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The Global Artificial Intelligence Index

The Global Artificial Intelligence Index

Introducing the Global Artificial Intelligence Index

This is the year of artificial intelligence. The generative AI boom has shaken the balance of power between the world’s largest technology companies, opening up new possibilities for innovation across sectors and increasing the pressure for regulation. 

Within the first quarter of 2023 alone global private investment in AI reached $18 billion, up from $9.7 billion in Q4 2022. Prime Minister Rishi Sunak pitched the United Kingdom as the future home of AI regulation. Europe sped up negotiations for the EU Artificial Intelligence Act – the first-ever comprehensive AI law. China is planning to draft its own artificial intelligence law by the end of this year. And the United States raised its budget for AI research and development by 13 per cent in 2022, compared to the previous year.

Despite its enormous power to transform business, government and society, however, the state of AI development around the world is often misunderstood.

The 4th update of the Tortoise Global AI Index, out now, shows which countries are currently leading the global AI race and why. It uses a combination of absolute and relative indicators to measure both countries’ absolute AI capacity (scale) and their AI capacity relative to their population and economy size (intensity). This year, for the first time, the index reveals which countries punch above their weight – identifying the most dynamic centres of AI operating today. 

“Artificial intelligence is the new electricity: it will disrupt almost every industry and create huge economic value at the same time as threatening millions of jobs. This year’s Global Artificial Intelligence Index shows us which countries are steaming ahead in the race for AI – and which are lagging behind.” 

  • Alexi Mostrous, Editor, Tortoise Media

For Chinese leaders AI is existential. To solve the demographic challenge they need aggressive productivity growth. To maintain political control they want automated surveillance. To leapfrog US military superiority in the Pacific they dream of a military revolution. AI is the perceived key to unlocking these challenges.”

  • Tim Gordon, Founder of Best Practice AI; Trustee at Full Fact

The United States remains the undisputed leader of the Global AI Index, once again followed by China. This year, for the first time since 2019, the UK loses third place thanks to soaring Singapore. It moves to fourth, closely followed by Canada in fifth.

The US scored 100 out of 100, maintaining first place on all three main pillars – Implementation, Innovation and Investment. On Investment especially, the US is particularly strong due to high scores in the Commercial sub-pillar. This measures the level of development of the industrial environment surrounding artificial intelligence, analysing the number, scale and funding of AI commercial ventures. 

China scored 62 out of 100, maintaining a significant gap from the US and ranking second on both Innovation and Investment. Within Innovation especially, China scores particularly high on the Development sub-pillar. Contribution to open-source artificial intelligence platforms, or the number of AI-related patents filed at the national level, are used to measure the development of new techniques and advancements in AI. Our index suggests that the gap between the US and China remained unvaried this year, but widened on metrics such as private investment.

Singapore scored 50 out of 100, jumping from sixth to third place. The country scores highly on most relative indicators (e.g. number of AI professionals per million people). Measuring the geographical concentration of AI specialists, their movements and the changing supply and demand for them determines the level of capacity offered by human capital within a given nation. But even in absolute terms, Singapore has made huge advancements through explicit government efforts aimed at boosting AI across innovation, research and human capital. 

Despite being Africa’s largest economy and most populous country, Nigeria scores second to last in our index, preceded by Sri Lanka and followed by Kenya. All three countries score low on all pillars, but are especially affected by low levels of investment and poor infrastructure. From basic electricity and internet access to supercomputing capabilities and deep databases, reliable infrastructure is required to sustain the operationalisation of different AI solutions, and increase adoption.

The Global AI Index: the rankings

Key findings

The United States and China have maintained first and second place in the ranking since the Global AI Index first launched in 2019. The US tops most metrics of AI capacity by a significant margin compared to all other countries examined, including China. This is likely thanks to highly qualified talent in the sector, advancements in AI research and innovation along with large private funding going to AI startups. 

On investment, the gap between the US and China has widened considerably. The share of global private investment to AI startups in the US increased from 51 per cent ($22.5 billion) in 2020 to 53 per cent ($27 billion) in 2022, whilst China’s share dropped dramatically from 29 per cent ($12.3 billion) to just 10 per cent ($5.3 billion).

Singapore, Israel and Switzerland lead the ranking on intensity – the newest data analysis tool of the Global AI Index. Unlike the US and China, which lead the overall chart when it comes to the scale of AI development, these countries perform best when looking at AI capacity relative to their population and economy size.

Singapore’s remarkable performance on both AI Intensity and Scale confirms the country’s recent ambitions to become a global artificial intelligence hub. Research and development spending on AI by Singapore is 18 times larger than that of the US in relation to GDP, the country hosts at least 270 active AI startups (49 per million people).

On the Research and Development sub-pillars of our index, Singapore has moved from 14th place in 2020 to 3rd and 5th place in 2023 respectively, particularly because of Singapore’s per capita contribution to over the past five years is higher than the overall increase in AI research papers globally (from 212 contributions per million people in 2017 to 379 per million in 2021). 

India currently ranks 14th on the index, despite relatively low scores on Infrastructure, Investment, Research and Development. Its strong performance is mainly due to its strength in the Talent sub-pillar, where India maintained 2nd place since 2020. 

However, although India has expanded its technical workforce, it lags behind more advanced countries on AI Innovation. Across our index, India performs well across indicators that measure AI raw activity, but less so for those that measure higher level AI expertise. For example, India is first in number of contributions to all AI repositories on Github (any open-source repository concerning AI development, regardless of number of contributors or users), but only 5th for contributions to the most important, high-impact libraries that underlay the AI open-source ecosystem. 

Our findings suggest that India has the potential to become a global AI hub if it can harness its talent for more cutting-edge AI development. 

The UK moved from third to fourth place in this year’s ranking. This is likely due to Singapore’s strong rise, considering the UK’s score has largely remained unchanged. In fact, the UK holds an overall edge in Research, Talent and Commercial Ecosystem for AI.

The UK is strong in terms of inward AI investment. Between 2013 and 2022, the UK received $12.9 billion in AI investment, representing the third highest in the world, and the 7th highest per capita – over two times more than France per capita, and nearly three times that of Germany and China. 

However, compared to similarly sized economies in the region, UK-based investors are less involved in the funding of their own AI companies, especially since 2020. Our analysis shows that between 2017 and 2022, 46 per cent of the top 500 AI funding rounds were made up of mostly or entirely domestic investors in the UK. In Canada and Germany, the domestic share goes up to 51 per cent and 57 per cent, while in France it is 70 per cent. When looking at historical trends, a gradual decline in domestic investment is visible from around 2018. In 2016, 68 per cent of the 100 largest funding rounds were mostly or entirely from domestic investors. By 2022, the share had fallen to 38 per cent.

The generative AI boom

Some of this text was written by ChatGPT – can you guess which part?*

The popularity of generative artificial intelligence sent society, markets, governments and businesses into a frenzy this year. Big tech companies are pouring billions of dollars into developing their own generative models, while governments are being pushed to address the regulatory vacuum.

To make sense of where individual countries stand on generative AI capacity, we built a mini index from 10 indicators measuring published academic papers, patents and private investment specific to generative AI. Once again, the US comes first, followed by China, and the UK. 

China leads in terms of raw number of all research publications. However when looking at the most important publications, the US retains a significant edge. Areas of expertise also differ. Chinese-authored papers on Generative Adversarial Networks (a slightly older model architecture often used for image generation) are cited 62 per cent more than US ones. Conversely, US publications on text-based Large Language Model research receive 39 per cent more citations than in China. 

Overall, looking at research papers through the lens of citations and subject areas strongly indicates that although China comes first in the mini-index by raw output, it is still the US that leads on the most significant research into cutting-edge developments.

For generative AI patents, while Chinese and US applicants filed a similar number, US applicants held nearly 10 times the number of actually granted patents, putting them in the clear lead. Although South Korean applicants filed and were granted significantly more patents than the UK, the proportion of generative AI patents within AI patents of any type for the UK was significantly higher (3.4 per cent) than South Korea (1.2 per cent), suggesting a greater level of UK focus on generative AI specifically where patent development is taking place.

Finally, over 50 per cent of generative AI startups (167 out of 309 companies) are based in the US, and have taken nearly 70 per cent of global private investment. The UK and Canada are a distant second (20 companies) and third (16 companies). 

While all countries in the index show promise in generative AI, it is crucial to avoid oversimplification and recognize that the AI landscape is a complex tapestry of interdependent factors. 

*[ChatGPT wrote the last paragraph when asked for thoughts on our Generative AI mini-ranking]

How it works

The Global AI Index draws on a range of 28 different data sources, including government reports, public databases from international organisations, think-tanks and private companies, as well as Tortoise’s own research, to measure the national ecosystems that determine capacity for artificial intelligence. 

The 111 indicators that comprise the Global AI Index Index have been selected because they: 

  • Reflect publicly-available information
  • Use up-to-date data sources
  • Relate to key issues in the artificial intelligence sector

The indicators are grouped by associative themes around three main pillars and seven sub-pillars:

  • Implementation. Indicators within this pillar reflect the operationalising of artificial intelligence by practitioners in business, government and communities. This pillar contains the sub-pillars of talent, infrastructure and operating environment. 
  • Innovation. Indicators within this pillar reflect technology breakthroughs and advancements in methodology that are indicative of greater capacity for artificial intelligence in the future. This pillar contains the sub-pillars of research and development. 
  • Investment. Indicators within this pillar reflect financial and procedural commitments to artificial intelligence. This pillar contains the sub-pillars of commercial ventures and government strategy.

More information can be found in the Methodology Report on our website.

Research by the Tortoise Intelligence Team: Serena Cesareo, Joe White, Alex Inch. Edited by Alexi Mostrous.