Artificial intelligence (AI) is no longer sitting inside research labs or tech demos. It is slowly becoming part of everyday systems, from banking and healthcare to government services. As that shift happens, countries are having to answer a basic but important question: who is AI really for? At the India AI Impact Summit 2026, India tried to respond to that through what it calls the M.A.N.A.V. Vision. In his address at the summit, Prime Minister Narendra Modi described MANAV not as a technical blueprint, but as a values-driven approach to how artificial intelligence should grow in the country. The idea is to keep human purpose at the centre rather than treat AI as just another tool for speed and scale. The acronym stands for five guiding pillars that India believes should shape how AI is built, used and regulated. Taken together, they are meant to show that innovation can move forward without losing sight of ethics, accountability and public trust.
SurveyM.A.N.A.V.: A human-centred lens for artificial intelligence
At its heart, the MANAV Vision rests on a simple belief. AI should not run on autopilot, guided only by data, speed or efficiency. It should work alongside people and reflect human judgement, social responsibility and democratic values. India’s thinking is closely tied to its scale. With a vast population, a young workforce and fast-growing digital public infrastructure, any AI system rolled out here can affect millions, sometimes even hundreds of millions, almost overnight. When the impact is that wide, safeguards cannot be treated as an afterthought. They have to be built in from the start. Each pillar of MANAV is designed to address a specific challenge or duty that comes with adopting AI at this scale.
M – Moral and Ethical Foundations
The first pillar asserts that AI systems must be grounded in moral and ethical principles. Fairness, transparency and human oversight are treated as baseline requirements, not optional extras. India’s approach also stresses early awareness. Digital literacy and AI-focused learning are being introduced at the education level so that future developers and users understand both the power and the consequences of these systems. The thinking is simple. If ethics are embedded early, the risks of bias, exclusion and unchecked automation can be reduced later.
A – Accountable Governance
The second pillar focuses on governance. The premise is direct. Trust in AI cannot exist without transparency, oversight and clear institutional responsibility. Under this pillar, India is building governance mechanisms alongside AI capability. Initiatives such as the IndiaAI Mission aim to integrate standards for development, deployment and monitoring into the public sector and large-scale AI use cases. Rather than relying only on action after something goes wrong, the model pushes for accountability from the start. Systems are expected to remain explainable, auditable and aligned with democratic processes.
N – National Sovereignty
National sovereignty in AI goes beyond physical borders. It includes control over data, algorithms, compute infrastructure and other critical digital systems. The MANAV Vision recognises that heavy reliance on external AI platforms can create strategic and economic vulnerabilities. India’s response has been to strengthen domestic capacity while remaining globally connected. Investments in semiconductor manufacturing, trusted data governance and sovereign digital infrastructure reflect this approach. The goal is autonomy, but not isolation.
A – Accessible and Inclusive AI
The fourth pillar addresses access. India’s position is that AI should act as a social multiplier, not a tool that benefits only a narrow group. Through digital public infrastructure, shared compute platforms and open datasets, entry barriers are being lowered for start-ups, researchers and institutions. This allows AI solutions to reach sectors such as healthcare, education, agriculture and governance at scale. Inclusion here is practical. Systems are designed to work across languages, regions and socio-economic contexts so that adoption does not remain limited to a small user base.
V – Valid and Legitimate Systems
The final pillar focuses on legality, safety and trust. As generative AI and synthetic media become more widespread, risks to public discourse and institutional credibility increase. India’s framework stresses that AI systems must be lawful, verifiable and transparent. Regulatory updates to digital governance rules aim to define accountability for AI-generated content and reduce misuse. In practical terms, this pillar supports tools for bias detection, privacy protection, auditing and risk assessment. The intention is to ensure that AI systems earn trust through clear rules and visible compliance.
Why the M.A.N.A.V. Vision matters globally
While MANAV is rooted in India’s context, its relevance goes beyond national borders. Many countries are dealing with similar concerns around trust, governance and inclusion, often without a clear organising structure. By outlining a values-led framework instead of a purely technology-first roadmap, India is positioning itself as a contributor to global AI norms. The emphasis is not on slowing innovation, but on aligning it with public purpose. Whether MANAV becomes a reference point for wider international cooperation will depend on how it is implemented. What is clear, however, is that the focus is shifting from what AI can do to what it should do, and the MANAV Vision offers a structured way to approach that shift while keeping human values at the centre.
Follow Us
Siddharth Malhotra
Siddharth Malhotra is a former software engineer who turned his lifelong fascination with gadgets into a full-time gig as a tech and gadgets anchor & writer. With over 200K followers across his social media platforms, all tuning in for their daily dose of tech, he’s your sneaker-wearing guide through the ever-evolving world of innovation. Expect sharp insights, a dash of humor, and an unshakable love for all things futuristic. View Full Profile
