The Ministry of Communications, through its Department of Telecommunications, has inaugurated the “AI for Good Lab Workshop: From Strategy to Impact” in partnership with the International Telecommunication Union (ITU) at India Mobile Congress 2026 in New Delhi. The workshop marks a shift from global AI policy discussions to practical deployment and locally relevant solutions, particularly for the Global South.
Union Minister Shri Jyotiraditya M. Scindia addressed the gathering, stating that the success of artificial intelligence should be measured not by the size of its models, but by how many human lives it improves. He emphasised India’s philosophy of universal welfare while noting that 2.2 billion people worldwide remain offline, and technology must expand opportunity rather than concentrate it.
Key facts
- Workshop held at India Mobile Congress 2026 in New Delhi
- Joint initiative of Department of Telecommunications and International Telecommunication Union
- India is one of ten pilot countries selected by ITU for the AI for Good Lab framework
- Over 38,000 high-end GPUs onboarded at one-third of global average cost; 20,000 more being added
- AI Kosh platform unlocking datasets across agriculture, healthcare, and education
- Indian developers contribute 5.2% of open-source AI projects with ten or more stars on GitHub
- Sanchar Saathi tool disconnected 7.14 crore fraudulent mobile connections and traced 35 lakh lost handsets
- IndiaAI Mission funded with over Rs 10,000 crore
- Telecommunications Engineering Centre developed national AI standards on fairness, robustness, and incident reporting
What is the AI for Good Lab framework
The workshop introduced a three-pillar framework designed to help countries overcome barriers to AI adoption. The first pillar, AI Readiness and Policy, assesses gaps in policy and establishes practical governance frameworks tailored to each country’s needs. The second pillar, AI Skills Development, focuses on building national talent through capacity-building and training programmes. The third pillar, Public AI Infrastructure, creates standardised, interoperable environments where countries can test, validate, and scale AI solutions before broader deployment.
The framework recognises that many countries face similar obstacles: insufficient technical skills, fragmented innovation efforts without coordination, and missing or inadequate computing infrastructure. By addressing these three areas together, the lab aims to accelerate the journey from policy intention to real-world impact.
India’s AI infrastructure and readiness
India is bringing its own experience and infrastructure to support this global initiative. The government has invested over Rs 10,000 crore in the IndiaAI Mission to build domestic AI capabilities. A key achievement is the availability of high-end graphics processing units (GPUs), which are essential for training AI models. India has onboarded more than 38,000 GPUs at approximately one-third of the cost charged globally, with plans to add 20,000 more. This makes advanced AI development accessible to startups, researchers, and institutions that might otherwise be priced out.
The AI Kosh platform is making datasets publicly available across three critical sectors: agriculture, healthcare, and education. These datasets enable developers to build solutions tailored to India’s needs without starting from scratch. India also leads globally in AI developer penetration relative to its population, with Indian developers contributing approximately 5.2% of high-quality open-source AI projects on GitHub.
Building trust in AI through standards and safety tools
Beyond infrastructure, the workshop highlighted the importance of building trust in AI systems. India’s Telecommunication Engineering Centre has developed national standards governing AI fairness, robustness, and incident reporting. A National Working Group on AI Standardization has been established to ensure alignment with global benchmarks set by ITU-T.
The government has already deployed practical AI tools to address real harms. Sanchar Saathi, an AI and data analytics platform, has disconnected over 7.14 crore fraudulent mobile connections, traced more than 35 lakh lost handsets, and prevented financial fraud worth over Rs 5,000 crore. This demonstrates how AI, when combined with rigorous safeguards, can protect citizens while expanding access to communication services.
India’s role as a pilot country
India has been selected as one of ten pilot countries participating in the AI for Good Lab initiative, alongside partners from Africa, Asia, Latin America, and the Gulf region. India’s model centres on shared computing resources, openly available datasets, and Digital Public Infrastructure—the building blocks that have enabled India to provide services to its population at scale. By sharing this model with the Global South, India aims to help other countries develop AI ecosystems that are innovative, inclusive, and secure.
What this means for you
If you work in agriculture, healthcare, or education, you may gain access to AI tools and datasets developed through this initiative. If you are a developer or researcher, the expanded GPU infrastructure and open datasets make it easier to build AI solutions without large capital investment. If you are a mobile user, the focus on AI safety and standardisation reinforces efforts to protect you from fraud and harmful uses of technology. More broadly, the workshop signals that India is positioning itself as a leader in shaping how AI is developed and deployed globally, with emphasis on practical benefits for ordinary people rather than concentration of technology in wealthy nations.
What happens next
The workshop concluded with commitments to move from dialogue to implementation. Follow-up actions will focus on structured roadmaps for institutional engagement, identifying priority sectors for AI adoption, and establishing knowledge-sharing mechanisms across the Global South. The Department of Telecommunications will continue coordination with the ITU and other pilot countries to translate the lab framework into working programmes.