2023 has been marked with the advent of mass scale adoption of Artificial Intelligence (AI). 2022 saw a record amount of investment in generative AI start-ups, with equity topping USD 2.6 billion1 (Figure 1). The first quarter of 2023 witnessed the large scale adoption of Open AI’s Chat-GPT platform which managed to scale to a million users in 5 days and a 100 million in 60 days. Other peers including Instagram (2.5 Months to 1 million users), Spotify (5 Months), Dropbox (7 Months) and Facebook (10 months) pale in comparison.
Source: CB Insights (2023), CBRE Labor & Location Analytics
This influx of capital and rapid uptake has sparked an AI race across all continents. Companies across Asia Pacific, similar to other regions, are grappling with high levels of hiring demand which far outpaces supply, in turn creating challenges for companies that need these skills for critical business objectives. Amid this highly competitive landscape, understanding where Asia Pacific AI talent is located, how to access it, and how the landscape is shifting are critical considerations for businesses as they formulate their location strategies.
What is AI?
AI is the simulation of human intelligence in computer systems by performing tasks normally requiring human thinking. With the ability to absorb extremely large datasets, AI enables speech recognition, visual perception, learning, planning, problem solving and much more.
How do we evaluate the strength of AI talent in a market?
The Asia Pacific region comprises a number of markets, each with their inherent advantages and trade-offs spanning scalability, quality, cost and diversity, among other factors. Talent in isolation therefore cannot guarantee success in a market. To create a more holistic comparison of these factors, we have measured the strength of the AI talent markets across 3 pillars: 1) AI Ecosystem & Investment; 2) University & Research Ecosystem; & 3) Talent Supply Pipeline & Growth.
AI Ecosystem: Which markets have the most AI companies and draw the most amount of investment?
China has a significant lead over all other Asia Pacific economies in terms of total investments, and has the second largest number of AI companies (Figure 2). AI companies here span the broader ambit of businesses operating in the Artificial General Intelligence, Intelligent Systems, Machine Learning, Natural Language Processing and Predictive Analytics space. India has the most companies in the AI space and the second highest level of investment after China.
Japan, South Korea, Singapore and Australia also have a high concentration of AI companies and a large amount of investment in this space. Markets with less investment and fewer companies include more nascent markets such as Indonesia, Thailand, Malaysia and New Zealand, among others.
Source: Crunchbase (2023), OECD (2012-23), CBRE Labor & Location Analytics
University & Research Ecosystem: Which markets have the highest ranked universities and highest quality of research for AI?
In terms of the quality of AI research as well as the university ecosystem, Singapore has a significant lead over all other markets in Asia Pacific (Figure 3). Australia and New Zealand follow in second and third place, although the median ranking of Engineering colleges is slightly lower than in markets such as South Korea, India and China.
Source: QS University Rankings (2023), Open Alex (2023), CBRE Labor & Location Analytics
Talent Demand vs Supply: Which markets have lower AI talent acquisition and retention risk?
The ratio of talent supply to demand (as measured by unique AI talent job postings) is one measure of the hiring risk in a talent market. Markets including Pakistan, New Zealand, Indonesia and South Korea have higher levels of talent available in comparison to the current hiring demand in these markets (Figure 4). Australia and India both benefit from larger AI talent pools, and despite high levels of hiring demand, only have a moderate hiring risk.
Malaysia and Vietnam have comparable AI talent pools to some of the markets categorised as low risk but have seen higher levels of hiring demand thereby reducing talent availability per active job role. Thailand and the Philippines have a lower availability of AI talent and relatively high hiring demand which results in higher hiring risk.
Singapore and Japan benefit from higher talent quality coupled with very high hiring demand, and are therefore two markets that have some of the highest hiring risk. China, unlike other evaluated markets, despite having a large AI talent pool (comparable only to India in Asia Pacific), has seen the highest levels of job postings and hiring demand compared to the overall AI talent pool, resulting in one of the highest levels of hiring risk across Asia Pacific.
Source: CBRE Labor & Location Analytics, Online Job Boards (Q1 2023)
Geographic Concentration: What are the established and emerging AI Talent markets?
China and India have the largest supplies of AI talent, with India’s talent growth outpacing that of China (Figure 5). Australia, Singapore, Japan and South Korea are the other established markets in Asia Pacific. However, they have experienced slower levels of talent growth in comparison to smaller markets such as the Philippines, Indonesia and Pakistan. New Zealand, Thailand and Vietnam are markets with less AI talent supply but moderate levels of talent growth, indicating potential for these markets to become larger centres of AI talent in the future.
Note: Talent Supply is measured on a log scale. India and China have significantly larger talent pools than all other markets.
Source: CBRE Labor & Location Analytics, LinkedIn Economic Graph, OECD, Recruiter Interviews (2023)
City Clusters: What are the major tech clusters for AI talent in Asia Pacific?
AI city clusters across Asia Pacific can be broadly classified into three categories (Figure 6). ‘Mega Clusters’ offer large-scale talent pools and strong city ecosystems. ‘Established Hubs’ have similar inherent benefits but offer lower levels of scalability. ‘Developing Hubs’ are upcoming city clusters that will eventually move up the value chain to become more established centres. Typically, Mega Clusters feature campus style office developments, Established Hubs feature a mix of more traditional office and co-working spaces leaning towards the former, and Developing Hubs are anchored around co-working spaces.
Source: CBRE Labor & Location Analytics
The Big Picture
Despite recent workforce reduction in the technology industry, AI will remain heavily in-demand as more companies seek to benefit from this technology. The significant imbalance between AI talent supply and demand will likely continue in the near future. Organisations hiring AI talent at scale should consider an informed location strategy that fully considers the supply and demand drivers in each market. This planning is necessary to achieve ongoing talent acquisition and retention in today’s employee-favourable market.
The Real Estate Paradigm
While choosing the right talent hub is a key success factor for companies, it is equally important to optimise for office space. Increased AI adoption and the normalisation of remote working will result in more fluid hiring and location strategies. Office spaces will continue to act as a magnet for talent, and companies will need to ensure that they continue to provide an engaging employee workplace experience to attract and retain this talent, and optimise for employee commute times and flexibility.