Israel leads the world in women in AI
LinkedIn AI Talent Index finds Israeli women nearly three times more represented in AI than the global average.
A new LinkedIn AI Talent Index from March 2025 has tracked overall AI talent across several countries and industries and found that Israel is a significant player in the overall ecosystem. The country’s score is 1.65 and ranked sixth-highest worldwide, making it 65% higher than the global average.
Israel is also ranked first in industry-specific AI talent, such as Education, Financial Services, Manufacturing, and Technology, Information, & Media. The country leads globally for women in AI, with an index of 2.95, far ahead of Singapore (2.37) and others, indicating superior female participation in AI roles.
When all is said and done, LinkedIn has ranked Israel sixth globally, losing out to Singapore, Netherlands, Luxembourg, Lithuania, and Ireland. It beats out performance from other leading countries such as Germany, Canada, the United Kingdom, and the United States (the latter two ranking 10th and 11th, respectively).
The results are a testament to the country’s leadership in industry-specific indices, which sets it apart from countries like Singapore, which, while leading overall, doesn’t match Israel’s cross-sector dominance.
LinkedIn considers one of its members as “AI talent” if users explicitly add at least two AI skills to their profiles or have been employed in an AI job. Overall, the LinkedIn AI Talent Index measured three metrics: the concentration of AI talent, in which Israel came first, and then by working age (fifth place) and by working population (sixth place).
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The study’s metrics were developed to measure AI technology adoption and AI talent characteristics based on LinkedIn data. It defined an AI job as an occupation that requires AI skills to perform the job, such as Machine Learning Engineer, AI Specialist, Data Scientist, Computer Vision Engineer, or others. LinkedIn categorizes AI skills into two mutually exclusive groups: “AI Engineering” and “AI Literacy”, where the firmer refers to technical expertise and practical competencies to design, deploy, or maintain AI systems, whereas the latter refers to knowledge, abilities, and thinking competencies to effectively interact with AI technology.
