As nations and corporations race to dominate artificial intelligence, the real question is whether AI will serve humanity — or force humanity to serve it.
Indian Interest by SHOBHAN SAXENA
The global scramble for artificial intelligence supremacy increasingly resembles a high-stakes economic arms race. Governments are announcing billion-dollar missions, venture capital is pouring into model-building start-ups, and tech giants are unveiling ever larger, ever more “powerful” systems. Yet beneath the headlines and valuations lies a deeper question: are we witnessing a genuine technological revolution — or a funding-fuelled hype cycle wrapped in the language of inevitability?
The competition between different models of AI has become intense. American tech giants are pushing proprietary large language models trained on vast datasets, guarded by paywalls and enterprise subscriptions. Europe speaks the language of regulation and ethical guardrails. China is advancing its own ecosystem, increasingly rooted in open-source or semi-open frameworks designed for rapid adoption and strategic autonomy. Now India, too, is entering the fray with its IndiaAI Mission and the high-profile AI Impact Summit.
At one level, competition is healthy. It drives innovation, reduces monopolistic control and accelerates breakthroughs. But at another level, much of what we see today feels like a race not merely for technological leadership, but for capital. AI firms are competing for funding rounds, valuations and geopolitical endorsements. Model sizes are brandished like trophies. Benchmarks become marketing tools. Every week promises a “transformative” breakthrough.
This atmosphere of hype has real economic consequences. Capital that once flowed to diverse sectors — manufacturing, green energy, public health technologies — is now being funnelled disproportionately into AI start-ups. Stock markets react dramatically to AI announcements. Entire business models are being reshaped on speculative projections of what AI might do, rather than what it demonstrably delivers today.
For the global economy, the implications are profound. Artificial intelligence promises productivity gains across logistics, finance, healthcare, agriculture and governance. Automation of repetitive cognitive tasks could lower operational costs and unlock efficiencies at scale. Countries that integrate AI effectively into public infrastructure — taxation systems, welfare delivery, transport networks — may see measurable gains in growth.
But growth will not be evenly distributed.
The nations that control foundational models, data infrastructure and semiconductor supply chains will command disproportionate influence. AI could widen the economic gap between technologically advanced economies and those still struggling with basic digital access. Just as the industrial revolution created both wealth and exploitation, the AI revolution risks concentrating power in a handful of corporations and countries.
The job market is already feeling the tremors. Unlike previous waves of automation that primarily affected manual labour, AI strikes at cognitive professions — content creation, legal drafting, coding, customer support, financial analysis. White-collar workers, once considered secure, now find themselves vulnerable to algorithmic substitution.
For developing countries that rely heavily on outsourcing and service exports, this shift is particularly sensitive. If AI reduces the cost of performing knowledge work in high-income countries, the traditional outsourcing model could weaken. The economic ladders that lifted millions into the middle class may require reinvention.
China’s approach offers an interesting counterpoint. Its growing emphasis on open-source AI models reflects both strategic necessity and geopolitical calculation. By making models accessible and adaptable, China positions itself as a technological alternative to Western proprietary systems. Open ecosystems encourage rapid experimentation, domestic adoption and lower entry barriers for smaller players.
However, open source is not automatically synonymous with openness in governance or freedom in usage. The real question is who sets the norms, controls the data and defines the boundaries of acceptable application.
India’s entry into the AI race comes at a crucial moment. With its vast talent pool, digital public infrastructure and growing start-up ecosystem, India has the potential to chart a third path — neither purely corporate-driven nor tightly state-controlled. The onboarding of tens of thousands of GPUs, the push for indigenous foundational models and the emphasis on AI applications tailored to Indian challenges signal ambition.
This is where the AI Impact Summit acquires significance beyond symbolism. Hosting the first global AI gathering of its scale in the Global South sends a message: governance conversations cannot remain confined to Silicon Valley or Brussels. The People, Planet and Progress framework suggests an attempt to anchor AI in sustainable development, employment generation and social welfare.
But summits must translate into structures. If India can champion shared compute infrastructure, AI Commons and ethical standards rooted in inclusivity, it could help rebalance global AI governance. It could argue that AI is not merely a tool for corporate profit or strategic rivalry, but for public good — improving agriculture productivity, healthcare access, disaster management and education.
Ultimately, the debate is not about algorithms; it is about agency.
The race is underway. But winning should not be defined by who builds the biggest model. It should be defined by who builds the most humane one.
