AI for Impact: Skilling, Inspiring, and Empowering the Next Gen
Abstract
The session brought together government policymakers, industry leaders, academia and grassroots innovators to examine how AI‑driven skilling can prepare India’s massive workforce for an AI‑led economy. After short pitches from three youth innovators demonstrating real‑world AI applications, a fireside chat with the Minister explored the nation’s strategic vision, followed by a panel that debated concrete pathways for scaling inclusive AI skilling, language localisation, public‑private partnership, and the role of AI in the Global South. The discussion highlighted concrete announcements (e.g., 100 000 youth target, 60 000 crore earmarked for ITI upgrades) and produced a set of actionable recommendations for industry, government and civil society.
Detailed Summary
- Host (Safin Matthew, VP 1M1B) welcomed the audience, noted the partnership between Meta, 1M1B and the Indian government, and framed the session around three pillars: Skilling, Inspiring, Empowering.
- He highlighted the UAEI initiative (Meta‑led AI skilling programme) that has already trained ~15 000 youth in two months, with a goal of reaching 100 000 on generative‑AI and large‑language‑model (LLM) tools.
- The host introduced the format: three brief youth‑innovator pitches (≈2 min each), followed by a fireside conversation with the Honourable Minister, and then a broader panel.
2. Youth Innovator Pitches
| Innovator | Project | Core AI Element | Impact Highlight |
|---|---|---|---|
| Nandakishore | AI for Cardio – offline desktop app for primary health centres (PHCs) | LLaMA 3.2 (11 B‑parameter) vision model fine‑tuned on 8 A100 GPUs; cross‑modal attribution visualisation | Deployed in >100 PHCs, assisting >1 000 patients; reduces 30‑40 min diagnostic delay; published in the British Medical Journal |
| Ashish Pradab Singh (Proxima AI) | Autonomous AI agent for MSME tasks (tender extraction, CRM queries, calendar mgmt) | Meta‑foundational models Scout & Maverick for reasoning, planning & tool use | Saves 15 000 minutes per month with 99.9 % compliance; 6‑9 month ROI for clients; 2023‑24 revenue ₹41 lakhs |
| Himanshu (Ayurveda GPT) | Conversational AI trained on 300 M+ Ayurvedic tokens, enabling real‑time dialogue with a “virtual Rishi” | 5.4‑billion‑parameter multilingual model rooted in classical manuscripts | Provides answers with source citation in multiple Indian languages; demoed live in Hall 14 |
All three pitches were applauded for demonstrating AI for social good and for being ready‑for‑deployment in underserved contexts.
3. Fireside Conversation – Minister Jayant Chaudhary & Aman Jain
| Topic | Key Points (Minister) | Key Points (Aman Jain) |
|---|---|---|
| AI & Employment | AI will create new job categories; India must adapt early to become a “first‑mover”. Emphasised that AI is a tool, not a threat, and that inclusive skilling will keep the “pie” (total employment) growing. | Meta sees AI as democratizing creation—no need to be a coder to build apps; stresses that AI lowers barriers for innovators, especially in the informal sector. |
| Inclusive Reach | AI should serve remote, multilingual, disabled populations. Cited existing Skill‑India Assistant (Meta‑partnered) and ongoing work on audio‑based, language‑localised content. | Highlighted Meta’s UAEI programme (15 k trained) and the commitment to expand to 100 k. Stressed the value of large‑language‑model APIs being made accessible to youth. |
| Language & Accessibility | India’s linguistic diversity (≈22 official languages, many dialects) demands multilingual AI models; announced collaboration with Sarvam on edge‑compute models that run on low‑cost devices. | Underlined that multilingual LLMs are now part of Meta’s open‑toolkit; urges the government to standardise data‑sharing across ministries to accelerate model localisation. |
| Governance & Trust | Data ownership and inter‑departmental interoperability are essential (example: weather data for farmers must sync with power‑supply data). Calls for a mental shift among officials towards data sharing. | Meta offers privacy‑first frameworks to help governments open data safely; offered Meta’s AI‑Kosh (multilingual knowledge base) as a resource. |
Announcements (explicitly made during the fireside):
- ₹60 000 crore earmarked for upgrading ITIs (Industrial Training Institutes) into AI‑ready hubs; the plan is to cluster 5 ITIs per region, each linked to local MSME ecosystems.
- Extension of the Skill‑India Assistant (a conversational portal for learners) with new APIs for regional language content.
- Commitment to develop a national “Skill Census” to map existing skills across the workforce (suggested as a complement to the upcoming caste census).
4. Panel Discussion – Moderated by Manav Subodh
The panel brought together the eight speakers listed in the agenda. The dialogue revolved around four thematic pillars:
4.1 Government‑led Data & Interoperability (Pankaj Kumar Pandey)
- Stressed the need for cross‑departmental data pipelines (e.g., weather ↔ irrigation power).
- Described a workshop that gathered “second‑in‑command” IT heads from all ministries to design shared data standards.
- Called for industry and academia to co‑create open‑source toolkits that ingest heterogeneous governmental datasets.
4.2 Multilingual AI & Grass‑root Reach (Buddha Chandrasekhar)
- Explained Anuvadini AI: a visual‑learning model that describes images in 22 Indian languages, addressing the gap in skill‑books that lack textual captions.
- Shared a field anecdote: a painter could not use a skill‑book because it was purely visual; solution was audio‑based, language‑localised content.
- Advocated for neutralising regional dialects into a common linguistic layer to make AI tools truly inclusive.
4.3 Innovation at the Bottom of the Pyramid (Deepak Bagla – Atal Innovation Mission)
- Highlighted 10 years of AIT (Atal Innovation Mission) – now the world’s largest grassroots innovation programme with 1.1 crore young entrepreneurs.
- Described hackathons that generated 25 lakh prototypes; showcased a 9‑grade student who secured a spot at a global robotics Olympiad within 96 hours.
- Envisioned a single dashboard linking school labs, incubators, mentors and policymakers to orchestrate collaboration.
4.4 Skills → Employability (Rishikesh Patankar, NSDC)
- Stated that skilling produces employability; the current budget explicitly links funding to job‑ready outcomes.
- Emphasised lifelong‑learning pathways across sectors (logistics, marine, aviation) and the role of modernised ITIs as “21st‑century Indian Institutes of Technology”.
- Called for private‑sector mentorship to keep curricula aligned with industry demand.
4.5 Public‑Private Partnerships (All Panelists)
- Industry ask: Share real‑world problem statements, co‑design training modules, and provide up‑skilling for government trainers (many of whom still teach outdated curricula).
- Government ask: Industry to pilot AI tools in government services (e.g., predictive maintenance for irrigation pumps) and participate in governance of AI‑ready ITI clusters.
- UN perspective (Darrin Farrant): India’s experience can serve as a template for the Global South; the UN will facilitate knowledge‑exchange platforms to avoid an AI divide.
5. Closing Reflections
- The moderator summed up the discussion: AI leadership is measured not by model size but by the number of people equipped to use it.
- A final thank‑you was extended to the institutional partners (Lloyd Business School, JIMS) and to the audience for their engagement.
- The session ended with the tagline “AI for all – Skilling, Inspiring, Empowering” and a reminder that investment in youth is investment in impact.
Key Takeaways
- Scale Ambitions: 100 000 youth will be trained on generative AI within the next few months; 15 000 have already completed the program.
- Funding Commitment: ₹60 000 crore dedicated to modernising ITIs, creating regional clusters that link training, MSME needs and industry partners.
- Multilingual Inclusion: Projects such as Anuvadini AI and collaborations with Sarvam aim to deliver AI‑powered content in 22+ Indian languages, making skilling accessible to non‑English speakers and the disabled.
- Data Interoperability: Government ministries must adopt a shared‑data mindset (e.g., linking weather, agriculture and power data) to enable AI‑driven service delivery.
- Public‑Private Collaboration: Industry is urged to co‑design curricula, provide real‑world problem sets, and mentor trainers; governments will open data and pilot AI tools in public services.
- Grassroots Innovation: Youth‑led hacks and prototypes (e.g., Proxima AI, Ayurveda GPT, AI for Cardio) demonstrate that AI can solve localized problems ranging from primary healthcare to MSME workflow automation.
- Global South Leadership: India’s diverse linguistic and socio‑economic landscape makes it a benchmark for other emerging economies; the UN will leverage India’s lessons to bridge the global AI divide.
- Skill Census Proposal: A national skill census was suggested to map existing competencies, identify gaps, and guide targeted up‑skilling interventions.
- Human‑Centred Perspective: All speakers emphasized that AI should augment human intelligence, not replace it; the goal is to make citizens “happier, more productive, and more empowered”.
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