When the India AI Impact Summit 2026 convened policymakers, technologists, startups, multilateral agencies and global CEOs in New Delhi from February 16 to 20, it was more than a technology conference. It was, in effect, a geopolitical statement, accentuated by the presence of around twenty heads of states, top executives from leading AI companies and delegates representing nearly eighty countries. India was certainly showcasing its innovative prowess. More significantly, it was positioning itself as a prospective norm-maker in the emerging global architecture of artificial intelligence.
Framed around a human-centric philosophy, reflected in Prime Minister Narendra Modi’s emphasis on inclusive and accountable AI, the summit highlighted a broader ambition that AI governance should not remain confined to Silicon Valley boardrooms or reduced to strategic competition between Washington and Beijing. Suggesting a middle path, India projected itself as a voice of the Global South, arguing that AI must serve development, equity and societal welfare. That framing received visible endorsement from leaders such as UN Secretary General António Guterres, French President Emmanuel Macron and Finnish Prime Minister Petteri Orpo, lending international weight to India’s attempt to broaden the normative conversation around AI.
There were tangible signals behind that rhetoric. Government backed platforms under the IndiaAI Mission, new sectoral applications in health and education and state level investment commitments suggested that AI is being embedded into India’s policy bloodstream. The summit also reflected India’s confidence in its digital public infrastructure model built around stack-based platforms, interoperable data systems and scalable public private ecosystems that have already transformed payments and identity management.
At the same time, the summit exposed the familiar tension between vision and capacity. Logistical glitches, cybersecurity advisories targeting participants and organisational bottlenecks reminded observers that technological ambition requires institutional depth. More fundamentally, questions remain about India’s comparative position in foundational AI research, high-end semiconductor ecosystems and frontier model development.
Within India’s own policy circles, this anxiety is palpable for quite a while. When DeepSeek emerged last year as a serious challenger to OpenAI’s ChatGPT, a question echoed across Indian tech debates about why India could not produce a comparable breakthrough model. When consumer facing platforms like Zomato soared in valuation and visibility, critics at home and abroad asked why India was not generating more globally dominant, knowledge intensive AI products rather than largely service-oriented applications. Each time American or Chinese giants such as Huawei or Apple unveil cutting edge hardware and integrated ecosystems, the same refrain surfaces:how can a country with such a vast and capable pool of engineers and data scientists remain dependent on external breakthroughs?
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This recurring introspection reveals something important. India’s AI moment is not driven by complacency but by restlessness. Its policymakers and public alike recognise the paradox that Indian origin talent contributes significantly to global technology firms, yet transformative innovation often occurs outside India’s borders. The frustration is not merely about prestige. It is about economic positioning, strategic autonomy and technological sovereignty in a century where AI capabilities increasingly define national power.
In that sense, the thirst for an AI surge in India is enormous. The summit signalled an intent to move from being a back-office technology service provider to becoming a rule-maker, platform builder and innovation pool. Whether that aspiration translates into sustained investment in research ecosystems, semiconductor fabrication, compute infrastructure and deep tech entrepreneurship will determine if India can close the gap it so acutely feels.
For the neighbourhood, and especially for Nepal, this internal Indian debate is significant. It shows that the AI surge next door is not accidental or rhetorical. It is forced by a powerful mix of ambition, insecurity and strategic calculation. We should be able to grasp the meaning of this. But at the summit, while Bhutan was represented at the highest political level, Nepal was miserably absent. The gathering was as much a response to India’s domestic pressures as it was a message to the world, one from which BBIN countries should have sought to benefit.
At the time India accelerates its AI discourse and institutional ecosystem, Nepal risks being left behind not only in technological capability but also in strategic imagination. Nepal’s digital public infrastructure remains underinvested and underdeveloped. E governance systems operate in silos. Data governance frameworks are weak. National debates on AI ethics, safety and industrial policy remain sporadic. Even within policy circles, AI is often treated as a distant abstraction rather than an immediate developmental instrument. This inertia is strategically dangerous. More critically, the election manifestos of political parties heading into the March 5 polls have remained largely silent on the subject. The narrative that computational power can create “enormous earning opportunities for youths sitting on the hills of Kirtipur” must be backed by investment and policy if it is to carry any meaning.
The lag is not merely technical. It is structural. Nepal lacks large scale compute capacity, sustained research investment and regulatory coherence. Universities produce capable graduates, yet brain drain persists. Even at this stage, Nepali youth are making significant contributions to advanced technological innovation abroad after educating themselves and creating opportunities through their qualifications. For a country of Nepal’s size, that is a critical resource. Private innovation exists at home, but without the scale or state backing necessary to anchor a national AI ecosystem that can connect with the emerging generation of the Nepali diaspora.
This is where strategic realism is required. Nepal is in no position to replicate India’s scale, nor should it treat AI as a zero-sum geopolitical arena. Instead, it should anticipate technological trickle-down through structured partnership with India, leveraging geographical proximity to strengthen its own digital public infrastructure for the demands of a new technological century. Such cooperation can emerge through university collaborations, joint research initiatives, partnerships between AI firms and carefully designed cross-border innovation frameworks.
Structured partnerships need not dilute sovereignty. On the contrary, they can enhance Nepal’s agency by preventing technological isolation. India’s experience with digital stacks, multilingual AI models and public private ecosystems offers templates that Nepal can adapt rather than attempt to reinvent at prohibitive cost. Shared regulatory dialogues, capacity building exchanges and coordinated data standards could transform asymmetry into productive enterprise.
There is also a civilisational logic to such collaboration. AI systems trained on South Asian languages, cultural contexts and developmental realities require regional participation. If Nepal remains absent from this ecosystem, its linguistic and social realities risk becoming peripheral in the algorithms that will shape future markets and governance systems.
In an era where digital public infrastructure is becoming as critical as roads and hydropower, technological inertia carries strategic costs. Nepal’s challenge is not simply to align with India’s AI surge, but to do so intelligently, building domestic capacity while leveraging regional partnership and weaving together its own ambitious generation scattered across the world.
The deeper lesson of the India AI Impact Summit is not about spectacle. It is about preparedness. India has signalled its intention to become a technological agenda setter. Whether it succeeds will depend on execution. For Nepal, however, the more urgent question is simpler. Will it engage with this shift strategically, or will it watch the AI century unfold from the margins?
(A software engineer at Ambition Guru, the author is a Digital Governance Fellow at Asia Dialogue Initiative Kathmandu.)
