Opinion The colonial era of AI is here — India must chart its own course

The new empire

The launch of Current AI with its $400 million investment, while laudable, is a drop in the ocean compared to the billions that companies like OpenAI, Anthropic, and Google pour into AI development monthly. This is, eerily, going the way of climate change. The initiative’s focus on public interest AI, while noble, seems more like window-dressing in a landscape where corporate AI development moves at breakneck speed, unfettered by democratic oversight. This follows after the US President rescinded domestic orders that were termed too onerous for AI development, and was further made clear by the US vice president when, under the garb of the “America First” argument, he railed against “excessive” AI regulation strangling the technology. The EU, as well as the host, France, have quickly aligned themselves with the US on this by promising to make it easier for businesses to operate in the field of AI. The guards have been lowered.

This new empire built on data, computing power, and algorithmic advantages cannot brook fetters placed by geographical boundaries. State and corporate power have merged, with tech companies wielding influence that would make colonial-era trading companies blush. The revolving door between Silicon Valley and Washington DC has never spun faster. It is only a matter of time before other arenas of contestation in the digital landscape, like data protection laws, are lined up for dilution.

For India, challenges and an unprecedented opportunity

For India, set to host the next AI summit, this presents both a challenge and an unprecedented opportunity. India is way behind in the long game in the field of AI. It has miles to go before it can be taken seriously as an AI tech superpower. However, rather than playing catch-up in a game designed by Western tech giants, India must chart an audacious new course.

First, India should spearhead the creation of a coalition of nations from Africa, Asia, and Latin America to pool computing resources, share data repositories, and develop AI models that address the unique challenges of emerging economies. This alliance would create a counterweight to both Western corporate AI dominance and Chinese state-controlled AI development, focusing on developing solutions for local contexts, such as agricultural productivity, healthcare access, and educational equity. The onslaught of big tech cannot be prevented in the world of hard-nosed, high-tech geopolitical negotiations. What can be done is the opening up of other fronts, other routes, that need not directly confront the established powers.

Second, India should propose a limited but strategic AI partnership with China focused specifically on developing large language models (LLMs) for non-English languages. This might seem like a taboo subject currently, but the same old ways of thinking won’t help. This “Digital Silk Route” would break the anglophone monopoly on AI development. The partnership could be structured with strict firewalls to address security concerns, perhaps with oversight from neutral countries like Singapore or Switzerland. The important thing is to not lose sight of the fact that collaboration is the need of the hour. India cannot afford to remain isolated or non-aligned.

The point is that with its unique position as both a rising tech power and a champion of developing economies, India has the potential to reshape the AI landscape. The Paris Summit’s environmental sustainability coalition, while important, sidesteps the fundamental question of power distribution in AI development. The coalition of 91 partners to address AI’s environmental impact is commendable, but without addressing the concentration of AI power in the hands of a few corporations, we risk creating a new form of digital colonialism where developing nations become mere data providers and consumers of AI systems designed for Western markets.

AI imperialism: An evolutionary biology perspective

Analysing the global onslaught of AI big tech supported by states from an evolutionary biology perspective provides interesting insights into what this might evolve into. This could help countries devise specific strategies suited to their contexts while also keeping in mind the big picture of working for the common good.

Biological systems evolve through natural selection, resource competition, and adaptive radiation. The global AI ecosystem is displaying remarkably similar patterns in its evolution toward imperialism. Like dominant species monopolising critical resources, major AI companies are engaging in aggressive competition for three essential resources: Computing power (particularly advanced GPUs), high-quality training data and elite AI talent. Just consider, for instance, how the US is focusing on creating exclusive talent pipelines through immigration policies targeting AI researchers. While practising these restrictive policies domestically, it is calling for lesser restrictions for US companies in foreign markets, all aimed at monopolistic competition.

This has led to what evolutionary biologists call “competitive exclusion” — where dominant species (in this case, companies like OpenAI, Google, and Anthropic) prevent others from accessing critical resources, effectively creating monopolistic niches. The dominant species is taking the help of the state to advance this competitive exclusion, creating the newest form of imperialism. Barriers are being dismantled at breakneck speed.

Similar to how species diversify to fill different ecological niches, we’re seeing AI companies undergo adaptive radiation: OpenAI focusing on general-purpose AI, DeepMind specialising in scientific AI applications, Stability AI concentrating on generative art. However, unlike biological evolution, where diversity often leads to stable ecosystems, this AI specialisation is occurring within an oligopolistic framework controlled by a few dominant players. Due to this, the AI ecosystem shows strong “founder effects” — where the initial conditions and early players disproportionately shape the entire field’s evolution. The early advantages of Western tech companies in data, computing infrastructure, and talent have created a self-reinforcing cycle of dominance, similar to how small founding populations can determine the genetic makeup of entire future populations.

Due to this, we are also witnessing predator-prey relationships where larger AI companies either acquire smaller AI startups (predation), or force them into dependent relationships (parasitism) or establish collaborative partnerships that primarily benefit the larger entity (commensalism). Just as prey and predators engage in evolutionary arms races, we’re seeing companies racing to build larger and more capable models, and escalating competition for AI talent and resources. There is also the aspect of competitive suppression, where export controls and sanctions are being used to limit AI chip access, allies are being pressured to align with US-centric AI governance frameworks, and regulatory barriers are being created that smaller nations cannot feasibly implement.

What are the implications of this evolutionary analysis? First, like evolutionary bottlenecks, the AI ecosystem might converge toward a small number of dominant players controlling most resources and capabilities. Second, an ecosystem collapse, in which the intense resource competition and rapid scaling could lead to systemic instability and overexploitation at the national and local levels. Third, adaptive diversification will see new niches emerging for specialised AI applications, creating opportunities for smaller players, though likely still within the larger imperial framework.

For countries like India, understanding these evolutionary dynamics suggests potential strategies. Go for niche specialisation and focus on specific AI applications where local advantages exist. Next, collaborate, collaborate, collaborate; like your life depends on it. Form symbiotic alliances and strategic partnerships with dominant players while maintaining independence. And lastly, focus intensively on resource pool creation and develop alternative sources of critical resources (talent, computing power, data).

Diversity protection and ecosystem balancing are urgently needed. As the Paris AI Action Summit showed, history, if not repeating itself, is surely rhyming at this point.

The writer is Research Analyst at The Takshashila Institution in their High-Technology Geopolitics Programme