech hubs like San Francisco and San Diego, but some smaller MSAs like Tucson, Daytona Beach, and Spokane also make the list. Surprisingly, Akron, Ohio ranks number one for AI talent-to-supply ratio of all MSAs with population above 500,000. Some of these smaller MSAs’ talent supply are influenced by the existence of large state universities (e.g., University of Wisconsin-Madison), but overall, firms looking to expand AI operations may find success in these areas.
How to find this data in JobsEQ
JobsEQ’s powerful job postings and resume data make this process simple. Using these tools provides a plethora of data beyond just the number of jobs ads/resumes and location. You can see top employers, skills, certifications, occupations, schools, award type, and more. Please refer to the methodology below to replicate the data in this post, but do remember that the JobsEQ chat team is always there to help if you get stuck!
Job posting analysis (RTI)
For the job posting analysis in RTI (Real Time Intelligence), Chmura used two filter groups (although more filters could be added to refine specific estimates/populations):
Keyword filters: "Artificial Intelligence" OR "Machine Learning" OR "Generative AI"
Occupation filters: Computer and Information Systems Managers (11-3021); Management Analysts (13-1111); Business Operations Specialists, All Other (13-1199); Computer and Information Research Scientists (15-1221); Software Developers (15-1252); Computer Systems Engineers/Architects (15-1299.08); Operations Research Analysts (15-2031); Data Scientists (15-2051)
Resume analysis (Resume Forensics)
For the resume analysis in Resume Forensics, Chmura also used two filter groups:
Keyword filters: "Artificial Intelligence" OR "Machine Learning" OR "Generative AI"
Program filters: Computer Science, Engineering, Mathematics, Computer Engineering, Machine Learning, Artificial Intelligence, Data Science, Technology, Electrical Engineering, Physics, Statistics, Mechanical Engineering, Information Technology, Applied Mathematics, Computational Science, Software Engineering, Business Analytics, Information Systems, Data Analytics, Systems Engineering, Computing, Information Science, Computer Programming
Chmura used college program as a filter group to eliminate profiles that mention AI but likely do not have technical AI experience/knowledge. Using programs as a filter is better than occupations in this case since those with AI skills may not be working in a technology occupation, or they may still be in school.
Overall, this method could be further refined to obtain exact numbers, but the simple method described above is useful to obtain accurate, directional results. Chmura is actively working on adding new AI-related hard skill definitions to RTI and Resume Forensics (a few of our own AI-powered applications!) which will make analyses like this even more accurate and easy in the future.
[1] Online job ads that were active from May 29, 2023 to May 29, 2024
[2] Meta, SAIC, Google, Amazon, IBM, and Microsoft
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