AI that understands various accents, aspirations, and challenges

With ideal intent and investment, India can now build a future where AI bridges divides, empowers livelihoods, and drives inclusion.

A small farmer in Madhya Pradesh may not think of himself as a “tech user.” But before sowing his crop, he uses a voice-enabled AI advisory service in his dialect that guides him on weather conditions, soil preparation, and government schemes. At the same time, a woman running a small dairy in Bihar uses an AI-powered app to track cattle health and milk yields. For her, what was once dependent on the advice of a visiting veterinarian now comes through a simple voice prompt in her native dialect, saving her both costs and uncertainty. In Kerala, a fisherman may not know what “machine learning” is, but he does know that the real-time weather alerts on his phone help him avoid treacherous tides.

If AI is designed with purpose, it has the potential to be the most powerful equaliser of our time. (Source: AI-generated)

Across the country, daily wage workers, frontline workers, smallholder farmers, gig economy workers, nano-entrepreneurs, and others are interacting with AI on an almost daily basis in ways they never imagined- ways that ease their lives and livelihoods, and help them progress.

Yet, AI’s promise is only partially realised. The gap between cutting-edge AI innovations and the communities that need them most continues to remain wide. The challenge is not just about developing powerful algorithms but about ensuring these systems are built with inclusion at their core, from an economic, social, and cultural perspective- keeping India’s diversity in mind.

AI as a Catalyst for Inclusion

The global AI narrative often revolves around efficiency- streamlining logistics, automating processes, and boosting productivity. But in India, AI’s significant role isn’t about making businesses leaner and more productive, it is about making opportunities more accessible and affordable to the hundreds of millions who can benefit from the personalisation and inclusive capabilities of AI. AI should bridge gaps in access, resources, and representation, helping technology to be an enabler of progress.

A major hurdle is that AI models are often developed with a default assumption of urban, English-speaking users. These linguistic and regional biases can create invisible walls, preventing millions from fully leveraging AI-driven solutions. For India to benefit, AI must be multilingual, community-led, and capable of adapting to diverse cultural and economic realities.

This is where initiatives like Pragati: AI for Impact, launched by The/Nudge Institute in partnership with Meta, play an important role—ensuring that AI-driven solutions are built for India's diverse population, reaching people in their native languages and hyperlocal contexts. The first cohort—nine organisations selected from over a hundred applicants— underscores an important shift. These innovators are not building AI to make existing systems faster; they are reimagining how education, healthcare, agriculture, and accessibility can work for those at the margins, thereby creating new pathways of opportunity.

Beyond Automation: AI’s Role in Work and Skilling for the Marginalised

AI implementation is somewhat different in the Indian context. It isn’t about eliminating jobs; it is more about redefining them. Consider DigiYatra- designed for seamless, paperless, fully automated airport entry—yet human staff remain essential in assisting passengers. The same logic should apply across industries, ensuring AI is a tool augmenting human capabilities.

In skill development and employment, AI can be a powerful leveller. Take, for example, an AI assistant that provides legal aid on labour laws in local dialects could be very helpful for millions of contract workers, gig workers, and informal sector employees to understand their rights, entitlements, and benefits.

Beyond simplifying processes, AI is also generating new income streams. A young girl in rural Karnataka—once disconnected from the digital economy-is now earning a steady income by creating voice datasets that are used to train AI foundational models in her native language.

The Three Pillars of AI for Social Good

For AI to be a force multiplier for inclusive growth, it should be built on these foundational pillars:

1. Ethical and Adaptive Governance

AI regulation is complex and continuously evolving. Policymaking struggles to keep pace with technological advancements, sometimes resulting in either an over-regulated environment or a free-for-all deployment, where biases may go unchecked. Neither works well. India’s approach should be adaptive—governance that moves in tandem with AI’s evolution. Regulation should be dynamic, inclusive, and forward-thinking—an approach that fosters innovation while ensuring AI remains a tool for equity, not exclusion. The focus should be on ensuring AI serves the poor as much as the privileged, whilst ensuring that the risk and exposure for the most vulnerable users is adequately protected from potential cyber threats.

We should build a regulatory framework that does not merely protect, but also enables. For example, proactive compliance measures, such as bias audits in AI hiring platforms, can help prevent exclusionary practices before they become systemic issues.

2. Data: Not Just Extensive, But Diverse

AI thrives on data, but not all data is created equally. If we’re training AI on datasets that mostly reflect urban, English-speaking users and ‘Western’ use cases, we are perpetuating exclusion and biases into the system. For AI to work for every Indian, it should be built on inclusive datasets factoring in every possible aspect of India’s diversity and heterogeneity. This means ensuring representation, whether it’s AI recognising dialect accents with regional languages, understanding gender nuances in job applications, or providing healthcare recommendations factoring in local dietary habits.

Moreover, India’s vast informal economy presents a unique challenge. Millions of migrant workers, gig workers, daily-wage laborers, and small-scale entrepreneurs operate outside current, structured datasets. How do we design AI solutions that capture their needs and use cases? The answer could lie in democratising data collection, including, but not limited to, open-data collaborations, community-driven datasets, and AI models that proactively include rather than exclude nuanced datasets.

3. Human-Centered AI Design

If technology isn’t built for real people and real use cases, it will continue to perpetuate the limited few, particularly in a country as diverse and complex as India. AI must be intuitive, accessible, and tailored to the everyday needs of every Indian. In a country where literacy gaps continue to exist, text-heavy interfaces may not work for many. But an AI tool that understands multiple dialects and even hyperlocal slang can be quite impactful.

Technology adoption is not just about availability; it’s about usability and, equally importantly, affordability. A farmer using an AI-powered weather advisory should not need to decode technical jargon—he should simply hear, “Bhaiya, kal barish hogi, annaj dhak lo” (Brother, it will rain tomorrow, cover your grain stock). These are the nuances that are fundamental to the transformational impact that AI can make in India.

Scaling AI for Sustainable Impact

Pilots and experiments are great, but the real challenge is scale. Today, the majority of investment in AI flows into consumer-facing applications: tools designed for people like us, not for those at the last mile. This leaves a critical gap where technology could be transformative but isn’t yet reaching. Philanthropic capital can play a catalytic role here by providing the risk capital needed to fund bold, early-stage AI solutions that commercial investors often overlook—innovative solutions that target India’s challenging problems, from healthcare access in remote areas to livelihood support for informal workers. At the same time, public–private partnerships remain crucial for scaling successful solutions, ensuring that inclusive AI moves beyond pilots to reach millions. Without such intent and investment, India risks building a future where AI deepens divides instead of closing them.

The Road Ahead: AI with Purpose

India’s AI journey is at an important point. We are past the stage of debating if AI will shape our future—it already is. The real question is: Whose future is it shaping?

Will AI widen the gap between the privileged and the underserved, or will it level the playing field? The answer depends on how we choose to build and deploy it.

If AI is designed with purpose—if it is built for India’s billion, not just the few millions—it has the potential to be the most powerful equaliser of our time. But that won’t happen without intent, investment, and a commitment to ensuring AI serves the last mile and the grassroots.

This is the AI that India needs—not only to compete globally, but to lead in use cases and playbooks that make AI technology and solutions work for every Indian.

This article is written by Subhashree Dutta, Managing Partner, Livelihoods Ecosystem, The/Nudge Institute.

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