AI for Every Woman: India's Missing Workforce Revolution

Introduction

Artificial Intelligence is rapidly transforming economies, workplaces, and public services across the world. In India, conversations around AI have largely focused on software development, healthcare, manufacturing, financial services, governance, and education. While these sectors are important, they represent only one side of India's labour market.

The country's largest workforce remains largely invisible in AI discussions.

India is home to nearly 195 million informal women workers, making it the largest such workforce in the world. They work as domestic workers, street vendors, construction labourers, home based producers, agricultural labourers, waste pickers, caregivers, and countless other occupations that keep the economy functioning every day.

Yet most AI solutions are designed for formally employed workers with smartphones, digital literacy, stable internet access, bank accounts, and verified digital identities.

This creates a serious policy challenge.

Instead of reducing inequality, AI could deepen existing social and economic divides if India's informal women workers remain excluded from the country's digital transformation.

A truly inclusive AI revolution must begin with those who have historically been left behind rather than those who are already digitally connected.

India's Invisible Workforce

The informal economy contributes significantly to India's economic activity while employing the overwhelming majority of the workforce.

Women constitute a large share of this informal labour force. Their work often remains unpaid, underpaid, or unrecognised despite being essential to households and local economies.

Domestic workers maintain urban households.

Street vendors provide affordable goods and services.

Construction workers build India's infrastructure.

Home based workers manufacture garments, handicrafts, food products, and numerous consumer goods.

Despite their contribution, these workers usually lack employment contracts, social security, regular wages, insurance, legal protections, and access to institutional finance.

As India moves towards an AI driven economy, these structural disadvantages risk becoming even more pronounced.

The challenge is no longer only about employment. It is about ensuring equal participation in the future digital economy.

The Double Exclusion Facing Informal Women Workers

Informal women workers experience what can be described as a double exclusion.

The first exclusion is digital.

Many women lack smartphones, stable internet connectivity, digital payment systems, reliable identity verification, or consistent access to government digital platforms.

Although initiatives such as Aadhaar, Jan Dhan accounts, and mobile connectivity have expanded financial inclusion, significant gaps remain in digital access and usage, especially among women in rural and low income urban communities.

The second exclusion is technological.

Even when digital infrastructure exists, AI systems are often designed assuming users possess literacy, English language familiarity, technical confidence, and continuous internet access.

A domestic worker searching for legal assistance, a street vendor applying for credit, or a home based artisan seeking market information may struggle to interact with AI platforms built primarily for educated users.

This means AI does not merely reflect existing inequalities.

Without deliberate intervention, it amplifies them.

Why AI Discussions Focus on the Formal Economy

Current AI policy discussions in India largely revolve around sectors that already possess organised data, digital infrastructure, and institutional capacity.

These include software development, banking, healthcare, logistics, manufacturing, education, agriculture technology, and government administration.

These sectors naturally generate measurable productivity gains and attract significant private investment.

However, the informal economy operates differently.

Work relationships are flexible.

Employment records rarely exist.

Income fluctuates daily.

Transactions are often cash based.

Documentation remains limited.

These characteristics make informal work less attractive for commercial AI developers despite its enormous social importance.

As a result, innovation flows towards organised industries while the largest segment of India's workforce receives comparatively little attention.

Why Inclusive AI Matters

Inclusive AI goes beyond providing internet access or smartphone applications.

It means designing technology that recognises the realities of diverse users.

An AI system built for India's informal women workers must accommodate multiple languages, voice interactions, low literacy levels, intermittent connectivity, affordable devices, and local cultural contexts.

Technology should adapt to people rather than expecting people to adapt to technology.

For example, a domestic worker should be able to ask an AI assistant about labour rights using her own language through voice interaction.

A street vendor should receive market information without navigating complex interfaces.

A home based artisan should access digital marketplaces without requiring advanced technical skills.

Inclusion begins when AI becomes accessible to ordinary citizens instead of remaining limited to digitally privileged users.

Digital Identity Beyond Aadhaar

India has made remarkable progress in creating digital public infrastructure.

Aadhaar, Unified Payments Interface, DigiLocker, and other digital platforms have transformed governance and financial inclusion.

However, digital identity alone is not sufficient for AI inclusion.

Many informal women workers possess Aadhaar but lack digital confidence.

Others may have smartphones but cannot effectively use digital services because of literacy barriers.

Some share devices within families, reducing privacy and independent access.

Inclusive AI therefore requires what may be called functional digital identity.

This includes verified credentials, digital skills, financial access, secure data ownership, language accessibility, and confidence in using technology.

Only then can AI services become genuinely meaningful.

The SHE MART Initiative and Women's Digital Markets

The SHE MART initiative represents an important effort to strengthen women's economic participation through digital platforms.

It seeks to connect women entrepreneurs, artisans, and self help groups with wider markets, helping them expand income opportunities beyond local communities.

AI can significantly strengthen such initiatives.

Intelligent recommendation systems can connect sellers with suitable customers.

Language translation tools can remove communication barriers.

Demand forecasting can help women plan production more efficiently.

Digital marketing assistance can increase visibility for small businesses.

Financial advisory systems can improve business planning and credit access.

However, these benefits will materialise only if AI systems remain affordable, multilingual, and simple enough for first time digital users.

Otherwise, digital marketplaces may primarily benefit already connected entrepreneurs rather than the most vulnerable women workers.

Bima Sakhi and AI Enabled Financial Inclusion

The Bima Sakhi initiative aims to improve insurance awareness and financial inclusion by creating women led insurance distribution networks.

This initiative demonstrates how technology and community engagement can complement each other.

AI can strengthen this model in several ways.

Voice based assistants can explain insurance products in local languages.

Personalised advisory systems can recommend suitable insurance schemes based on occupation and income.

AI powered claim support can simplify documentation.

Fraud detection tools can strengthen trust while reducing administrative delays.

Most importantly, AI can reduce information asymmetry.

Many informal workers remain uninsured not because insurance is unavailable but because they lack understandable information and trusted guidance.

Community based women leaders supported by accessible AI tools can bridge this gap.

Building Gender Responsive AI

Gender responsive AI is not merely about increasing the number of women using technology.

It is about ensuring that technology itself recognises gender specific realities.

Women often face unequal access to education, property ownership, finance, healthcare, mobility, and digital infrastructure.

These inequalities influence how AI systems should be designed.

Training datasets must represent women from different occupations and regions.

Algorithms should be regularly audited for gender bias.

Voice recognition systems should accurately understand regional accents spoken by women.

Translation models should include local dialects.

AI interfaces should prioritise simplicity over technical complexity.

Privacy safeguards become particularly important because women frequently face online harassment and data misuse.

Inclusive AI therefore requires inclusive design from the earliest stages of development.

AI as a Tool for Social Justice

Artificial Intelligence should not be viewed only as an economic technology.

It is also a governance tool.

AI can improve access to welfare schemes, healthcare, legal aid, financial services, skill development, education, and employment opportunities.

For informal women workers, this can be transformative.

An AI assistant could identify government schemes for which a worker is eligible.

It could provide legal guidance regarding wages or workplace rights.

It could assist in preparing digital applications.

It could recommend nearby training programmes.

It could help women compare market prices before selling products.

When deployed responsibly, AI becomes a tool that expands capability rather than replacing labour.

This aligns closely with the constitutional vision of social justice and inclusive development.

Challenges to Inclusive AI

Building inclusive AI is far from simple.

The first challenge is infrastructure.

Reliable internet connectivity, affordable smartphones, electricity, and digital service centres remain unevenly distributed.

The second challenge is digital literacy.

Millions of women have never interacted with AI systems and require sustained support rather than one time training.

The third challenge involves algorithmic bias.

AI systems trained primarily on urban, English language, and formal sector data may produce inaccurate or discriminatory outcomes for informal workers.

The fourth challenge is data privacy.

Women working in vulnerable occupations often face greater risks from identity theft, financial fraud, and digital exploitation.

The fifth challenge is affordability.

AI solutions should not require expensive subscriptions or premium devices.

Public digital infrastructure must remain accessible to everyone.

The Role of Government

Government has a central role in ensuring that AI promotes inclusion instead of exclusion.

Policy should encourage the development of multilingual public AI platforms.

Digital literacy programmes should specifically target women in the informal economy.

Public AI infrastructure should remain interoperable with existing Digital Public Infrastructure.

Government procurement policies can encourage companies developing accessible AI tools.

Local governments, self help groups, women's cooperatives, and civil society organisations should become implementation partners rather than passive beneficiaries.

Inclusive AI cannot be delivered solely through technology companies.

It requires coordinated public policy.

The Role of Private Industry

Private technology companies also have important responsibilities.

Commercial success should not be measured only through enterprise software or premium consumer products.

India's largest untapped market consists of citizens currently excluded from advanced digital services.

Businesses that develop voice based interfaces, offline AI capabilities, affordable language models, and accessible financial tools can create enormous social and economic value.

Corporate innovation should therefore expand beyond urban professionals and formal enterprises.

Designing for inclusion is not merely corporate social responsibility.

It is also long term market development.

AI and the Future of Women's Economic Participation

The future of work will increasingly depend on digital capability.

If informal women workers remain excluded from AI, existing inequalities in income, productivity, and opportunity may widen.

Conversely, if AI becomes accessible to them, it can improve productivity, market access, financial resilience, social protection, and entrepreneurial growth.

Technology alone cannot eliminate structural inequality.

However, it can become a powerful multiplier when combined with education, financial inclusion, social security, and institutional support.

India therefore has a unique opportunity.

Rather than replicating technology models developed elsewhere, it can create an AI ecosystem designed around inclusion from the beginning.

Such a model would be relevant not only for India but also for many developing economies facing similar labour market realities.

The Way Forward

India's AI strategy should move beyond viewing inclusion as an optional objective.

It should become a foundational principle.

Future AI systems should be multilingual, voice enabled, affordable, privacy preserving, and designed for users with varying literacy levels.

Digital identity should evolve from simple verification towards meaningful participation.

Government schemes such as SHE MART and Bima Sakhi should integrate AI tools that simplify access instead of increasing complexity.

Universities, research institutions, technology companies, and civil society organisations should collaborate to build datasets that accurately represent India's social diversity.

Regular gender audits of AI systems should become standard practice.

Above all, informal women workers must participate in designing AI solutions rather than merely becoming recipients of them.

Nothing about inclusion should be designed without the participation of those who seek inclusion.

Conclusion

India stands at the beginning of one of the most significant technological transformations in its history.

Artificial Intelligence has the potential to reshape governance, productivity, healthcare, education, finance, and economic growth.

Yet the true measure of success will not be the sophistication of algorithms or the size of technology investments.

It will be whether AI reaches the woman selling vegetables on the roadside, the domestic worker managing multiple households, the artisan producing goods from her home, and the construction worker building India's cities.

These women form the backbone of India's informal economy.

Ignoring them would mean building an AI revolution for only a fraction of the nation.

Placing them at the centre would create an AI ecosystem that is not only technologically advanced but also socially just, economically inclusive, and consistent with the constitutional promise of equality and dignity.

India's AI future will be strongest when its most invisible workers become its most empowered digital citizens.