Artificial Intelligence (AI) has emerged as the defining technology of the 21st century, reshaping economies and businesses. By 2030, it is projected to add nearly USD 15.7 trillion to global GDP , unlocking unprecedented productivity gains and accelerating innovation across sectors. AI is more than a tool; it is fast becoming a strategic asset that underpins global influence and drives socio-economic progress. This makes it essential for countries and businesses to invest decisively in AI capabilities and resources.
The global AI race is unfolding across four related dimensions: compute, data, models, and talent. A few countries, such as the United State (US) and China, have taken an early lead by investing in research and development. Others, such as India, the European Union (EU), Singapore, the United Arab Emirates (UAE), and Israel, have endeavored to focus on building applications, specialized talent pipeline, and regulatory innovation. Many nations that face structural barriers in infrastructure, funding, and talent risk being left behind, and completely dependent on imported solutions. This unevenness is also visible across industries – while finance and healthcare, along with sector agnostic solutions are advancing rapidly, others such as agriculture and public services remain constrained by the longer gestation periods.
Together, these disparities are creating a widening “AI divide”. In 2023, over 66% of developed economies had an AI strategy in place, compared to only 30% in developing and 12% in least developed ones. On the business front as well, organizations that adopt AI in strategic ways are seeing an outsized improvement in their performance. For example, 34% of organizations use AI to create new Key Performance Indicators (KPIs); the ones that do so are 3x more likely to see greater financial benefit.
Businesses are increasingly focused on implementing AI for economic gains. However, despite this traction, many remain stuck in pilots and struggle to scale impact. Skill gaps, difficulties in embedding AI into business processes, and navigating cultural resistance are key barriers which slow adoption. To catalyze impact at scale, leadership must focus on integrating AI into the core of their business, starting with quick wins that build confidence, then embedding AI more deeply into processes while empowering people to create greater value.
At an ecosystem level, there are structural inequities in infrastructure, capital, skills, and governance across nations. Access to compute remains prohibitively expensive and scarce. Data, though abundant, is often fragmented, localized, non-digitized or of poor quality, restricting scalability. Talent remains limited and highly concentrated in a few geographies, fueling global competition for AI expertise. Funding remains constrained, particularly for AI infrastructure and socially sensitive sectors. Trust in AI remains fragile, with bias, misinformation, and opaque systems threatening public confidence, while fragmented regulatory frameworks make compliance and innovation complicated.
Nations must ‘RISE’ to the occasion and intervene across four key levers – Research, Investment, Skilling, and Ethics (RISE). Research requires building open, collaborative, public-private ecosystems and fostering innovation. Investment must extend beyond ventures to strengthen the digital backbone and support underserved sectors. Targeted Skilling is essential to bridge the widening talent gap through revamped curriculum, reskilling of the workforce, and knowledge sharing. Upholding Ethics requires clear governance frameworks that balance innovation with safety, ensuring trust and adoption.
AI represents both an unprecedented growth opportunity and a strategic necessity. Nations and businesses must bridge the AI divide, unlock productivity across sectors, and secure global competitiveness.