With the ever-growing integration of artificial intelligence (AI) in our modern life, practically every company is seeking AI experts to add to their organizations. However, since the existing talent for AI is insufficient, the competition for these experts is intense. This a huge problem for the development and implementation of AI, as evidenced by a recent poll by EY, which says the greatest single barrier for AI implementation is the lack of talent and experienced professionals.
There has been conflicting information on how limited the expertise for AI truly is. Previously, Element AI Inc., which is a Montreal-based startup, had estimated that there were less than 10,000 people in the world that had the necessary expertise to create machine learning systems. Later, Tencent Holdings Ltd., a Chinese internet giant, announced their findings on the number of AI talent around the world. They had estimated that there were 200,000 to 300,000 people who were AI researchers or industry practitioners. Tencent’s estimation is supported by LinkedIn’s 2017 Emerging Jobs Report. LinkedIn researchers have claimed that the demand for machine learning engineers have grown 9.8x since last year. This growth trumps many other high demand jobs such as data scientists and has earned the title of the #1 emerging job.
There were less than 10,000 people in the world that had the necessary expertise to create machine learning systems. - Element AI Inc.
Element AI later published a new estimate and explained their process. They had scoured LinkedIn for people who earned PhDs since 2015 and checked profiles that mention technical terms such as artificial neural networks, computer vision, natural language processing, robotics, or deep learning. These people also needed to be proficient in TensorFlow, Python, or Theano. Their research concluded that there are about 22,000 Ph.D. educated researchers working on AI and approximately 3,000 of these are currently seeking work. They also stated if the Ph.D. restriction was removed, there are at most 90,000 people globally that have the right skill sets.
Given that salaries for this kind of resource are usually more than $300,000, only a handful of companies end up hiring a disproportionately larger share of AI talent.
For companies to have their AI project dreams become a reality, the AI skills gap needs to get much smaller. An effective way to close this gap is by increasing the number and capacity of education programs in related topics. However, this alone is not nearly sufficient to make an impact, fast. In fact, in the UK, the Careers and Employability Service had predicted that before 2022, there would be a need for more than 500,00 new skilled workers in this area. For the UK to meet this need, they would have to increase their computer science graduates (or similar degrees) ten-fold. Jean-Francois Gagne, Element AI’s co-founder and chief executive officer, said it would take at least 3 to 4 years for programs that teach data science to have an impact on the talent shortage.
For companies to have their AI project dreams become a reality, the AI skills gap needs to get much smaller. An effective way to close this gap is by increasing the number and capacity of education programs in related topics.
Tech companies such as Amazon and Google are investing internationally to increase their capacities. Amazon has a lab near the University of Cambridge, and various research labs located in different cities in Germany that are focused on AI, and Google has a facility called Google Brain which is based in Mountain View, California and has satellite groups in Accra, Amsterdam, Beijing, Berlin, Cambridge (Massachusetts), London, Montreal, New York City, Paris, Pittsburgh, Princeton, San Francisco, Tokyo, Toronto, and Zurich.
It will take time for new AI graduates to emerge from the programs. In the meantime, companies can set their focus on retraining and up-skilling their existing employees. According to a survey conducted by Forbes, 63% of companies are currently providing in-house data analytics training. Employees will need to be responsive and adjust their skills as new developments happen in the AI field.
According to a survey conducted by Forbes, 63% of companies are currently providing in-house data analytics training.
There are several potential approaches to solve the AI skills shortage but they will take time. They will also require a collaborative effort from companies and governments to educate current and potential employees.
IADSS Research continues as we collect insight from the industry. Recently, we attended KDD 2019 and Strata Data Conference NY. You can follow IADSS on Twitter, YouTube and LinkedIn, or subscribe to our bi-monthly newsletter by filling the form here to stay up-to-date with the latest news.
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