The long-term potential of AI to change key aspects of the way we live and to support the operation of businesses, governments, and other organizations is hard to grasp. But even today, existing and proven AI applications can potentially create value for economies and societies around the world.
Indeed, AI has contributed to improvements in quality of life for all segments of society through innovations such as predictive healthcare, adaptive education, and optimized crisis response.
The National Health Service in the United Kingdom, for instance, set up a National COVID-19 Chest Imaging Database containing a shared library of chest X-rays, CT scans, and MRI images to support the testing and development of AI technologies to treat COVID-19 and a variety of other health conditions.
Businesses have seen increased productivity and operational efficiency through the use of autonomous robotics in manufacturing, AI-optimized supply chains, and intelligent cargo routing with autonomous vehicles, among other initiatives. For example, many logistics companies are using AI-powered sorting robots to optimize their warehouse operations. Governments can also harness the power of AI through personalized services and automated processes. Consider Singapore’s “Ask Jamie,” a virtual assistant that helps citizens and businesses navigate government services across roughly 70 government agencies through AI-powered chat and voice.
But governments face numerous barriers—including a lack of specialized talent, limited investments in AI research and innovation, and often-unclear regulations designed to ensure that AI is applied in an ethical, secure, transparent, and human-centric manner across all sectors—that could prevent them from adopting AI use cases and capturing the value of AI. Indeed, when developing and deploying AI use cases, it is critical that governments proactively consider and address the fast-changing universe of privacy and the security risks and ethical pitfalls that AI technologies can expose them to.
Below, we share three steps to measure the potential impact of AI in a country, and we examine how this could play out in a handful of countries. We also review a range of initiatives that could help governments overcome current challenges and capture this value throughout their economies. These initiatives include launching programs in the areas where AI could have the most impact for the country, creating a vibrant AI ecosystem, and considering appointing an AI authority, as some countries have already done.
Measuring the potential impact of AI in a country
AI may mean different things to different people, but here, we use the term “AI” to refer to a subset of data analytics. AI systems include computer vision, natural-language processing, and advanced robots. They are both autonomous (performing complex tasks without human supervision) and adaptive (improving by “learning” from more data).
In September 2018, the McKinsey Global Institute modeled trends in AI adoption, using early adopters and their performance as a leading indicator of how businesses across the board may want to absorb AI. In the aggregate and netting out competition effects and transition costs, early evidence suggests that AI could potentially deliver an additional global economic output of about $13 trillion by 2030, boosting global GDP by about 1.2 percent a year.
However, while it’s generally understood that AI holds a great deal of potential, it can be difficult to measure and track the impact of AI in a specific country in a structured manner that can be replicated. Below is a methodology that could help governments estimate this potential (see sidebar, “Considerations when quantifying the impact of AI”).
- Identify the most relevant use case domains. Our research suggests that the hundreds of AI use cases that have the potential to unlock value in countries can be grouped into 15 domains, which can inform efforts to measure impact (Exhibit 1). While each of these use case domains includes numerous AI applications, the underlying technologies and mechanisms through which they create value are similar, as is their typical impact when applied across like organizations.
It may be useful to determine which use case domains are the most relevant for businesses and organizations across sectors of the economy. For example, the most relevant domains for manufacturing are yield, energy, and throughput (where AI could enable predictive machinery maintenance and resource productivity maximization) and integrated supply chain optimization (including demand forecasting and inventory optimization).
- Estimate the impact of use case domains. Using benchmarks, the average financial impact of relevant domains can be identified at the company level or organizational level per priority sector. For example, if predictive maintenance in manufacturing reduces maintenance costs by 10 percent on average, it would improve a company’s EBIT by 2 percent.
- Scale up impact to the sector and economy level. Suppose that for one manufacturing company, all relevant use case domains combined can increase EBIT by 10 percent. If total EBIT for all companies in the sector is $10 billion, then that EBIT would rise to $11 billion. If net operating surplus (approximated by EBIT) accounts for 50 percent of gross value add (GVA)—that is, contribution to GDP—in the manufacturing industry (which would total $20 billion), an industry-wide 10 percent EBIT increase from AI would increase the sector’s GVA by 5 percent. Once the impact at the sector level is understood, it can be scaled up to the total economy level by adding up the impact of all sectors.
Of course, governments must carefully consider and address the potential risks of implementing AI technology. These risks include the following
- Privacy. Is the privacy of customers being protected through adherence to local and global data privacy regulations?
- Security. Is the AI model comprehensively protected against cybersecurity vulnerabilities and risks?
- Fairness. Is the AI model fair and unbiased toward all segments of customers?
- Transparency and explainability. Is it possible to explain how the AI model works and the methodology it uses?
- Safety and performance. Has the AI model been adequately tested to ensure that the desired safety and performance are delivered each time?
- Third-party risks. Are all third-party vendors and partners following the required risk mitigation and governance standards?
Methodology in action: The potential impact of AI across Gulf Cooperation Council countries
Many countries in the Gulf Cooperation Council (GCC)—which comprises Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates (UAE)—are working to diversify their economies away from oil, modernize them, and increase efficiency through technology. AI is one of the technologies that many GCC countries are betting on. For example, in October 2017, the UAE government launched the UAE Strategy for Artificial Intelligence, one of the first of its kind in the region.
Similarly, in October 2020, the Saudi Data and AI Authority in Saudi Arabia launched its National Strategy for Data and AI with the ambition of elevating the kingdom as a global leader in the elite league of data-driven economies.
When applied across all GCC countries, our methodology reveals a $150 billion potential value across all sectors of their combined economies. Our analysis shows that AI could potentially add value corresponding to 6 percent or more of each economic sector’s GDP in GCC countries.
Indeed, across GCC countries, the methodology suggests that AI could play a transformative role in the public sector and manufacturing, with a 12 percent and 15 percent impact potential (percent of GDP), respectively. Given that oil and gas is the largest sector in most of these economies, our analysis also reveals significant potential value there; however, investing in new AI technologies could also be an opportunity to accelerate a necessary diversification away from oil and gas and modernize other high-potential sectors as the world gradually shifts away from fossil fuels.
This impact comes from different use case domains depending on the sector. For example, in the manufacturing sector, large productivity gains could potentially be achieved from predictive maintenance, whereby fewer, more-targeted maintenance activities reduce downtime both from failures and from maintenance itself, which increases production at lower costs. Advanced robotics could also play an important role in this sector, and significant value may be captured through data-driven supply chain optimization—for example, through better demand forecasting that improves product availability, inventory costs, and overall production costs.
In the public sector, successful AI implementation could have an outsize effect on the wider economy across countries. Some use cases in the sector could have a meaningful, direct impact on government cash flows, such as advanced analytics to detect fraud and incorrect payments in grant and transfer systems or tax evasion—which are often significant sources of financial leakage. Moreover, many public-sector use cases affect the population and total economy by improving the quality and outcomes of public services. With personalized, predictive, and preventive services in areas as diverse as education, transport planning, and firefighting, better outcomes may have an economic multiplier: they not only save money directly for the government but could also enable higher productivity for citizens and private companies.
There are significant nuances across countries (Exhibit 2). For instance, the methodology suggests that the potential impact of AI in the public sector may be especially pronounced in UAE (23 percent), Oman (15 percent), and Qatar (15 percent). Across these countries, public-service personalization and fraud and debt analytics could represent a significant portion of this potential value. Procurement and spending analytics may also be large opportunity use cases in the public sector in Qatar and UAE because procurement and investments, not least in the construction sector, account for a large share of these countries’ public spending.
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Meanwhile, our analysis suggests that the manufacturing sector could potentially see outsize impact from AI in Bahrain (32 percent) and Kuwait (30 percent). In Bahrain, this opportunity likely stems from the fact that the manufacturing sector accounts for 18 percent of the economy, compared with just 9 percent on average in the other five countries.
Of course, moving to capture this value in GCC economies raises potential risks from these technologies. For instance, an AI model being used to distribute social benefits must be thoroughly checked for inherent biases against segments of society. Similarly, an AI model being used for predictive maintenance in a manufacturing plant must be tested to ensure that it delivers the desired performance and safety every time without any failures.
Governments can potentially play an active and critical role in capturing the many benefits of implementing AI technology across a country.
Possible opportunities for governments to help capture this potential
Governments can potentially play an active and critical role in capturing the many benefits of implementing AI technology across a country. They can choose from a variety of approaches, depending on factors such as local political and economic structures. And when these approaches are applied to different sectors or countries, there may be unique challenges to navigate. Based on our benchmark analysis of early adopters of AI technologies, we have identified several example initiatives.
Enabling a vibrant AI ecosystem
Countries may consider creating an AI sector or ecosystem consisting of skilled practitioners, research institutes, start-ups, and large enterprises. Five enablers can be helpful in creating a vibrant AI ecosystem that has the potential to unlock benefits for citizens, businesses, and government entities: AI regulations; a highly skilled workforce; globally recognized, cutting-edge research and innovation; a combination of domestic and foreign funding; and world-class data and computer infrastructure. Of course, these enablers require planning and resources to attain and are not guaranteed to have impact. Globally, governments have spearheaded initiatives across the enablers:
- Regulations. Given the quickly evolving security, privacy, and ethical risks related to the use of AI, governments may consider establishing a systematic approach to actively watch for and potentially even penalize organizations that do not effectively identify and manage the risks associated with AI. In 2021, the European Union became the first governmental body in the world to issue comprehensive draft regulations aimed specifically at the development and use of AI.
These regulations suggest that organizations should have robust processes in place to manage AI risks and comply with existing and future regulations. Rather than scaling back on AI development, organizations may need to create a framework for risk management and compliance that will enable them to continue to innovate and deploy AI at a safe pace. Additionally, governments may want to define regulations on managing citizen data to the highest international data privacy standards, following guidelines from entities such as the United Nations.
- Workforce. To build talent broadly in the population, Finland launched Elements of AI in 2018—a free online course designed to introduce AI basics to nonspecialists in the public. As the course was published, the Finnish government pledged to educate at least 1 percent of its population—a target that was quickly met and surpassed. The course is now available in more than 20 languages, and 750,000 people around the globe have completed it.
Similarly, AI Singapore has launched LearnAI, a program that provides customized training courses targeted at various segments of society, including students, educators, industry professionals, and the larger public.
- Research and innovation. The National Science Foundation in the United States founded multiple National Artificial Intelligence Research Institutes focusing on a variety of AI themes, and the US government announced $1 billion in grant awards to create 12 new AI and quantum information R&D institutes.
Likewise, AI Singapore’s AI research grants provide up to 1 million Singapore dollars (about US $718,000) in funding to researchers focused on advanced AI to seed high-quality research efforts aimed at developing fundamental novel AI techniques, algorithms, and adjacent technologies.
- Funding. UK Research and Innovation has committed to providing £530 million of funding for AI research and development, comprising £129 million for novel AI algorithms, tools, and techniques and £401 million for the applications and implications of AI.
AI Singapore’s flagship program, 100 Experiments (100E), aims to solve AI problem statements for entities across different sectors by providing about 250,000 Singapore dollars (roughly US $180,000) of funding per 100E project and giving access to a team of researchers and technical specialists.
- Infrastructure. Singapore has set up the Centre of Excellence for Testing & Research of Autonomous Vehicles (CETRAN) in collaboration with Nanyang Technological University. At CETRAN, emerging AI innovations such as autonomous vehicles can be tested in a sandbox environment that aims to replicate the different elements of Singapore’s roads with common traffic schemes, road infrastructure, and traffic rules.
Similarly, in Taiwan, the Ministry of Economic Affairs recently launched the Unmanned Vehicles Technology Innovative Experimentation Program, which licensed a company to conduct a one-year experimental sandbox operation for Winbus, an electric, self-driving minibus.
Launching transformative, national-level AI programs
Some countries also launch transformative AI programs where they see the biggest opportunities for disruption based on their natural strengths. For example, Singapore is launching five programs in high-potential areas for the country, including smart cities and smart urban-mobility initiatives, a digital platform for businesses to access government services and resources, and an electronic-payments project.
To help identify which programs to launch, countries can consider each program’s potential economic impact, how programs align with strategic priorities and inherent strengths, the readiness of the target sector to adopt AI, and the potential impact of programs on citizens.
Consider setting up an AI authority
Many countries, including Saudi Arabia, Singapore, the UAE, and the United Kingdom, have set up centralized AI authorities to realize the value of AI.
This body typically is responsible for overseeing the country’s approach to AI adoption and benefits, from a mandate to mobilize the entire ecosystem to initiatives that drive the country’s overall AI agenda. The authority in Singapore, for instance, is part of the National Research Foundation, which reports directly to the prime minister’s office.
Governments can potentially pave the way for capturing the full value of AI by considering some of the steps above, educating the private sector about the potential of AI, identifying where the biggest opportunities lie, and supporting the adoption of AI technologies in an ethical and secure manner that addresses the risks of these technologies. But governments cannot do this alone. Research institutions and universities, for example, may lead the testing and development of new AI algorithms and make their solutions available for commercialization. They may also collaborate with government entities to support the development of a comprehensive set of policies and guidelines for organizations to ensure secure, responsible, and ethical use of AI in the technologies they develop and deploy. Citizens can be catalysts for change by actively demanding higher-quality, faster, and more personalized services from public- and private-sector entities; they also can be vocal about the privacy, security, and ethical risks associated with AI. And the biggest potential impact could come from private companies, which can adopt and even innovate AI use cases, build employee capabilities, double down on AI investments, and adopt a systematic approach to identifying and managing the risks related to AI.
Indeed, a joint effort across the economy to build innovative new AI solutions and support the widespread adoption of AI through skill building, investments, incentives for adoption, and regulations can potentially help countries capture the economic value of AI. If approached carefully, with consideration given to the unique challenges, AI could have the power to fundamentally transform societies around the world.