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For further commentary beyond the report, see the accompanying blog post. The demand for AI experts has grown exponentially over the last few years. As companies increasingly adopt AI solutions for their businesses, the need for highly experienced, Talent search business plan, and technically-adept talent shows no signs of stopping anytime soon.
This report summarizes our research into the scope and breadth of the worldwide AI talent pool. Although these data visualizations map the distribution of worldwide talent at the start ofwe want to acknowledge that this is a predominantly Western-centric model of AI expertise.
Their number far exceeds the high-end of our measure at 22, primarily because it includes the entire technical teams and not just the specially-trained experts. We drew on two popular data sources for this line of inquiry.
First, we used the results from several LinkedIn searches, which showed us the total number of profiles according to our own specialized parameters. Second, for an even more advanced subset, we captured the names of leading AI conference presenters who we consider to be influential experts in their respective fields of AI.
Finally, we relied on other reports and anecdotes from the global community to put our numbers in greater context and see how the picture may develop in the near future. Even though we relied talent search business plan on English-language data sources, our view of the talent pool provides a good global representation of the best experts that the field currently has to offer.
For this reason, the second half of the report focuses on a qualitative assessment of talent and funding in Asia and Africa, where the reliability of our numbers drops off significantly and does not match the industry or academic output of these hotspots.
According to our broadest LinkedIn measures, we have found that there are roughly 22, PhD-educated researchers in the entire world who are capable of working in AI research and applications, with only 3, candidates currently looking for work.
In the smaller, more advanced subset, we have found that there are currently 5, AI experts in the world who are publishing and presenting at leading AI conferences across the globe and who are well-versed enough in the technology to work with teams taking to take it from research to application.
The teams that need to be filled should be able to identify a problem that can be solved with modern machine learning techniques, build and implement that solution from scratch, and then optimizing the solution to work efficiently.
In our search, our hypothetical expert must be either highly talented or very experienced in order to capture the most elite leaders, seniors, and top juniors who would be able to work on such an effort. We used two different approaches to accurately size the pool of people in the world: LinkedIn searches and identifying participants in academic conferences.
LinkedIn Using LinkedIn, we broke down these search criteria to capture a broad view of what it means to be an AI specialist. To qualify for this subset, these profiles must also have mentioned "AI" or Artificial Intelligence in addition to one or more advanced concepts, such as deep learning, artificial neural networks, machine learning, computer vision, natural language processing, or robotics.
These candidates must also be technically adept: Using these very broad parameters, we identified a total of 22, experts. In this search, we identified a number that comes very close to that of our conference presenter numbers: For our visualization, we decided to plot the less conservative estimate, in order to capture talent with potentially interdisciplinary skills.
Academic Conferences In addition to these narrower LinkedIn searches, we counted authors of published papers or posters to estimate other high-level influencers and "rising stars" in the field. In theory, these candidates are required to apply AI theories established in controlled environments to messier real-world settings.
In this talent pool, we found 5, experts who have presented a research paper in the last few years. The following conferences were prioritized in our research: We scraped researcher names from these conferences and filled out their location, experience, and education profiles using Mechanical Turk.
Dataset Biases According to our data, European and Asian countries have significantly fewer researchers than the US, the UK, or Canada, but we are the first to acknowledge that this is most likely due to LinkedIn being a predominantly Western platform. Our searches found candidates in China, in Singapore, in Japan, and in Korea.
A recent tabulation of LinkedIn users by country done by Meenakshi Chaudhary points out a large discrepancy in LinkedIn user penetration rates, even among developed countries.
The same goes for the careful examination of presentations at academic conferences. By limiting our search to several English-speaking conferences in the Western world, we risk missing other institutions where AI research and development is done:Looking to build a business or expand one you're already running?
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