The Catalyst
March 2026
Artificial Intelligence is a force multiplier for the most difficult part of development work—reaching the last mile, at scale, through systems that are chronically under-resourced. However, the number of developmental organisations seriously deploying AI remains small relative to the opportunity.
Ashish Dhawan,
Founder-CEO, The Convergence Foundation
Ashish Dhawan,
Founder-CEO, The Convergence Foundation
Artificial Intelligence (AI) is no longer just a topic of conversation across The Convergence Foundation’s (TCF) networks – it is already being deployed. What is worth noting is the diversity of what it looks like in practice. The use cases span domains, mechanisms, and types of problems that resist easy summary, and that picture should shape how the broader philanthropic and development sector thinks about where to invest next. What makes the work across our portfolio distinctive is that these organisations are present close to impact, embedded in government systems, working with frontline workers, and accountable to measurable outcomes. That proximity gives them an unusually clear view of where the real bottlenecks lie, and it is shaping a thoughtful, grounded approach to how AI gets integrated: not as a technology overlay, but as a genuine response to problems they understand deeply.
Central Square Foundation (CSF) works across the EdTech ecosystem – supporting the creation of high-quality learning solutions, generating evidence on what works, helping governments adopt effective software, and creating public goods for the sector. National-level outcomes in foundational literacy and numeracy have improved under the NIPUN Bharat Mission, with CSF serving as a key knowledge partner. AI is now being brought to bear to sustain and deepen those gains. In February, CSF hosted a national dialogue on AI and education – a satellite event of the India AI Impact Summit that brought the Union Education Minister to the table alongside global philanthropies, state governments, and the leading EdTech innovators working at India's scale. At the same event, CSF released the Bharat Survey for EdTech - a comprehensive national picture of how technology is actually reaching low-income learners.
90%
Of low-income households now own a smartphone
The finding that 90% of these households now own a smartphone reframes the problem entirely: access is no longer the bottleneck. The question is whether AI can now close the gap between a device in every hand and a genuinely educated child. CSF's partnership with Anthropic – to support AI-powered tutoring, teacher coaching, and assessment tools for underserved communities – is a direct bet that it can.
The same logic is playing out in early childhood. Rocket Learning has spent years building a technology platform that reaches 5 million children and parents and 400,000 Anganwadi workers across 11 states, delivering localised learning content and AI-enabled coaching through WhatsApp, and working closely with the Ministry of Women and Child Development. Now, that foundation is being extended further. In partnership with the Government of Maharashtra and OpenAI, Rocket Learning has launched Shiksha Saathi: a multilingual AI assistant on WhatsApp that gives Anganwadi educators real-time guidance on child development, curriculum-aligned activities, and learning strategies, available in their language, on the device they already use. Maharashtra is the first state to implement this at scale, but the model is replicable across the country.
1.4M
India has Anganwadi centres across the country
Governments make decisions about millions of people based on data that is months old, gathered through surveys that are expensive, slow, and cover only a fraction of the population. Centre for Effective Governance of Indian States (CEGIS) ran a pilot this year that begins to change that arithmetic. Using Voice AI through the Listen at Scale initiative – in partnership with EkStep Foundation, AI4Bharat, and Sarvam – CEGIS deployed conversational AI calls across three live government programmes in Uttar Pradesh and Chhattisgarh: farmer registry enrollment, maternal nutrition monitoring, and an anti-filariasis drug drive. The AI handled routine interactions and triaged to human callers where needed – making high-frequency, district-level monitoring economically viable for the first time.
TrustBridge is building Large Language Model-based tools that help regulators – across power, finance, telecom, and infrastructure – draft orders that are better reasoned, more legally consistent, and less likely to be overturned on appeal. It is also automating the analysis of thousands of past regulatory orders to surface the patterns that drive remands and reversals. Improving the quality of a regulatory order unblocks capital at a scale that very few other interventions can match.
30-40%
Of particulate pollution in Indian cities is contributed by potholes and broken roads
Air Pollution Action Group (A-PAG) is developing a computer vision system that verifies whether civic defect repairs – the potholes and broken roads that contribute 30-40% of particulate pollution in Indian cities – have genuinely been completed. The tool is still being refined internally, but the underlying question it is trying to answer applies far beyond air quality: how do you verify delivery at the scale that government programmes operate?
What connects these efforts is a shared recognition that AI is a force multiplier for the most difficult part of development work: reaching the last mile, at scale, through systems that are chronically under-resourced. But this remains the exception rather than the rule. Very few organisations in India's development sector are seriously deploying AI relative to the opportunity, and the foundations to do so responsibly are not yet in place.
Recognising this challenge, TCF is building dedicated capacity, including hiring a Chief Technology Officer (CTO). The CTO will be charged with helping our portfolio in identifying high-potential use cases and building and deploying AI solutions on the ground. We are also keen to engage with others in the sector on the questions no single organisation can answer alone: around architecture, governance, and how we learn collectively from what is already working.
If these are questions you are working on, we would welcome the conversation.
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Highlights from our Network
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The Economic Survey 2026 highlights a critical structural gap in India’s innovation ecosystem: strong research capabilities but limited translation into industrial outcomes. It emphasises the need for Translational Research Centres as shared national infrastructure. This aligns closely with India’s Translational Research Initiative’s (ITRI) mission to enable long-term translational platforms that de-risk experimentation, strengthen industry-academia collaboration, and support scalable outcomes. With Anusandhan National Research Foundation’s proposed role in governing such facilities, this deve ...
Rocket Learning's Shiksha Saathi, an AI-powered learning assistant, was unveiled at the India AI Impact Summit 2026 by Chief Minister of Maharashtra Devendra Fadnavis and OpenAI's Chris Lehane. Designed to provide instant pedagogical support — from personalised lesson plans to automated reports — Shiksha Saathi equips preschool educators to deliver high-quality early learning with confidence. With this launch, Maharashtra is set to become the first Indian state to deploy an AI-enabled tool for Anganwadi educators at scale, strengthening early education for India's youngest learners. ...
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Atithi Foundation formally established a Strategic Programme Support Unit working directly with the Secretary and officials to design and drive tourism development interventions nationwide. In December, Atithi Foundation partnered with Prosperiti and NITI Aayog to draft an Ease of Doing Business in Tourism report, identifying regulatory streamlining opportunities across five states. It was also invited to the Ministry of Tourism conclave in January to deliberate on the One State One Global Destination scheme, Ease of Doing Business, the India Tourism Stack, and e-visa reforms. ...
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A Large Language Model (LLM) is an Artificial Intelligence system capable of analysing and predicting language patterns by examining large text samples, and thereby generating natural language text.
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