Deeper Characteristics of Global AI & Big Data Talent
Demand for AI and Big Data talent has reached the 1mn mark for G500 R&D spenders in 2018.
Draup launched a systematic study to understand the deeper characteristics of Artificial Intelligence and Machine Learning talent. Our analysis shows the total global demand for AI & Big Data talent is around 1.2 million jobs as of 2018. This is deducted by triangulating open jobs across G500 top R&D spenders, AI and Big Data start-ups and service providers. Within this demand, there is an unmet demand for about 500,000 jobs.
We’ve performed a deeper analysis of the talent available in mature and emerging locations in terms of quality of work done:
- US: The Bay Area & Seattle have talent consolidation across the tech giants and start-ups while the Central and Eastern region’s talent is largely spread across start-ups. Tier-1 US locations have nearly ~44% of total employed Big Data and AI talent pool largely consolidated within the Tech giants.
- Europe: The mature AI talent pool is employed by start-ups focussed in Fintech & Health-tech industries; Tech giants have made landmark acquisitions from University labs in their Europe HQ’d centers.
- China: Chinese tech giants have the majority of their engineering teams based in Tier-1 locations; Chinese Deep learning start-ups have scaled globally during the last 2 years raising multi-million dollar late-stage rounds.
- Israel: There is a high concentration of AI talent across start-ups focused on industry-specific applications specifically Cybersecurity and Healthcare.
- India: Research labs established by large technology companies are leading the AI/ML developments in India. India is competing with global markets to grow its start-up base.
You can access the comprehensive report in Braindesk for a full in-depth analysis of university characteristics across global locations.
At Draup, we’re constantly tracking emerging trends and markets to help you spot the next big opportunity. We’re periodically updating our Insights section to track the general progression of industry trends and help you decide what avenues to explore. Our recent insights on AI and Big Data unearth the maturity of university courses in artificial intelligence.
76% of all AI courses are in ‘Horizontal Technology’ areas such as NLP, Neural Networks and Virtual Reality
Bulk of the research effort from universities is focused on ‘Horizontal Technologies’ that can be used across verticals. Outside of the US & UK, verticalized AI courses in areas such as Healthcare, Legal or Education are almost non-existent. Most of the research effort and dollars is focused on more traditional fields such as NLP and Computer Vision. The task of applying these technologies and finding use cases for them is left to the businesses, but, these organizations struggle to find the right talent to help them apply this technology in a particular context.
Keep checking back for periodic updates that cover a variety of companies, verticals, metrics, and geo-locations.