The problem

Governments around the world allocate billions of dollars every year to benefits programs designed to provide essential support to citizens and families in need. Yet year after year, a significant share of that allocation goes unspent as eligible people never receive the support they are entitled to.

The reasons are compounding. In low- and middle-income countries, many eligible families simply don’t know which programs they qualify for. Those who do know often face a labyrinth of administrative processes that create barriers severe enough to make people give up before receiving a single payment, like complex documentation requirements, outdated eligibility databases, and multi-step digital portals.  Research across 23 low- and middle-income countries found that poverty-targeted schemes excluded between 44% and 97% of their intended recipients (Kidd & Athias, 2020).

Frontline government officials are frequently dedicated to bridging this gap. But they operate in chronically under-resourced environments, with understaffed offices and caseloads that make it impossible to give each citizen the support they need. The result is the best intentions, even backed by allocated public funds, still fail at the point of delivery.

Technology offers a real path forward, working with and through existing government structures rather than around them. Specifically, four levers stand out:

1. Smarter targeting. Data can be used to build an intelligence layer that automates eligibility checks, generates personalized scheme recommendations, and triggers proactive outreach based on citizen profiles, rather than waiting for people to wade their way through fragmented information channels.
2. Easier applications. LLM-backed natural language interfaces, including voice and text in local languages, can lower the barrier to application, automating repetitive steps and guiding citizens through what has historically been an opaque process.
3. Empowered frontline workers. Technology can take on the bulk of routine processing, surfacing only the cases that actually require human judgment. This would allow front-line workers to serve citizens better, instead of being overwhelmed by administrative volume.
4. Continuous learning. Layering a learning agenda onto this citizen-government engagement through monitoring, evaluation, and experimentation enables the system to improve over time, so that each iteration of service delivery is more effective than the last.

BenefitsAI in India

India represents an acute version of the benefits access problem. The country has over 4,650 government welfare schemes, spanning social protection, education, housing, sanitation, and public safety. State and central governments have allocated over ₹4 lakh crore (~$50 billion) to these programs. The government is committed to providing support and has allocated large amounts of funding for this, but the administrative complexity of enrollment causes many potential beneficiaries to miss out on the support they are entitled to.

IDinsight is building BenefitsAI to address this directly: an AI-enabled, end-to-end platform designed to help Indian citizens discover which programs they qualify for, assess their eligibility, complete applications, and ultimately receive the benefits they are entitled to.

The vision is for BenefitsAI to become a citizen-friendly interface that any new welfare scheme can plug into by default, natively integrated into government ecosystems so that a modern, frictionless experience becomes the standard for benefits access and public service delivery.

Current phase and approach

The team is currently in active discovery, with four focus areas driving the work:

• Eligibility Engine: Building the intelligence layer; automated eligibility checks, personalized scheme recommendations, and proactive outreach based on citizen profiles. Partners include government agencies and NGOs.
• Enabling Enrollment: For citizens who cannot self-serve, building a platform that supports enrollment through existing community networks and organizations with frontline workers.
• Self-serve Experience: For citizens who can navigate the process independently, exploring via governments to personalize the experience and layer an agentic application journey.
• Lifecycle Approach: Working with partners to deliver proactive nudges and enrollment support as citizens move through key life stages.

Discovery work involves speaking with organizations across the welfare ecosystem, scoping partnerships with government agencies, and conducting field visits with partners like TRIF. The team is actively looking for partners to run quick pilots in India to pressure-test the approach.

Active engagements

BenefitsAI is being shaped through active partnerships and scoping conversations with organizations working at different points of the welfare delivery ecosystem.

1. Transform Rural India Foundation: Frontline worker tool for VPRP enrollment

Transform Rural India Foundation works with community institutions and frontline workers, local women known as Didis, to help families in India’s poorest states access government entitlements captured in the Village Poverty Reduction Plan. Following a field scoping exercise in April 2026, IDinsight is partnering with TRIF to pilot BenefitsAI as a mobile app for these frontline workers. 

The tool will support document scanning and quality checks, automated eligibility assessment across 12 priority schemes, enrollment tracking, and pre-visit outreach to improve field visit efficiency. This is BenefitsAI’s first active pilot and is designed to generate early evidence on whether technology-assisted eligibility matching can reduce the gap between scheme allocation and actual enrollment at the household level.

2. The Nudge Foundation and Head Held High Foundation: Scoping for frontline worker tools

IDinsight is in early scoping conversations with the Nudge Foundation and the Head Held High Foundation to explore builds similar to the TRIF engagement, where BenefitsAI would support frontline workers in identifying eligible households, verifying documentation, and facilitating scheme enrollment.

Next steps

IDinsight’s team is identifying right-fit partners in India that support citizens in accessing government programs while exploring applications of this solution in South Africa and Southeast Asia. In parallel, the team is looking to run pilots to address specific problem statements and figure out how to integrate the learnings into a platform-based approach.

To learn more or explore a partnership, reach out to Sid Ravinutala (sid.ravinutala@idinsight.org) or Jahnavi Meher (jahnavi.meher@idinsight.org).