The Department of Consumer Affairs, under the Ministry of Consumer Affairs, Food and Public Distribution, has adopted an AI-enabled National Consumer Helpline (NCH) system to enhance the efficiency, transparency, and sector-wise analysis of consumer grievances. This AI-driven approach significantly shifts towards a data-driven, responsive, and consumer-centric ecosystem.

AI-Powered Consumer Redressal

The deployment of AI in the NCH system has enabled real-time data analysis, automated grievance classification, and predictive analytics to identify emerging consumer issues. With the surge in digital transactions and e-commerce, AI-driven tools have played a crucial role in handling complex complaints across diverse sectors, including education, e-commerce, healthcare, and digital payments. By leveraging Natural Language Processing (NLP) and Machine Learning (ML) algorithms, the helpline can efficiently analyze consumer grievances, categorize them based on sector, and provide actionable insights for quicker resolutions.

Enhanced Consumer Engagement and Confidence

Since the introduction of AI-enabled systems, the number of calls received by NCH has dramatically increased, from 12,553 in December 2015 to 1,55,138 in December 2024. This growth underscores the rising consumer confidence in the helpline. Similarly, complaints registered per month have surged from 37,062 in 2017 to 1,12,468 in 2024. The shift to digital platforms has further facilitated easier access to grievance redressal, with the monthly average number of digitally registered complaints increasing from 54,893 in FY 2023-24 to 68,831 in FY 2024-25.

Faster and More Efficient Resolutions

One of the most significant outcomes of AI implementation in NCH has been reducing grievance disposal time. The average resolution time has decreased from 66.26 days in 2023 to 48 days in 2024, reflecting a substantial improvement in efficiency. AI-powered chatbots and automated workflows have minimized manual intervention, ensuring faster resolution of consumer complaints. Predictive analytics facilitates the identification of recurring grievance patterns, enabling proactive intervention to prevent escalation.

Convergence Partnerships: Strengthening Consumer Protection

A key strategy of the AI-enabled NCH system has been onboarding companies with high consumer grievances as ‘convergence partners.’ These companies, which previously had significant unresolved complaints, must now collaborate closely with NCH for prompt and effective grievance redressal. This initiative has expanded significantly, with the number of convergence partners growing from 263 in 2017 to 1,038 in 2024. By mandating prompt grievance resolution, AI analytics ensures that companies remain accountable, ultimately fostering a culture of consumer-centric business practices.

Sector-Specific Insights and Policy Formulation

The AI-driven sectoral analysis provided by NCH enables policymakers to identify trends, gaps, and systemic issues affecting consumers. By analysing complaint data across industries, regulatory authorities can make informed decisions to strengthen consumer protection laws and introduce targeted reforms. This data-driven approach improves compliance and enhances overall consumer welfare by addressing systemic inefficiencies.

Empowering Consumers Through AI-Driven Innovation

The AI-enabled NCH represents a paradigm shift in consumer grievance redressal, making it more accessible, transparent, and effective. The government has empowered consumers with a robust platform for swiftly resolving grievances by integrating AI technologies. The toll-free number 1915 and the web portal are essential tools in this digital transformation, ensuring that every consumer complaint is addressed efficiently.

As AI continues to evolve, its integration into consumer protection frameworks will further enhance service delivery, optimize resolution times, and ensure a fair marketplace. India’s AI-powered NCH stands as a testament to the transformative potential of AI in governance, reinforcing trust and accountability in the consumer ecosystem.

Source: PIB,

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