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India’s Human Development Index (HDI) ranking improved to 130th in 2025, showing gains in health, education, and income. However, inequality, responsible for a 30.7% HDI loss, remains a critical barrier, undermining the inclusive nature of development and delaying the realization of human potential.

Inequality Persists Despite HDI Gains

• Unequal Wealth Distribution: Economic gains remain concentrated, with the top 1% owning over 40% of national wealth, widening the socio-economic gap.
• Gender Disparities: Female workforce participation remains low, with women significantly underrepresented in formal employment and decision-making positions.
  Example: As per Periodic Labour Force Survey (PLFS) 2023, female labour force participation in India stands at only 41.7%,
• Regional Imbalances: Disparities between states affect access to education, health, and income opportunities.
  Example: NITI Aayog’s SDG Index shows Kerala ranks highest, while Bihar and Uttar Pradesh lag across human development indicators.
• Limited Social Mobility: Marginalized groups face restricted access to jobs, finance, and education.
• Education and Skill Gaps: School enrolment has improved, but learning outcomes and job-readiness remain low.
  Example: ASER 2023 found about 25% of the youth cannot read a Class II level text fluently.

How India Can Leverage AI for Inclusive Development

Addressing Persistent Gender Disparities

• Reducing Gender Bias in Recruitment: AI can analyze hiring processes to identify and eliminate gender bias in job recruitment, ensuring equal opportunities.
  Example: AI-powered recruitment tools like HireVue can help eliminate biased hiring practices by evaluating candidates based on skills rather than gender.
• Promoting Women’s Access to Financial Services: AI can offer personalized financial products to women, promoting financial inclusion.
  Example: RBL Bank’s AI-based platform offers personalized microloans to women entrepreneurs, facilitating easy access to finance.
• AI for Women’s Health and Safety: AI can support women’s health by offering diagnostic tools, telemedicine services, and enhancing safety through surveillance systems.
  Example: AI-powered health apps like MediBuddy are improving healthcare access, especially in rural areas, by providing remote consultations for women.

Addressing Persistent Income Disparities

• AI for Inclusive Economic Growth: AI can help develop new business models and job creation opportunities in underdeveloped sectors, benefiting low-income groups.
  Example: Karya, an Indian startup, partners with NGOs to provide AI data annotation jobs to rural workers.
• AI for Tailored Welfare Schemes: AI can enhance the delivery of welfare services, ensuring targeted distribution and reducing leakages.
  Example: The EasyGov AI chatbot assists citizens in identifying and accessing government welfare schemes based on real-time eligibility checks. 
• AI for Financial Literacy in Low-Income Groups: AI can promote financial literacy in low-income communities, helping individuals manage their finances and escape poverty.
  Example: Accenture Labs and Grameen Foundation India developed AI based applications to improve financial capacity and decision-making among low-income women.

Challenges in Leveraging AI for Inclusion

• Digital Divide: Limited internet access in rural areas restricts the reach and benefits of AI technologies.
  Example: According to NSSO, Only 24% of rural Indian households have internet access, compared to 66% in urban areas.
• Bias in AI Algorithms: Poor data diversity can cause exclusionary outcomes and reinforce social biases.
  Example: The National Strategy for Artificial Intelligence by NITI Aayog highlights risks of discrimination due to data selection bias.
• Low AI Literacy: Citizens lack understanding of AI tools, preventing full utilization.
  Example: The IndiaAI initiative aims to bridge this gap by extending AI education to Tier 2 and Tier 3 cities, ensuring accessibility across urban and rural areas. 
• Inadequate Data Infrastructure: Fragmented or poor-quality data hampers AI’s scalability in public systems.
  Example: The National Data Governance Framework Policy seeks to standardize data management and security standards across the government.
• Private Sector Dominance: Concentrated innovation in private hands limits AI’s application in public welfare.
  Example: The Responsible AI initiative by the Global Partnership on Artificial Intelligence advocates for public-private collaboration to direct AI towards social good.

Multidimensional Policy Framework for Inclusive Development

• Gender-Responsive Budgeting: Targeted spending improves women’s education, health, and financial access.
  Example: Gender Budget 2024–25 allocated ₹ 3.09 lakh crore, about 6.5% of the total budget.
• AI Ethics and Regulation: Rules are needed to ensure AI systems remain fair and accountable.
  Example: The draft Digital India Act (2023) proposes ethical standards and algorithm audits for transparency.
• Strengthening Public Education and Health: More investment ensures equal access to basic services.
  Example: NEP 2020 and Poshan Abhiyaan aim to improve foundational literacy and childhood nutrition.
• Localized AI Innovation: AI must reflect regional languages and local development contexts.
  Example: The Bhashini project enables multilingual AI tools for inclusive education and governance.
• Universal Digital Infrastructure: Expand access to devices, connectivity, and digital literacy.
  Example: PM-WANI provides free Wi-Fi through Public Data Offices to bridge urban-rural digital gaps.

India’s HDI progress reflects strong human development efforts. Yet, inequality persists as a structural barrier. By integrating ethical AI, targeted investments, and inclusive governance, India can transform its development paradigm to ensure no one is left behind in the AI age.

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