OP-ED:The AI Race Has No Single Winner — And Pakistan Must Choose Its Own Future

As Washington bets on technological breakthroughs and Beijing turns artificial intelligence into industrial power, Pakistan faces a more urgent challenge: ensuring that the next technological revolution strengthens its economy, institutions and citizens rather than deepening their dependence.

The future of artificial intelligence may be decided as much on factory floors as inside research laboratories. Yet the world remains preoccupied with a deceptively simple question: will China overtake the United States in the race for AI supremacy?

It is an attractive question because it promises a familiar answer. One nation wins, another loses, and the balance of global power shifts accordingly. History, however, rarely unfolds so conveniently. Technological revolutions do not produce a single victor. They produce competing centres of power, new dependencies and unexpected opportunities for countries willing to recognise them.

For Pakistan, this distinction matters enormously.

A farmer struggling with falling agricultural yields has little reason to celebrate whether an American or Chinese model leads an international benchmark. A textile manufacturer facing high production costs needs technology that improves efficiency. A public hospital short of specialists needs more reliable diagnostic support, not another announcement about becoming a regional AI hub.

The real question is not who will invent the most intelligent machine. It is who will turn intelligence into prosperity — and who will be left paying for technologies designed elsewhere.

Two superpowers, different advantages

America continues to enjoy formidable advantages in AI research, capital markets, advanced computing and the commercial development of frontier models. China, meanwhile, possesses industrial scale, integrated supply chains and an increasingly sophisticated manufacturing ecosystem capable of bringing technological improvements into practical use.

The numbers reveal the contrast.

According to Stanford University’s 2026 AI Index, American private investment in artificial intelligence reached approximately $285.9 billion in 2025, compared with $12.4 billion in China. The figures are striking, although they do not capture the entirety of Chinese government-directed investment.

The same report shows that the performance gap between leading American and Chinese AI models has narrowed considerably. The two countries have repeatedly challenged each other’s position at the technological frontier.

This suggests that American financial dominance no longer guarantees an equally commanding technological advantage.

China, however, is competing on another front.

In 2025, Chinese factories installed approximately 354,000 industrial robots, accounting for 59 per cent of global installations, according to figures reported by Dawn from the International Federation of Robotics.

The United States installed substantially fewer.

These figures demonstrate the scale of China’s manufacturing automation. They do not mean that every installed robot possesses advanced artificial intelligence, or that China has already mastered general-purpose robotics.

That distinction is important.

An industrial robot repeating a programmed welding operation is not equivalent to a machine capable of independently navigating an unfamiliar environment, recognising unexpected problems and adapting safely without human intervention.

Indeed, a detailed Reuters investigation into China’s humanoid robotics industry found that many impressive demonstrations remain far removed from commercially viable autonomous factory work.

China’s industrial advantage is therefore substantial but not conclusive.

Its deeper strength lies in something less spectacular: the ability to manufacture components, improve them through repeated production, reduce costs and distribute the resulting technologies across industries.

America may remain stronger at developing some of the world’s most capable models. China may prove exceptionally effective at making increasingly capable systems affordable and useful.

Neither achievement guarantees overall victory.

The limits of technological nationalism

Much of the discussion surrounding AI resembles an updated version of the Cold War space race. Political leaders invoke national prestige, strategic supremacy and the danger of falling behind.

But artificial intelligence differs from a contest to place the first human on the moon.

There is no final destination. There is no agreed finishing line. A breakthrough in model performance can quickly lose its commercial advantage if competitors develop cheaper alternatives or if businesses find that the technology is too expensive to deploy.

The economics may ultimately matter more than the publicity.

Consider the semiconductor industry.

American companies occupy strategically important positions in AI chip design, software and computing platforms. China has responded to export restrictions by accelerating efforts to build domestic alternatives.

The results are beginning to appear. An October 13 Reuters report citing IDC figures found that Nvidia held 34 per cent of China’s data-centre AI accelerator market in the first half of 2026, while Huawei had reached 28 per cent.

This does not establish technological equivalence between the two companies’ most advanced products. It does show how restrictions intended to protect a technological advantage can simultaneously encourage competitors to develop substitutes.

China faces serious obstacles involving advanced semiconductor manufacturing, specialised equipment and access to leading-edge computing resources.

America confronts vulnerabilities of its own, including dependence on international chip fabrication, enormous infrastructure costs and uncertainty over whether anticipated commercial returns will justify extraordinary investment.

The global AI economy is not dividing neatly into two self-sufficient technological empires.

It remains interconnected, even as governments attempt to redraw its boundaries.

Electricity may matter as much as algorithms

Another neglected dimension of AI competition is energy.

Training and operating sophisticated AI systems requires substantial computing infrastructure. Data centres need dependable electricity, cooling systems, transmission networks and capital.

The International Energy Agency projects that worldwide data-centre electricity consumption could approximately double to 945 terawatt-hours by 2030 under its base-case scenario.

That is a forecast, not a certainty. Improvements in chip efficiency, model design and computing practices could alter the trajectory.

Nevertheless, the direction is unmistakable: intelligence is becoming increasingly dependent on physical infrastructure.

China’s investments in electricity generation, renewable energy manufacturing and industrial supply chains provide significant advantages.

America, meanwhile, combines deep capital markets with major investments in data centres and energy infrastructure, although electricity supply constraints and grid expansion delays remain concerns.

The lesson is not that one country possesses an unbeatable advantage. It is that the AI revolution will reward governments capable of coordinating technology, energy, investment and infrastructure.

For Pakistan, where electricity reliability and industrial competitiveness remain longstanding concerns, this should be a warning against misplaced priorities.

A country struggling to deliver affordable power to existing industries cannot assume that building fashionable AI infrastructure will automatically generate economic development.

Indeed, the World Bank’s approval of $375.9 million for Pakistan’s grid stability programme in July 2026 illustrates the continuing importance of basic infrastructure.

Reliable electricity is not separate from digital transformation. It is one of its essential foundations.

The winner may not be the greatest beneficiary

There is another problem with viewing AI as a contest between Washington and Beijing: it confuses technological leadership with public welfare.

A country can lead in artificial intelligence while large sections of its population experience economic insecurity, stagnant wages or declining opportunities.

An impressive national AI industry does not automatically produce better schools, more equitable healthcare or greater economic mobility.

The opposite is also possible. Businesses may enjoy efficiency gains while workers bear the costs of technological disruption.

The enormous spending commitments associated with AI also deserve scrutiny.

As Reuters has reported, the current investment boom has intensified questions about whether productivity improvements and commercial revenues will eventually justify the scale of expenditure.

History offers reasons for both optimism and caution.

Electricity, computers and the internet transformed economies, but the benefits were neither immediate nor evenly distributed. Productivity gains required complementary investments, organisational changes, human skills and functioning institutions.

AI is unlikely to escape these realities.

Nor should societies overlook the human labour behind supposedly autonomous machines.

Training advanced robotic systems frequently involves people performing repetitive tasks, collecting data and correcting machine errors. The apparent intelligence of the final product may conceal an extensive workforce whose economic contribution receives comparatively little attention.

This raises questions about worker protection, compensation and the distribution of benefits from automation.

Technological progress should not be measured exclusively by the amount of human labour a machine can replace.

It should also be measured by whether people gain better opportunities, greater security and improved living standards.

The emerging battle over technological dependence

AI competition is increasingly becoming a struggle over the systems other countries will adopt.

Washington’s AI Action Plan promotes the international export of integrated American technology packages, including computing hardware, models, applications and standards.

China is pursuing its own international technological influence through infrastructure, manufacturing, increasingly competitive models and industrial partnerships.

For developing countries, this competition presents both opportunities and dangers.

Affordable AI tools can reduce barriers to innovation. Open-weight models can allow smaller firms and universities to adapt technologies without financing the development of enormously expensive frontier systems.

But accessibility is not the same as independence.

A system may be inexpensive to adopt and costly to abandon. Businesses can become dependent on foreign computing platforms, proprietary software, remote infrastructure and licensing arrangements.

National institutions may surrender control over sensitive data without fully understanding the implications.

The danger for Pakistan is not simply choosing American technology over Chinese technology, or vice versa.

It is allowing technology procurement decisions to create dependencies that limit future national choices.

Technological sovereignty does not require Pakistan to manufacture every advanced chip or build a rival to every frontier model. It requires the ability to choose, evaluate, adapt and, when necessary, replace the systems on which its economy and public services depend.

That means encouraging interoperability, competitive procurement, cybersecurity, local technical expertise and meaningful data protection.

Such safeguards should apply regardless of whether the technology originates in Silicon Valley, Shenzhen or Islamabad.

Pakistan’s unfinished AI agenda

Pakistan is not starting entirely from zero.

The federal government approved its National Artificial Intelligence Policy in July 2025, outlining ambitions in skills development, innovation, infrastructure and responsible technology adoption.

In February 2026, the government also announced plans to invest $1 billion in AI by 2030, alongside scholarships and training programmes intended to improve national capabilities.

These announcements suggest that policymakers recognise AI’s importance.

Recognition, however, is not implementation.

A Dawn investigation published in February 2026 reported delays in implementing the national AI policy, including difficulties establishing governance structures and coordinating with provincial authorities.

Subsequent initiatives indicate policy activity, but activity alone is an inadequate measure of progress.

Pakistan’s problem has rarely been a shortage of ambitious announcements.

It has been the persistent distance between official promises and institutional delivery.

The country should therefore resist the temptation to pursue AI prestige projects disconnected from economic realities.

Building a national computing facility may be worthwhile if researchers, universities and businesses can use it effectively. It becomes an expensive symbol if the necessary electricity, technical expertise, governance and sustainable financing are absent.

Similarly, training large numbers of people in basic AI terminology is not equivalent to creating a competitive workforce.

Skills programmes must be connected to employers, technical standards and demonstrable improvements in productivity.

Otherwise, Pakistan risks producing another generation of certificates without corresponding economic opportunities.

From national ambition to measurable results

A credible national AI strategy should begin with Pakistan’s most urgent economic and social needs.

Agriculture offers one opportunity. Better weather analysis, pest identification, irrigation planning and market information could help farmers make more informed decisions. Such systems would need reliable local data, affordable access and independent evaluation.

Manufacturing offers another. Pakistan’s textile exporters face demanding international competition. AI-assisted quality inspection, predictive maintenance and production planning could help some firms reduce losses and improve competitiveness.

Education requires an equally practical approach.

AI can support teachers, develop supplementary learning materials and provide assistance in regional languages. But an unreliable automated tutor is not a substitute for trained teachers, functioning schools and sound educational standards.

Healthcare presents similar possibilities and risks. AI-assisted administrative systems, screening tools and clinical support could improve service delivery, provided qualified professionals retain responsibility for consequential decisions.

These are not arguments for indiscriminate automation.

They are arguments for carefully designed experiments with measurable outcomes.

The government should begin with a limited number of publicly evaluated projects across agriculture, education, healthcare, manufacturing and public administration.

Each project should establish its baseline costs, expected benefits, privacy protections and measurable results before receiving substantial public funding.

An independent assessment should then determine whether the technology actually improves services.

Did patients receive faster care? Did farmers reduce avoidable losses? Did schools demonstrate better learning outcomes? Did exporters achieve measurable productivity gains?

Projects that succeed should be expanded. Those that fail should be modified or discontinued.

This approach may attract fewer headlines than announcing an AI revolution, but it would provide a more credible foundation for one.

The missing foundation: citizens and institutions

Pakistan cannot build a successful AI economy while ignoring the inequalities that already restrict participation in its digital economy.

In June 2026, the World Bank approved $70 million for Punjab’s Connected Punjab Programme, designed to improve broadband connectivity, digital public services and participation by underserved communities.

The initiative illustrates a broader principle: meaningful digital transformation requires infrastructure that citizens can actually access.

Investment in AI must therefore accompany improvements in basic education, digital literacy, affordable connectivity and technical training.

Pakistan also needs systems that work beyond English-speaking urban professionals.

Tools designed for Urdu and regional languages could widen access to information and public services. But they must be tested carefully, particularly where errors could affect healthcare, legal rights or financial decisions.

There is also a question of accountability.

An algorithm used by a private company to recommend products does not raise the same public-interest concerns as one used by a government department to determine access to welfare, monitor citizens or make decisions affecting individual rights.

Public institutions should disclose consequential uses of AI, provide meaningful human review and establish procedures through which citizens can challenge harmful automated decisions.

Without those protections, technological efficiency can become a convenient justification for unaccountable power.

The quality of a country’s institutions will determine whether AI strengthens public services or merely digitises existing dysfunction.

A different measure of national success

The United States may continue producing some of the world’s most advanced AI models. China may expand its commanding position in industrial automation and develop increasingly competitive alternatives across the technology supply chain.

Their rivalry will shape global economics, trade and security for years to come.

The country that truly benefits from AI will not necessarily be the one that creates the smartest machine. It will be the one that makes its people more capable, its institutions more accountable and its economy more productive.

But the future need not belong exclusively to whichever country leads the next benchmark or unveils the next generation of machines.

Other countries will exercise influence through the choices they make as users, regulators, innovators and economic partners.

Pakistan should seek productive partnerships with both established technology powers and other countries, without confusing geopolitical allegiance with a development strategy.

It should purchase technology where appropriate, build domestic expertise where necessary and protect public interests consistently.

Above all, it must reject the mistaken belief that access to advanced technology is itself evidence of progress.

A country is not transformed by possessing artificial intelligence. It is transformed by acquiring the institutional capacity to use that intelligence wisely.

For Pakistan, the defining challenge is therefore not to predict whether America or China will win.

It is to prevent another technological revolution from exposing familiar national weaknesses while allowing others to capture most of the gains.

Pakistan’s future in artificial intelligence will be decided less by the technological achievements of Washington or Beijing than by the quality of decisions made in Islamabad, the provinces, universities and workplaces across the country.

We may need to import advanced intelligence for years to come. What we cannot afford to outsource is our judgment about how it should serve us.