India Among Top 10 Nations in AI Readiness

BCG’s AI Maturity Matrix offers a comprehensive overview of the AI landscape across 73 economies by focusing on two pivotal aspects. First, it assesses each economy's vulnerability to AI-driven shifts, such as job displacement and industrywide productivity gains. Second, it evaluates the preparedness of each economy to navigate the risks associated with AI, while leveraging its potential to stimulate economic growth.

According to the report, there are six sectors that are most exposed to AI-driven change: information and communication, high-tech goods, retail, financial services, public services, and motor vehicle manufacturing. Economies with a high share of sectors that are most exposed to AI are among the world’s most exposed to disruption. These include Luxembourg (with financial services making up almost 30% of GDP), Hong Kong (22% financial services and 22% business services), and Singapore (18% business services, 16% retail, 14% financial services).

Economies with industry sectors that are less susceptible to AI disruption are less exposed. Such sectors include construction, agriculture, and furniture manufacturing; countries include Indonesia (13% agriculture and 11% construction of GDP), India (17% agriculture and 8% construction), and Ethiopia (36% agriculture).

"Readiness" for AI refers to an economy’s ability to effectively implement and integrate AI. The study measures readiness across the six dimensions that make up BCG’s ASPIRE index: Ambition, Skills, Policy and regulation, Investment, Research and innovation, and Ecosystem.

Of the 73 economies assessed, only five—categorized as AI pioneers—have achieved a high level of readiness. Pioneers are also out in front in skills, R&D (research and development), ecosystems, and investments. In skills, the US and Singapore stand out with robust AI talent pools, crucial for driving innovation. The US leads in investing, driven by its sophisticated capital markets and the abundance of AI unicorns. In the R&D race, Mainland China is leading in patents and AI academic papers.

Six Distinct Archetypes of AI Adoption

AI Pioneers: These are the vanguards of AI adoption, building on strong infrastructure and engaging the technology in diverse sectors. All pioneers invest liberally in R&D and job sectors, and education systems are full of highly skilled talent. AI will make up progressively larger shares of the pioneers’ GDPs over the next several years, as these actors supply more and more AI technologies, services, skills, and investment to the world.

Steady Contenders: These economies have higher shares of highly exposed service sectors, however their exposure is balanced by high readiness. This group is mainly dominated by high-income European economies like Germany, which has high exposure due to its large information and communication technology (ICT) and advanced manufacturing sectors. Malaysia stands out as a non-European leader, with its government’s strong focus on AI through the National AI Roadmap, tech hubs, and university training. This illustrates how public sector leadership can drive tech maturity and competitiveness in emerging economies.

Rising Contenders: These are mainly economies with lower AI exposure due to a relatively higher share of industrial and/or resource-based mix of sectors. This lower level of exposure is the main difference between rising contenders and steady contenders, but governments in this subgroup push for AI adoption with the same commitment as steady contenders. India, Saudi Arabia, and Indonesia are notable examples in this group.

Gradual Practitioners: These are typically upper middle- and lower middle-income countries that are adopting AI at a moderate pace. Their economies include low-tech sectors such as tourism, textiles, wood manufacturing, and agriculture, where adopting AI is not yet imperative for companies.

Exposed Practitioners: This group includes developing and developed economies vulnerable to AI disruption due to more high-exposure sectors and low readiness. Actors here will need to accelerate AI adoption and mitigate potential risks. While these countries may currently have a gap between their AI exposure and readiness, they are well positioned to gain ground quickly with investments in infrastructure and education. Notable economies in this group include Malta, Cyprus, Bahrain, Kuwait, Greece, and Bulgaria.

AI Emergents: These economies are at the early stages of AI adoption. They need to build foundational strategies and infrastructure to reach the basic levels of AI integration and competitiveness. These countries lack a national AI strategy or similar holistic approaches to AI. Skilled workers and investment are often scarce, as is activity related to research papers, patents, and startups.