Governments are rushing to get ahead of the AI tsunami, and for good reason. Like any useful technology, AI presents huge economic opportunities for governments around the world. In fact, PricewaterhouseCoopers (PwC) estimates that AI will contribute up to $15.7 trillion to the global economy in 2030, an amount larger than the current economic output of China and India combined. PwC also provides a breakdown of where this money is likely to come from. The organization says that around $6.6 trillion could come from productivity gains and another $9.1 trillion from “consumption-side effects.”
To learn more about how much governments are spending on AI and what we can expect from government AI spending in the coming years, let’s take a look at the hard numbers.
Opportunities presented by AI
It's clear that AI will have a profound impact on the economy as a whole, which is why governments are looking to invest in giving their citizens an edge in the economic future. But they're also looking to solve problems that are unique to government.
In future articles, we’ll go into more detail about governments’ investments in areas like healthcare and national security, but one of the more interesting and tangible benefits of AI in government is that it helps overcome bureaucracy and regulation.
While some may argue that the only reason government exists is to enforce the law, many of these regulations can be difficult to understand for ordinary citizens and experienced government officials alike.
For the former, take a look at Singapore's virtual assistant, Ask Jamie. The AI tool helps citizens and businesses avail government services across around 70 government departments. Ask Jamie works through both chat and voice and aims to make life easier for Singaporeans.
The Singapore government has previously pledged to stay on the cutting edge of technology.
For the latter, I can refer you to a recent interview I did with Rick Stevens of Argonne National Laboratory. We discussed many topics related to Argonne's AI for Energy report, but the most interesting part of our conversation was about nuclear reactors.
As you can imagine, nuclear reactors are some of the most complex systems humans have ever built. They are an incredible innovation that can help us move away from fossil fuels, but they can also be extremely dangerous if implemented incorrectly.
The AI for Energy report said building an advanced nuclear reactor in the U.S. is a “lengthy, costly and complex regulatory process.” Obtaining a building permit and operating license for a new reactor in the U.S. typically takes five years, the report said, but the process can sometimes stretch out over decades.
By training on datasets of scientific literature, technical documentation, and operational data, the Multimodal LLM can help streamline and speed up the nuclear regulatory licensing and compliance process. Because so much of government’s work is about finding ways to cut through bureaucratic red tape to actually get something done, AI has the potential to completely change how government operates.
Regional Investment Strategy
While AI is a widely used tool at present, its implementation varies by region and local government, and in future articles we will further break down global spending by region.
Here’s a quick overview of what’s happening around the world with government spending on AI.
China
In July 2017, the State Council of China released the New Generation Artificial Intelligence Development Plan. Since then, the total expenditures of China’s national and local governments to implement the plan have not been made public. By 2022, the Chinese government has reportedly established 2,107 leadership funds with a registered target size of $1.86 trillion. However, according to a Zero2IPO report, by 2023, these funds have only raised a total of $940 billion. One specific regional figure we have is from 2018, when Shanghai announced it would set up a fund of about 100 billion yuan (about $14.6 billion at the rate at the time) for the development of China’s AI industry.
european union
Similar to China, the European Union also released a national plan for AI investments, called the AI Innovation Strategy. It includes a public-private investment package of around €4 billion until 2027, dedicated to generative AI. The AI Innovation Strategy calls for a range of measures, starting with the intention to create “AI Factories” across the European Union that will bring together supercomputing infrastructure and human resources to further develop AI applications. In addition, the Commission plans to make data available through the development of a “Common European Data Space.” The aim here is to improve the availability and access of high-quality data for start-ups and other innovation organizations to train AI systems, models and applications. In addition to the AI Innovation Strategy, the European Union also enacted the AI Act to establish a comprehensive legal framework for AI. Although the AI Act is not specifically aimed at innovation and growth, it aims to promote trustworthy AI that respects fundamental rights and ethical principles.
united states of america
Like the European Union and China, the United States has also developed a plan for AI in the form of the US National AI Research and Development Strategic Plan. The plan, updated in 2023, outlines a roadmap for federal AI research and development. The United States also has a National AI Initiative Act. Federal AI spending will reach $3.3 billion in fiscal year 2022, up 2.5 times from $1.3 billion in 2017. The overall US federal IT budget for 2025 is projected to be $75.13 billion, with a strong focus on cybersecurity and AI. The Department of Defense has been the main driver of AI spending, with AI-related federal contracts growing by nearly 1,200%, from $355 million in August 2022 to $4.6 billion in August 2023. The United States will also be the largest market for AI-centric systems, accounting for more than 50% of the total global AI spending.
Notable Mentions
Japan: Led by the Ministry of Economy, Trade and Industry, Japan is working with NVIDIA and other Japanese companies to unlock the economic potential of AI in the country. Japan has allocated around 114.6 billion yen ($740 million) as subsidy for the country's AI computing industry. India: The Indian government recently announced the IndiaAi Mission initiative to promote the country's AI ecosystem. Of the INR 74 billion (US$1.25 billion) investment, around INR 45 billion ($543 million) will go towards building computer infrastructure and INR 20 billion ($241 million) towards funding startups. South Korea: The South Korean government plans to invest 9.4 trillion won ($6.94 billion) in AI by 2027. The funds are meant to help the country maintain its dominance in the semiconductor industry and develop AI chips such as artificial neural processing units and next-generation high-bandwidth memory chips.
While this may not represent all investments in AI globally, it is certainly notable how much money major companies are putting into AI development.
Challenges and Barriers
Governments recognize the benefits of investing in AI, but there are some challenges to overcome, both on a national and international scale. First, some societal issues need to be resolved over time.
Most countries have a significant shortage of AI skills, and much of the existing workforce may be resistant to adopting new AI technologies. Both of these issues could be addressed through government-funded education efforts, but there are more specific issues countries need to address.
A big problem that will require significant funding to solve is that many of the legacy systems used by government agencies are not ready for AI/ML implementations, which will require a massive modernization of data, network, cloud, and cybersecurity capabilities.
Finally, the overall cost of AI infrastructure inhibits governments' ability to rapidly deploy these tools. In a recent survey, 55% of respondents said that the biggest barrier to adopting AI-enabled tools is cost. Prices for various hardware required for AI work have skyrocketed recently, and these costs are unlikely to come down anytime soon. Investing in AI at government scale requires significant upfront costs that some countries simply cannot afford on their own.
