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Artificial intelligence is rapidly becoming a transformative force across every sector of the global economy. From automating manufacturing processes to revolutionizing how we diagnose diseases or make investment decisions, AI is fundamentally reshaping productivity, innovation and economic competitiveness.
According to estimates by the International Data Corporation, AI has the potential to boost the global economy by an astonishing $19.9 trillion by 2030. This figure represents a seismic shift in economic potential, equivalent to more than the current size of China’s economy. Experts project that AI could increase the annual growth rate of global gross domestic product by up to one full percentage point over the next decade, rivaling the levels of economic transformation seen during the Industrial Revolution.
This anticipated surge in economic growth is driven by several key factors: massive gains in productivity due to automation, the ability to generate and analyze vast datasets, and the creation of entirely new markets and services powered by AI.
Industries are already seeing the early impacts of this transformation. In the finance sector, AI-driven algorithms are reshaping trading and risk analysis. In healthcare, AI is assisting in early diagnosis and personalized treatment plans. In logistics and manufacturing, autonomous systems are enhancing efficiency and lowering operational costs.
The scale and speed of change are unprecedented and AI is increasingly seen as a general-purpose technology — akin to electricity or the steam engine — with the power to permeate and uplift virtually every domain of economic activity.
However, while the overall global economic impact of AI is expected to be vast, the distribution of this growth will likely be highly uneven. A handful of industries and countries are poised to capture the lion’s share of AI’s benefits, leaving others at risk of being left behind.
Nations that already have strong digital infrastructures, advanced research institutions, robust regulatory frameworks and large pools of investment capital are in the best position to lead. Countries that are dominating the AI race are doing so due to their early investments in machine learning research, large-scale computing power and highly skilled technical workforces. These nations are not only producing the most AI patents and startups but they are also setting the ethical and technological standards that others will have to follow.
Within countries themselves, this dynamic is mirrored across sectors. High-tech industries such as finance, biotech, defense and cloud computing are poised to absorb and scale AI quickly. In contrast, lower-tech sectors — particularly those in developing economies or rural regions — face significant challenges in adoption. These include lack of infrastructure, limited access to high-speed internet, underdeveloped capital markets and a shortage of skilled labor.

As a result, AI’s economic windfall is likely to accrue primarily to a relatively small number of players, exacerbating existing divisions between the Global North and Global South and between urban and rural, high-skilled and low-skilled, and capital-rich and capital-poor populations.

Collaborative efforts to establish shared standards, address data privacy and coordinate AI governance are vital.

Dr. Majid Rafizadeh

This raises a critical and urgent question: Does GDP, the standard metric used to measure a country’s economic performance, adequately capture the real impact of AI? GDP was developed in the 20th century to track industrial production and consumption. While it remains useful for measuring overall output, it often fails to reflect the full social and economic implications of technological revolutions.
For example, GDP growth driven by AI may mask increasing inequality, job displacement or the erosion of traditional sectors. A country’s GDP might grow robustly even as millions of workers in routine or manual labor are made redundant by intelligent machines. Similarly, GDP cannot account for the ethical and psychological dimensions of AI, such as surveillance, algorithmic bias or mental health effects related to job insecurity. This disconnect raises important questions about how policymakers should assess economic well-being in an AI-powered world.
If AI continues to drive enormous wealth creation while simultaneously fueling inequality, social unrest and economic dislocation, then governments, institutions and global bodies must act now.
Countries that wish to share in AI’s benefits and avoid being left on the sidelines must begin by investing in the foundational building blocks of an AI-ready economy. This includes not only physical infrastructure — such as data centers and broadband access — but also legal and institutional infrastructure to promote innovation, regulate ethical risks and foster global cooperation. Countries without these ingredients risk becoming consumers rather than producers of AI, missing out on the wealth and geopolitical influence that comes with leadership in this domain.
At the same time, education systems must undergo a profound transformation to prepare the workforce for a future where AI is ubiquitous. Traditional education focused on rote memorization and static technical skills will no longer suffice. Nations must implement lifelong learning systems that teach adaptable skills such as critical thinking, data literacy, ethics and problem-solving — abilities that complement rather than compete with machines.
Furthermore, targeted reskilling programs must be developed to support those displaced by AI. These programs must not merely teach coding or technical skills but also create pathways into emerging sectors like AI ethics, data stewardship, human-centered design and interdisciplinary AI applications.
Investment also plays a central role. Governments need to provide incentives for both private and public sector investment in inclusive AI innovation. This includes funding AI startups, supporting open-source platforms and ensuring that AI applications address real-world problems such as climate change, food security, education and healthcare access in underserved communities. Tax incentives, public-private partnerships and inclusive procurement policies can help channel innovation toward socially beneficial ends. Without such intervention, market forces alone will likely prioritize profit-maximizing applications, further entrenching inequality and ignoring broader human needs.
Moreover, international cooperation is indispensable. AI is a global technology and its benefits and risks cross borders. Collaborative efforts to establish shared standards, address data privacy and cybersecurity, and coordinate AI governance are vital. Equally important is the need for wealthier nations to support capacity-building in the Global South, ensuring that the developing world has a fair opportunity to access and shape the future of AI. Otherwise, AI risks becoming yet another tool of global dominance, deepening rather than bridging the digital divide.
In conclusion, as AI stands at the frontier of a new era in global economic history, it holds the power to lift productivity, unlock innovation and catalyze trillions of dollars in new economic value. But it also threatens to leave behind those who are not prepared — intensifying inequality both within and among nations. The challenge ahead is not just to harness AI for growth but to ensure that this growth is inclusive, sustainable and aligned with human values.
The decisions made today — about policy, education, investment and international collaboration — will shape not only the trajectory of global GDP but also the kind of world we build for future generations.

• Dr. Majid Rafizadeh is a Harvard-educated Iranian American political scientist. X: @Dr_Rafizadeh