Who will win and who will lose in the AI revolution?
By M A Hossain
Artificial intelligence (AI) is no longer a futuristic concept confined to science fiction; it is rapidly transforming every sector of the global economy.
From streamlining manufacturing operations and revolutionizing healthcare diagnostics to enabling algorithm-driven investment strategies, AI is redefining how productivity, decision-making, and economic competitiveness are measured and pursued.
As this technology continues to advance, it raises a fundamental question: Who will emerge as the true winners in the AI revolution?
According to projections by the International Data Corporation (IDC), AI is expected to contribute a staggering $19.9 trillion to the global economy by 2030 – a figure roughly equivalent to the entire GDP of China in 2023.
This potential economic boost is expected to raise global gross domestic product (GDP) growth by as much as a full percentage point annually over the next decade, a rate of transformation reminiscent of the Industrial Revolution.
The underlying drivers of this growth are multifaceted: rapid productivity gains through automation, data-driven decision-making at an unprecedented scale, and the emergence of new markets, products, and services enabled by AI. In essence, AI is quickly becoming a general-purpose technology – like electricity or the internet – capable of revolutionizing entire economic systems.
While AI’s influence will eventually touch every industry, certain sectors are already experiencing transformative change. In finance, algorithmic trading and AI-powered risk management tools are offering levels of speed and precision unattainable by human analysts.
In healthcare, machine learning models are detecting diseases like cancer and Alzheimer’s earlier and more accurately, leading to better outcomes and lower costs. Meanwhile, logistics and manufacturing are being optimized by autonomous systems that improve supply chain efficiency and reduce human error.
These gains are not limited to efficiency. AI also enables innovation: new drug discovery platforms, predictive climate models, and intelligent energy grids are all examples of AI opening new frontiers of possibility. The potential for AI to accelerate human knowledge and creativity is immense – but it is not guaranteed to be shared equally.
Despite its global potential, the economic impact of AI will be highly concentrated. A relatively small group of countries and industries are currently positioned to dominate the landscape.
Nations with robust digital infrastructure, advanced research institutions, skilled technical workforces, and large pools of investment capital will capture the lion’s share of AI’s benefits.
The United States, China, the European Union, and a few other technologically advanced economies are leading in AI research, patent filings, startup activity, and computational power.
These countries are not only shaping the pace of innovation but also setting the standards – ethical, technical, and regulatory – that others will have to follow. This dominance positions them not just as economic leaders but also as gatekeepers of the AI-driven global order.
Within countries, a similar divide is taking shape. High-tech urban centres with established innovation ecosystems – such as Silicon Valley, Shenzhen, and Berlin – are reaping early rewards, while rural and underserved regions lag far behind.
Industries like finance, defense, biotechnology, and cloud computing are integrating AI rapidly, whereas agriculture, traditional manufacturing, and low-skilled services face significant adoption barriers due to infrastructure gaps and workforce constraints.
This imbalance risks deepening existing economic and social divisions, reinforcing a pattern where wealth, power, and opportunity accrue to a concentrated few while the majority fall further behind.
As AI contributes to global GDP growth, it also raises questions about the adequacy of GDP as a measure of progress. GDP was developed in the early 20th century to measure industrial output and consumption.
While it remains a useful economic benchmark, it does not account for factors such as inequality, environmental degradation, job displacement, or the ethical dilemmas posed by new technologies.
A country’s GDP may increase due to AI-driven efficiencies, but that growth might mask a rising tide of joblessness, especially among workers in repetitive or manual jobs displaced by automation.
It also fails to capture the growing concerns around surveillance, algorithmic bias, and mental health impacts linked to technological disruption. In this light, GDP alone is a limited tool for assessing the broader societal impacts of AI.
To properly evaluate the AI revolution’s impact, policymakers will need to adopt more holistic metrics that consider quality of life, social equity, and sustainability. Indices that track digital inclusion, ethical governance, and workforce adaptability could provide a more accurate picture of who is truly benefiting from this technological shift.
If left solely to market forces, the AI revolution could exacerbate global inequalities, concentrating wealth and power in a small number of hands. But it doesn’t have to be this way. With thoughtful, proactive policies, countries can position themselves to both participate in and help shape the AI-driven future.
Infrastructure Investment:
Countries must invest in both physical and institutional infrastructure. This includes data centers, high-speed broadband, secure cloud platforms, and AI research hubs, as well as legal frameworks to protect data privacy, ensure algorithmic transparency, and promote ethical AI development.
Education and Workforce Development:
Traditional education models are poorly suited for a world where AI automates many predictable tasks. Nations must invest in lifelong learning programs that equip citizens with adaptive skills – including data literacy, problem-solving, ethics, and creativity. Vocational reskilling should also extend beyond coding to include fields like AI ethics, data stewardship, and interdisciplinary applications of AI.
Inclusive Innovation Policies:
Governments can steer AI development toward public good by incentivizing research and startups focused on societal challenges like climate change, healthcare access, and educational equity. Public-private partnerships, targeted tax breaks, and inclusive procurement practices can all play a role in democratizing AI innovation.
Global Cooperation:
AI is not constrained by national borders. As such, international governance is critical to managing its development and diffusion. Global cooperation is needed to establish shared standards for data privacy, cybersecurity, and ethical deployment. Wealthier nations should also help build AI capacities in the Global South – not just out of altruism, but because global stability and prosperity depend on
AI represents one of the most profound technological revolutions in history. Its power to generate wealth, boost innovation, and transform society is extraordinary. But that power comes with equally profound risks: widening inequality, eroded labor markets, and the potential for authoritarian misuse.
The winners of the AI revolution will not be determined by technology alone. They will be the countries, institutions, and communities that invest in infrastructure, embrace inclusive education, regulate wisely, and cooperate globally. Those who fail to act risk being relegated to the periphery – consumers rather than producers in the new AI-powered economy.
Ultimately, the choices we make today will shape the economic, ethical, and human dimensions of the future. If we want AI to build a world that is not just richer but fairer and more resilient, then bold, inclusive, and cooperative leadership will be essential. The race is not just for AI dominance – it is for the kind of civilization we want to create in its wake.
