6 new insights into AI research – dig into the data for your country

Elsevier’s analyses reveal the sectors and fields getting the most attention in Asia, Europe and the United States – and what this means for policy and the workforce

AI main image
Selected AI-relevant policies and events (upper panel) and technology breakthroughs (lower panel), 1998-2018. (Source: Artificial Intelligence: How knowledge is created, transferred, and used, Elsevier 2018)

Whether you’re doing research or making decisions about it as a research leader, policymaker or funder, it’s important to understand where artificial intelligence (AI) is headed.

By focusing on AI research in Asia, Europe and the United States, Elsevier’s report Artificial Intelligence: How knowledge is created, transferred, and used aims to help you navigate this rapidly evolving field. The report delves into research output, collaboration and mobility, revealing trends on a country and international level.

You can download the report and delve into the data in Elsevier’s AI Resource Center.

Here are some insights the report and follow-up analyses revealed about individual countries.

1. India is the third most prolific country in AI research

India is the third most prolific country in artificial intelligence research, after China and the US. More than half of the research output in India comes from conference papers.

The report noted the rapid emergence of India, which is now the third most prolific country for AI publications after the US and China. This growth is being driven by a strong academic sector and rising collaboration within institutions. At the same time, national collaboration is declining and international collaboration remains low.

India’s AI performance is marked by a strong academic sector and rising institutional collaboration but declining national collaboration and low international collaboration. In the chart on the right, the size of the circles represent the field-weighted citation impact of publications resulting from each collaboration type.

Meanwhile, India’s government has also been supportive of AI and its economic potential. Last year, India released a report detailing its national AI strategy.

2. China, the EU, India and the US are growing – but not equally

Share of each country’s publications in AI, all document types, relative to global AI publications output.

There are strong regional differences in AI activity. Europe is still the largest actor in AI research, despite rapid growth and ambition from China, while the US has been regaining ground in recent years.

China has produced more than a quarter of global AI publications in recent years, coming from less than 10% two decades ago.

Meanwhile, there are significant differences in citation impact, with the United States leading; however, the three regions have similar download impact, suggesting comparable usage of each region’s research.

A comparison of field-weighted citation impact (FWCI) and field-weighted download impact (FWDI) in various countries from 1998 to 2017.

While China’s field-weighted citation impact (FWCI) is still below that of Europe and the United States, it shows tremendous growth over the past two decades, from half the world average to reaching the world average in recent years. In contrast, India’s has decreased overall during the same period.

Europe’s FWCI remains stable over the period, comfortably higher than the global average. The United States’ FWCI is high, between one and a half to two times as high as the global average. The 2016-17 dip in FWCI for the US may be due to incomplete citation data, although there seems to be a slight decreasing trend following a 2014 peak.

3. In Japan and the US, a significant portion of AI research comes from the corporate sector.

Annual Japanese AI research output by sector type, 2013-17 (Source: Scopus)

Japan is among top nations in terms of AI research. The advanced manufacturing sector, service industry, health sector, and agricultural sectors of Japan are all to benefit from the use of AI technologies.

While three quarters of Japan’s AI research involves the academic sector, the corporate sector’s contribution is high at 10%. This percentage is higher than China’s at 3% and slightly lower than the United States’ at 13%. Government institutions were involved in 14% of Japan’s AI research in 2017 (up from 12% in 2013), reflecting the national importance of the topic from the government’s perspective, with notable contributions from RIKEN and the National Institute of Advanced Industrial Science and Technology (AIST).

With the Society 5.0 vision, Japan has an important role to play in showing how AI can benefit society. However, challenges lie in the investments in the area, human resources, the uptake of results by different sectors, and leveraging the benefit of strategic international collaborations.

4. In China, it’s easy for AI graduates to find a job; few pursue PhDs or go abroad

The most common subject areas related to AI at the Institute of Automation, Chinese Academy of Sciences, and types of graduate outcomes.

In China, university and research institutes are responsible for helping students find work by contacting employers or creating job-hunting plans for undergraduates and graduates. At the Institute of Automation, Chinese Academy of Sciences (IA, CAS), most graduates benefit from being sent directly to work – either in positions the institution finds them or jobs they find themselves.

At that institution, there are five common subject areas related to AI: control engineering; control theory and control engineering; pattern recognition and intelligent systems; computer application technology; and computer technology. Pattern recognition and intelligent systems has the largest number of graduate students followed by computer application technology and control theory and control engineering.

Overall, it seems easy for graduates in AI to find a job in China, and few pursue PhDs or go abroad.

5. Low international collaboration levels in China point to potential isolation

The greatest percentage of Chinese AI research output comes from institutional collaboration. While international collaboration is on the rise, it remains low. In the chart, the size of the circles represent the firld-weighted citation impact of publications resulting from each collaboration type.

Collaboration is key to expanding the reach and impact of research. In China, low international collaboration levels point to potential isolation. This isolation is reflected in the relatively low mobility level of China’s AI researchers, the vast majority of which are not internationally mobile. China has a very high level of sedentary researchers with a rather low relative citation impact and relative productivity compared to migratory or transitory researchers.

On top of the approximately 25% of AI researchers that come to the country, 17% stay for more than 2 years but still bring productivity and impact benefits. Through short- and long-term researcher mobility, China is gaining in relative productivity and relative impact.

Mobility and collaboration also occur across sectors. An analysis of recent cross-sector movements within China reveals 80% more researcher movements from the academic to the corporate sector than reciprocally but a more balanced distribution of researcher movements between Chinese academia and international industry and Chinese industry and international academia. This suggests that within China, the corporate sector is attractive to AI researchers.

6. The UK is a major player in AI research

Annual AI research output in the UK by publication type, 2013-17 (Source: Scopus)

In 2017, the UK ranked 4th globally in volume of AI research publications, behind China, the United States and India, confirming that the UK is a major player in the field. However, AI research in the UK has been growing at a lower annual rate (11%) than that of the global corpus of AI research (13%). This growth could be accelerated by more collaboration, which has been shown to expand the reach and impact of research in other countries.

As in other countries, UK AI research is not confined to research articles, and outputs embrace many forms, in particular conference papers, which represent more than half of the UK’s AI research output in recent years.



Written by

Sarah Huggett

Written by

Sarah Huggett

Sarah Huggett is Head of Analytical Services APAC at Elsevier, based in Singapore. She leads a group providing consultative services to government agencies, funding bodies, policymakers and research institutions planning for the future. Her team analyzes research performance to offer insights and recommendations to research leaders.

Sarah’s first job at Elsevier, in Research & Academic Relations in Oxford, UK, gave her expertise in using data to inform strategic planning. She has a particular interest in new developments in research evaluation, such as measures of attention and engagement. After completing a bachelor’s and master’s degrees at the University of Grenoble, France, Sarah moved to the UK to teach French at the University of Oxford, prior to joining Elsevier in 2006.

Written by

Alison Bert, DMA

Written by

Alison Bert, DMA

As Executive Editor of Strategic Communications at Elsevier, Dr. Alison Bert works with contributors around the world to publish daily stories for the global science and health communities. Previously, she was Editor-in-Chief of Elsevier Connect, which won the 2016 North American Excellence Award for Science & Education.

Alison joined Elsevier in 2007 from the world of journalism, where she was a business reporter and blogger for The Journal News, a Gannett daily newspaper in New York. In the previous century, she was a classical guitarist on the music faculty of Syracuse University. She received a doctorate in music from the University of Arizona, was Fulbright scholar in Spain, and studied in a master class with Andrés Segovia.

Related stories


comments powered by Disqus