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The Quiet Crisis of Care in a Young and Ageing India

I am often struck by the extraordinary demographic moment we are living through in India. We may be the only country where we are substantially young and substantially old at the same time. Sixty-five percent of our population is below the age of 35, while approximately 150 million people, close to ten percent of our population, are above the age of 60. This is not a distant future, it is the India we inhabit today, and it compels us to think urgently and deeply about the systems and structures that hold families and communities together.

There are several trends that demand our immediate attention. One of the most significant is the rapid rise of nuclear households, driven largely by urbanization and changing economic realities. Nuclear families accounted for around 50% of Indian households in 2022, up from 34% in 2008, signaling a significant shift in family structures across both large and small cities. With this shift, the social infrastructure of care that once sustained generations is diminishing at an unprecedented pace. Traditional forms of caregiving, which were embedded in extended family arrangements and community culture, are weakening, leaving individuals and families with fewer sources of support.

Life expectancy has increased dramatically, and many of us are now living into our eighties. Elderly women live even longer by three or four years on average. But health span is not keeping pace with lifespan. The quality of the years we gain depends on our physical health, our independence, our dignity, and our financial security. Recent data indicates that seventy-five percent of elderly people in India have one or more chronic illnesses, twenty percent face mental health struggles, five percent have experienced some form of abuse (physical, sexual, psychological, or financial) within their own homes, and only eighteen percent have any health insurance. These challenges are further intensified in rural areas, where sustained out-migration of younger family members has sharply reduced the availability of everyday care.

This is why I frame care as a continuum that stretches across childcare, eldercare, domestic work, and even animal care, particularly in rural economies where livestock defines livelihood. Across this continuum, the burden of care is disproportionately borne by women. Care responsibilities account for the exclusion of an estimated 53 per cent of women from India’s labour force.  According to the government’s time-use survey, women spend between five to seven hours a day engaged in unpaid care work, the largest share of which is household labor. In many cases, entry into the workforce is not only constrained by supply of jobs but by the quality of work available. If decent and quality employment opportunities are not available for women, they may choose to stay home for their children or elders rather than accept low paid work. When care remains invisible and unsupported, women’s economic exclusion is not a failure of aspiration or a personal choice, they are economic and structural realities.

We are dealing with a huge care deficit, and its implications are social, economic, and moral. The care economy must be understood as a long-term priority. Care cannot remain a private matter, silently absorbed within families and largely by women. It is a public issue and a shared responsibility of the state, the market, and communities. We also have to consciously move away from phrasing “care” as a “burden”. Care makes us human and is an essential prerequisite for human capital to survive and thrive. Every one of us begins life needing care, and if we are fortunate to live long enough, we end life needing care again. In between these stages, we depend on care more than we often admit.

Care forms the very foundation of human capability and economic development. We must learn to see it not as expenditure but as investment. The single most important investment we can make is in the care of children, the elderly, and families who sustain our social fabric. When governments and markets invest in eldercare, they are investing in their own future, because every one of us is aging. When we support high-quality childcare, we create the conditions for a healthier, more capable generation. When workplaces genuinely support caregiving needs, they not only follow the law but strengthen their own wellbeing and productivity.

Families will always remain irreplaceable in care. No institutional model can replicate what family care provides in emotional depth and trust. But we must build systems that offer dignified, high-quality, and affordable options for families who need supplementary care from outside support systems especially when economic insecurity is a reality for millions. We need multiple models, new imaginations, and pathways that help families balance paid and unpaid work without forcing impossible choices.

The question before us is profoundly simple: What kind of society do we want to grow old in and what choices are we making today to shape it? If we ignore care now, we will inherit a future marked by loneliness, inequity, and exhaustion. If we choose to value care, invest in it, and place it at the center of how we measure progress, we can build a society that is humane, dignified, and deeply connected.

And all of us must decide together—because the future we are building is the one we ourselves will inhabit.

This was first published in “Reimagining The Family” on 14th January 2026.

Women’s collectives driving India’s next phase of growth

Across rural India, women are redrawing the map of local economies. What begins as an attempt to survive scarcity often evolves into innovation that not only sustains households but creates new markets. These are not the unicorns of urban India, but enterprises built from goats, grains and solar panels; ventures that generate income, empower communities, and weave new circuits of demand and supply. This shift rests on one of the world’s largest social and financial inclusion platforms, an infrastructure of women’s collectives unmatched in scale across the developing world.

In Bihar’s Gaya district, for instance, Santra Devi, a widow with no land, accessed a government scheme to build a goat shed and bought a few animals through her self-help group (SHG). Within a year, she was selling livestock, leasing land, cultivating pigeon peas and purchasing a year’s ration for her family. What appears modest is, in fact, transformative: A woman once dependent on others had secured her livelihood and added a steady stream of goats, grain and fodder into the village economy.

Such stories are becoming more common as India has spent nearly three decades building an unparalleled architecture for women’s livelihoods. Under the National Rural Livelihood Mission (NRLM), over 10 crore women—a population roughly the size of Japan— have been mobilised into 90.90 lakh SHGs. This mobilisation represents a unique success: collectivisation of rural women at an unprecedented scale, backed by formal credit, training and structured pathways to enterprise. These groups have evolved from savings circles into engines of enterprise, enabling women’s access to credit, skills and markets. They are also becoming market intermediaries—pooling produce, negotiating with buyers and linking village enterprises to procurement systems.

Today, the SHG ecosystem spans 21 clusters and 8–11 key value chains (from agriculture, livestock, textiles and handicrafts.) State Rural Livelihood Missions have further aggregated these collectives into 6–7 emerging national brands, helping SHG enterprises move beyond local markets. This foundation has enabled the second leap: the rise of women-run micro-enterprises that are beginning to reshape local markets and participate in value chains with growing sophistication.

Livestock rearing, food processing, retail and local services sit at the heart of this transition. Goats and poultry offer low-entry pathways for women who, until recently, had virtually no productive assets and minimal access to formal banking. Over the past two decades, this has shifted dramatically. Under DAY-NRLM, banks have disbursed over 11 lakh crore in credit to women’s SHGs, enabling group loans, first-time asset ownership and working capital for micro-enterprises. Independent impact evaluations across nine states show incomes rising by around 19%, savings increasing by nearly 28% and dependence on informal moneylenders dropping by 20 percentage points—clear evidence that women are moving from subsistence to steady enterprise.

With infrastructure such as MGNREGA-funded sheds and seed capital from state schemes like Bihar’s Satat Jeevikoparjan Yojana, many women have formalised and expanded their ventures. Similar transitions are visible in dairy, where women—who make up nearly 70% of India’s dairy workforce—supply to cooperatives such as Amul, linking household production to national-scale markets. The next opportunity lies in connecting these enterprises to wider markets through digital tools, e-commerce channels and transparent procurement systems.

What binds these diverse models together is sheer intent. Women innovate by combining what is available—a government wage scheme, a collective loan, a leased plot, a training programme—into a sequence that yields surplus. That surplus is reinvested. Earnings from one activity financing the next, savings cycles strengthening household resilience and steady cashflows enabling investments in nutrition, education and mobility. Scarcity becomes the raw material of creativity.

While there are some challenges—from uneven market access to weak last-mile services and women shouldering a disproportionate share of unpaid care work that constrains how much time women can invest in enterprise. Yet, where enabling ecosystems exist, the gains are unmistakable. A World Bank review of NRLM programmes shows improvements in women’s agency, participation in household decisions and measurable increases in income from diversified micro-enterprises.

The lesson is clear. Organising as groups shifts the starting point, giving women collective strength no individual enterprise can achieve alone. Access to group loans and working capital enables asset creation and income diversification. And small, strategic investments in infrastructure, training and procurement linkages turn necessity-oriented enterprises into opportunity and growth-oriented ventures.

India’s SHG ecosystem demonstrates that inclusive growth starts at the grassroots. Local women entrepreneurs collectivised in a group have become a driving force for women led rural transformation. To unlock their full potential, policymakers must invest in digital access, infrastructure, and fair procurement systems. With the right support, these groups can lead the next wave of rural prosperity.

This was published in “The Hindustan times” on 20th January 2026.

Integrated Digital Farmer Services (DFS) platform for Bihar: Bihar krishi app

The Bihar Krishi platform is a government-owned, integrated Digital Farmer Services (DFS) initiative designed to address the structural challenges faced by Bihar’s predominantly small and marginal farmers. A majority of farmers in the state experience limited access to timely agricultural advisory, government schemes, markets, finance, risk-management tools, and modern technology. These challenges are further intensified by climate change, leading to uncertain rainfall, extreme temperatures, pest outbreaks, rising input costs, productivity losses, and reduced incomes. A dipstick survey highlighted high levels of functional, financial, and digital illiteracy, low awareness of government advisories, limited smartphone penetration, and persistent issues with grievance redressal and scheme applications.

Launched on 19 May 2025 by the Honorable Chief Minister of Bihar, Shri Nitish Kumar, under the 4th Agriculture Roadmap of Bihar, Bihar Krishi is supported by the Gates Foundation and is operational across all 38 districts of the state. The platform aims to reach 20+ million farmers by providing a single, unified access point for agricultural information, advisory, and services throughout the farming lifecycle. It works in alignment with existing Government of Bihar IT systems and Digital Public Infrastructure (DPI), ensuring interoperability, data privacy, and public ownership.

Bihar Krishi is designed as an inclusive, multimodal platform, accessible through mobile apps, web, SMS, IVR, call centers, chatbots, and assisted modes via extension workers. Special emphasis is placed on women farmers, low-literacy users, and farmers with limited digital access. The platform integrates reliable farmer and agriculture data such as land details, crop-sown information, soil health data, and scheme history to deliver personalized and hyperlocal services.

The platform offers a wide range of core services, including government scheme discovery, eligibility checks, application support, grievance redressal, and farmer support services. Advisory offerings include hyperlocal weather alerts, plant protection, soil health recommendations, precision agriculture guidance, and access to agriculture knowledge repositories. Market linkage services enable real-time price discovery, market intelligence, and integration with private agri-service providers for input and output aggregation. Financial services include farmer passbooks, credit and insurance product recommendations, AI-assisted claim submission, and credit-worthiness assessment. The platform also supports allied sectors such as livestock and fisheries, and promotes climate-resilient agriculture.

Bihar Krishi leverages AI-enabled solutions to deliver voice- and text-based advisory in local languages, including AI chatbots (such as PM-KISAN e-Mitra), AI-powered voice search, and personalized notifications. Long-term AI use cases include hyperlocal agronomic advisory, scheme navigation, market intelligence and price prediction, credit and insurance facilitation, and contextualized learning content. These services are built on comprehensive farmer profiles that combine demographic, agronomic, market, and behavioral data, enabling predictive insights, risk management, and climate adaptation support.

Since launch, Bihar Krishi has demonstrated strong early impact, with 850,000+ farmers registered, coverage across all districts, 38,000+ scheme applications, over 50 schemes onboarded, and 12+ system integrations. Monthly engagement levels range between 20–25%, supported by AI-driven advisory and voice-based interfaces. The platform has trained 15,000+ agricultural extension workers and conducted state-wide digital outreach reaching over 20 million farmers. Its innovation and governance model have been recognized with the ET DigiTech Award 2025 (Gold) and the SKOCH Award 2025 (Gold).

Overall, Bihar Krishi represents a transformational, scalable, and inclusive digital public platform that strengthens agricultural resilience, improves farmer access to services, and sets a national benchmark for AI-enabled, government-led agricultural digitalization in low-resource settings.

 

Reimagining grievance and redress mechanisms to fix the weakest link for India’s financial consumers

India’s journey of financial inclusion has been remarkable. In just a decade, more than 571 million Jan Dhan accounts have been opened, and digital public infrastructure, from UPI to Aadhaar, has reshaped how households access money, insurance, and government benefits. For millions of low-income families, women, and migrant workers, the formal financial system is finally within reach.

Yet beneath this progress lies a quieter, persistent challenge. Financial inclusion does not end with access alone; it also depends on protection, trust, and timely support when things go wrong. For many consumers, especially in rural India, grievance redress remains difficult, confusing, and unreliable. Take Rani, a daily wage worker from Uttar Pradesh, who learned this the hard way. When a failed PI transaction deducted money from her account, she made repeated visits to her bank branch. Each visit cost her a day’s wages, only to be asked for new documents every time. “I do not know if anyone will solve my problem,” she lamented. Her experience reflects the reality of millions who struggle to reach equitable financial services. While they have access, the system fails to solve their problems.

India’s vision of financial inclusion acknowledges this gap. The National Strategy for Financial Inclusion (NSFI 2025-30) emphasizes that inclusion can only be sustained when consumers have access to simple, responsive, and technology-enabled grievance and redress mechanisms. However, inclusivity remains a distant dream for many low-income users today.

What MSC’s research uncovered

MSC conducted a study across nine states to understand how low- and moderate-income (LMI) consumers navigate grievance and redress mechanisms. We used a stratified sampling approach that covered 443 LMI respondents who had registered a grievance with a regulated financial entity. Through this study, we examined their awareness, registration behavior, follow-up patterns, and resolution experiences. Our study revealed important patterns and persistent gaps that form the evidence base for the insights shared in this blog. The following section outlines key insights. Discover the detailed methodology and findings in our full study here.

Awareness remains uneven and heavily dependent on informal channels

Most respondents knew about basic grievance channels. 73% of them were aware of helpline numbers, and 63% knew they could approach their local bank branch. However, awareness of digital or formal channels lagged significantly. Only 43% of respondents knew of online grievance portals, and just 34% were aware of email-based channels. Although financial service providers (FSPs) are expected to educate consumers, only one out of five respondents reported that they had learned about grievance and redress mechanisms from the institution itself. In contrast, 69% of respondents reported word of mouth, 55% reported internet search, and 53% reported social media as the primary sources of information. This leaves consumers vulnerable to misinformation and unsure about how to escalate their complaints effectively.

Resolution is slow, inconsistent, and often incomplete

Among all registered grievances, only 59% were fully resolved. Another 25% were partially resolved, while 16% remained unresolved, often for months. For many, delays were significant. 37% of cases took longer than a month to resolve. A farmer in Maharashtra described a harrowing experience with a pending crop insurance claim. He said, “I kept calling the helpline, but each time they asked me to wait for 15 days. It has been months now.” Such delays erode trust and force consumers to engage in repeated follow-ups.

Persistence, not system efficiency, drives outcomes

Consumers’ grievances move forward largely because they continue to follow up consistently. Nearly 40% had to follow up three to five times, while 14% followed up more than six times.

The process often depends on individuals rather than institutional systems. More than half of respondents credited branch managers or staff to help them resolve their issue, while 49% said customer care agents played a major role. The system’s design does not work proactively. Resolution depends on whether a sympathetic employee chooses to support the customer. This makes outcomes arbitrary and inequitable.

Women face layered, gender-specific barriers

– Women experience greater hesitation and lower confidence when they navigate grievance and redress mechanisms.

– 22% of women were afraid to interact with officials, compared to 18% of men.

– Only 57% of women’s grievances were resolved within a month, compared to 71% for men.

– Only 7% of women respondents were aware of channels, such as the RBI Ombudsman, for grievance and redress.

As a result, women often accept partial resolutions just to end the exhausting, time-consuming process. “In the end, I had to accept whatever help they offered. It was taking too long,” shared a woman from Odisha. These stories reveal a concerning pattern. They highlight a system where grievance redress relies on individual persistence, personal favors, and local goodwill, rather than structured and efficient mechanisms.

Why does this matter?

Financial inclusion cannot thrive without trust. When problems go unresolved, or grievance and redress mechanisms feel slow, confusing, or intimidating, consumers withdraw from digital channels, mobile banking, and sometimes from formal finance altogether. This disengagement harms consumers, reduces usage for providers, increases reputational and operational risks, and signals systemic weaknesses to regulators. A strong, transparent, and timely grievance and redress mechanism is therefore not a mere service feature. It is essential infrastructure that protects users, sustains confidence, and strengthens the integrity of India’s financial ecosystem.

What needs to change?

MSC’s study reveals that nearly 20% of LMI users experience fraud or attempted fraud within their networks. This has a severely negative impact on usage. of the respondents moderately reduced their digital usage, 11% sharply reduced it, and 8% stopped using digital services altogether.
This erosion of trust mirrors the concerns highlighted in the NSFI 2025–30, which underscores that sustained financial inclusion depends on strong, technology-enabled, and user-centric grievance and redress mechanisms. Such mechanisms protect consumers and reinforce confidence in digital finance. It also highlights the need for stakeholders to take systematic actions across different categories to strengthen grievance and redress mechanisms.

Category 1: Strengthen grievance access and user inclusivity

  • Integrate GRM access through Unified Mobile Application for New-age Governance (UMANG), DigiSaathi, Jan Suraksha0; enable business correspondents (BCs) or customer service centres (CSCs) or self-help groups (SHGs) to help users file complaints into the RBI’s Complaint Management System (CMS) or Centralised Public Grievance Redress and Monitoring System;
  • Expand IVR, WhatsApp, or USSD grievance flows;
  • Build guided DFS grievance flows on DigiSaathi and ;
  • Pre-fill fraud complaints through the Digital Payments Intelligence Platforms (DPIP)
  • Integrate UPI, OTP, or KYC error codes into complaint workflows.

Category 2: Improve data standardization and integration

  • Create a national unified grievance taxonomy;
  • Enable API-based real-time data flows;
  • Create a national GRM intelligence layer that will integrate the CPGRAMS, CMS, the DPIP, the National Payments Corporation of India (NPCI), and the State Level Bankers’ Committee (SLBC) dashboards.

Category 3: Enhance grievance resolution efficiency and timeliness

  • Enable digital workflows with CMS or CPGRAMS; automate updates and publish monthly TAT dashboards;
  • Deploy a SupTech early warning engine that will combine DPIP alerts, CPGRAMS data, CMS data (capturing grievance pendency and time elapsed since registration), and outage feeds.

Category 4: Strengthen last-mile facilitation and coordination

  • Provide BC or CSC grievance apps linked to UMANG or CMS;
  • Train BC agents to capture issues related to the DPIP and incentivize capture;
  • Establish state GRM hubs that will integrate the SLBC, CPGRAMS, DPIP, and CMS, supported by quarterly audits.

Category 5: Build awareness, trust, and consumer protection literacy

  • Integrate awareness into Jan Suraksha0, PMJDY, and SHG or CSC programs through multilingual outreach campaigns;
  • Push DPIP alerts through WhatsApp or SMS;
  • Embed safety nudges and create local fraud-watch cells.

A path forward that can build trust

Grievance resolution must become a frontline service, not a back-office burden. When a customer like Rani receives timely, fair support, it reinforces confidence in the system not just for her, but for her entire community.

However, our study reveals that today only , which reveals significant gaps in service experience and accountability.

Effective grievance and redress mechanisms strengthen financial inclusion as they ensure that every user is treated fairly, problems are solved transparently, and complaints are not dismissed or lost. When redress systems work, customers feel respected, protected, and empowered to remain active participants in formal finance.

Research shows that grievance redress or effective dispute resolution significantly increases users’ “continuance intention” to use mobile wallets and digital payments. Globally, studies by the United Nations Conference on Trade and Development (UNCTAD) find that strong dispute-resolution systems boost consumer loyalty, reduce churn, and increase repeat transactions. For India, a strong, transparent, and accessible redressal system is not a luxury- it is foundational infrastructure. As India advances toward the NSFI 2025–30 vision, strengthening grievance redressal becomes central to deepening usage, enabling safer digital adoption, and ensuring that every financial consumer feels protected within the system. By ensuring that user grievances are fairly and promptly addressed, we not only protect consumers but also sustain long-term engagement, deepen financial inclusion, and build a resilient, trustworthy digital finance ecosystem.

Every eligible grievance should be recorded, and once registered, it must be resolved as per regulatory guidelines. With the right systems and accountability, we can ensure that every person who enters the formal financial system feels protected, respected, and empowered to stay.

Every voice matters: Tracing the journey of grievance and redress for India’s LMI segment

This study analyzes how low- and moderate-income users in India navigate grievance and redress mechanisms for financial services. Based on a multi-state quantitative survey of individuals who have filed grievances, the report assesses awareness of grievance channels, patterns of registration and escalation, resolution outcomes, and user effort. The findings highlight persistent gaps in accessibility, timeliness, transparency, and institutional responsiveness, and present evidence-based recommendations to improve the effectiveness and inclusiveness of grievance and redress mechanisms. 

Will AI take over public policy in India?

For decades, governments have struggled with how to turn broad welfare goals into clear rules, such as who should be included, on what criteria, and how much support each person should receive. Policy choices around merit, reservations, and socioeconomic vulnerability have effectively decided who benefits and who does not. Public policy has always been about using imperfect information to make decisions that are as fair and just as possible. The advent of AI will turbocharge this process.

AI can now scan millions of data points, and predictions can be made in seconds. Today, technology has made it easier to identify where the floods will hit, which geographies in a country are most food insecure, which children are most likely to drop out of school, and who is most susceptible to health hazards. All this was not possible before, but AI has made it easier and faster to execute such dynamic and real-time analytics at a more local level.

We can see this shift in the core sectors. In the agriculture sector, crop insurance﷟ the PM Fasal Bima Yojana, reportedly added coverage of about 10 million hectares and 8.5 million farmers in recent cycles. These programs experiment with remote sensing and automated yield assessments. AI models can now combine weather, soil, and satellite data to help the government determine which blocks require additional irrigation support, which crops to encourage, and where to focus extension staff.

For example, our team at MSC co-designed the Bihar Krishi platform with the state agriculture department. We built a voice-first, AI-enabled interface that offers local-language audio advisories, voice-based scheme search, and personalized soil-health recommendations. The platform makes AI-driven agricultural advice accessible to more than 750,000 smallholders. It won a national DigiTech award for its efforts in farmer empowerment.

Disaster risk management follows the same path. Between 1995 and 2024, India has faced more than 400 extreme weather events and suffered more than 80,000 deaths. Annual disaster-led deaths have again crossed 3,000 in 2024–25. In this context, AI-enhanced early warnings, impact forecasting, and evacuation planning are no longer futuristic and have become an essential tool for survival. MSC’s 2025 case study, prepared for the GSMA of India’s SACHET public warning system, shows the importance of multichannel early warning systems. These systems combine cell phones with radio, television, social media, sirens, and other channels to ensure that everyone at risk is notified on time.

Use cases with potential for AI-driven improvement

Beyond these early deployments, the nation offers significant room for AI to strengthen the current public systems. India’s food security net under the National Food Security Act covers about 800 million people, each with a fixed monthly grain entitlement at a fixed subsidized price. AI layered on top of this infrastructure could make the system more responsive. It will anticipate where demand will spike due to migration and move stocks accordingly, as well as flag places where offtake is unusually low.

Education is another front where the need is obvious. The Annual Status of Education Report 2024 shows that only 23.4% of Class III children in government schools can read a Class II text, and 45.8% of Class VIII students can do basic arithmetic. AI cannot replace teachers, but it can help policymakers see, almost in real time, where learning falters and which interventions are effective. It also identifies children who consistently struggle or do not progress in basic skills.

Moreover, current developments offer a broader governance opportunity. Grievance portals and citizen feedback systems are being digitized at scale to provide policymakers a textured, bottom-up view of where the state fails and why. Alongside this, the India AI Mission is a political signal that AI is not a side experiment but part of the state’s core toolkit.

However, these examples also highlight the risks of incorporating AI into public policy. Most datasets in the country reflect imbalances in caste, patriarchy, and regional differences, alongside uneven state capacity. Models trained on this data can learn that specific communities are at higher risk, are less creditworthy, or are less deserving of support. They then quietly code that conclusion into welfare targeting, enforcement, or policing. A biased official can be challenged, but a biased model wrapped in technical language is much harder to contest.

AI systems hallucinating at scale is another source of danger. A 1% error rate in a consumer app is a problem. However, a 1% misclassification in a system that touches 800 million food security beneficiaries or tens of millions of farmers is a failure on a national scale. When crop loss models underestimate damage or when an AI-powered fraud detection system mislabels genuine beneficiaries as “suspicious,” the result is lost food entitlements, unpaid claims, and mistrust.

Cross-cutting risks also affect the overall public information space. Deepfakes can inflame tensions, synthetic news can distort public discussion, and automated micro-targeting can make it easier to manipulate opinion than to engage with it honestly. Together, these tools can reshape the environment in which people discuss, understand, and ultimately decide policies.

The realistic path now is to recognize that AI will shape policymaking and put the right guardrails in place, rather than keep AI out. We suggest several practical directions:

Adopt a risk-based framework for AI in government:

– Distinguish clearly between low-stakes uses, for instance, basic predictive analytics and dashboards, and high-stakes decisions, such as ration eligibility, disaster evacuation planning, crop loss assessment, or school placement;

– Strengthen requirements for transparency, documentation, testing, and human oversight as the impact on people’s rights and entitlements increases.

Make explainability a core obligation, not a technical afterthought:

– Ensure that when a model influences an individual decision, such as stopping a pension, it offers a clear, accessible explanation of why that decision was made;

– Build simple, human appeal routes into every high-stakes AI system, along with logs and review mechanisms, from the design stage.

Protect beneficiary data and set strict limits on reuse:

– Allow program data for defined public purposes only, with no sharing of personal data without explicit consent;

– Include no training, resale, and secondary use clauses and strong audit rights in all AI vendor contracts.

Embed AI within a broader accountability ecosystem:

– Align the use of AI with the Digital Personal Data Protection Act to set boundaries on surveillance, profiling, and secondary use of personal data;

– Equip regulators with the technical capacity to challenge algorithmic systems used in public programs;

– Enable independent researchers and civil society to audit real-world impacts.

Use India’s digital public infrastructure to set the standard:

– Make open standards and APIs, as well as privacy-aware public datasets, the default for AI in public policy;

– Create an internal registry of AI systems and publish information on those that directly affect citizens’ rights and entitlements.

When we look at the bigger picture, AI will not write and govern policies for us. It will only change how we see problems and solutions. The task is to use these tools to make informed and fair decisions. If public institutions can combine the power of AI with clear rules and accountability, they will serve the public interest better without losing sight of the people behind the data.

Based on this agenda, MSC has also cofounded the Alliance for Inclusive AI with BFA Global and Caribou. We are committed to developing practical “small AI” solutions that expand opportunity for underserved communities across the Global South.