India AI Impact Summit 2026

reskilling-for-tomorrow-ai-sustainability-and-indias-jobs-transition

6 min read

TRACK:Human Capital
SPEAKERS
  • Dr Arunabha Ghosh, Council on Energy, Environment and Water (CEEW)
  • Dr Claire Melamed, UN Foundation
  • Mr Nirmit Parikh, Apna Jobs and Bluemachines AI
  • Ms Aditi Jha, LinkedIn India
  • Ms Sabina Dewan, JustJobs Network
SESSION OVERVIEW

India's move toward a green and digital economy is reshaping jobs, skills, and employer expectations. This panel examines how AI and automation can support skill mapping, personalised training, and workforce transitions—while addressing challenges of access, trust, and inequality. Policymakers, industry, training providers, and technology experts will discuss how India can prepare workers for emerging green and tech-enabled roles and build inclusive, future-ready skilling systems.

VIDEO RECORDING

Reskilling for Tomorrow: AI, Sustainability, and India’s Jobs Transition

Abstract

The panel examined how AI and the green transition are reshaping India’s labour market. Speakers debated global‑level governance, wealth redistribution and migration, then turned to the twin pressures of climate change and AI on employment. They emphasized the need for local, place‑based analysis of job impacts, highlighted recent survey data on Indian firms’ AI adoption, and outlined emerging skill pathways—particularly in AI‑enabled “forward‑deployment engineering” and evaluation work. Policy recommendations centred on proactive government action, social‑protection redesign, and coordinated multi‑stakeholder partnerships to build inclusive, future‑ready skilling systems.

Detailed Summary

Dr Arunabha Ghosh opened the discussion by framing job transition as a global governance challenge. He noted that traditional social‑protection schemes are administered nationally or locally, but the redistribution of wealth in the age of AI‑driven automation is complicated by the fact that winners and losers often reside in different jurisdictions. He argued that new trans‑national institutions will be required to manage short‑term wealth transfers, even though political obstacles are formidable.

Ghosh then shifted to migration as a politically sensitive lever: societies can move money to where workers are, move workers to where money is, or relocate jobs themselves. In the context of climate‑induced displacement, this becomes even more pressing.

Key point: Migration—both demand‑pull (seeking better markets) and climate‑push (environmental distress)—must be factored into any global‑level policy response.

2. AI Meets Climate: Who Gets Affected First?

Ms Sabina Dewan responded, emphasizing that AI disruption cannot be examined in isolation from climate change, energy transition, pandemics, and trade shocks. She cautioned against siloed analyses and highlighted local decision‑making: individuals and families decide on jobs based on immediate, place‑based considerations, not abstract sectoral forecasts.

Sabina also challenged the prevailing narrative that developing economies will be less affected because most work is informal. She argued that >90 % of Indian employment is formal (or “one in ten jobs is formal”), meaning that disruptions to formal, higher‑skill jobs can have a disproportionate impact on youth and on the broader economy through multiplier effects (e.g., layoffs in Bangalore’s IT sector cascading to restaurants and services).

Key insight: The macro‑level view must be complemented by granular, socioeconomic segmentation to capture the true depth of AI‑ and climate‑induced job displacement.

3. Government‑Side Guidance: Managing the Transition

The moderator (Pragya) asked Sabina how governments could consciously manage this transition. Sabina replied that the problem is often under‑counted; better measurement is essential before any policy can be crafted.

Recommendation: Governments should invest in robust, place‑based job‑impact mapping before designing interventions.

4. OpenAI’s Role: Data, Surveys, and Upskilling Initiatives

Mr Nirmit Parikh (representing OpenAI via “OpenAI Academy”) presented the organization’s contribution:

  • Economic research – OpenAI’s chief economist, Dr Ronnie Chatterjee, leads a research function that tracks AI adoption and its job impact.
  • Blueprint & Report – A 2023 blueprint, produced with India’s chief economic advisor, examined potential job loss and the evolving AI landscape.
  • Survey of 650 Indian firms – Conducted with ICRIER, the survey revealed:
    • Hiring slowdown but overall job‑growth within firms.
    • Productivity gains across functions (engineering, finance, legal, HR) due to AI adoption.
  • OpenAI Academy – Offers free AI‑skill content for teachers and professionals, together with certifications that boost employability.

Parikh stressed that upskilling can be faster when AI tools are used for training, and that AI‐augmented productivity should be leveraged to design reskilling pathways.

Data point: 650 surveyed companies report increased internal productivity despite slower hiring, indicating AI’s role in efficiency rather than outright job loss.

5. Emerging Skill Pathways: Green & AI‑Centric Jobs

Ms Aditi Jha (LinkedIn India) – although her specific remarks are not verbatim in the transcript – is referenced as having presented data on the premium on green and AI skills in the labour market.

Mr Nirmit Parikh then outlined concrete future job categories that India could cultivate:

  • Forward‑Deployment Engineering (FDE) – Specialists who translate AI models into sector‑specific applications (e.g., AI for trucking).
  • Evaluation (Evals) Professionals – Experts who test AI systems for reliability, bias, and localisation in India’s multilingual, multisectoral context.

Parikh highlighted that Apna Jobs and Bluemachines AI are already building data‑sets and frontier labs for these roles, positioning India as a future hub for AI‑training data.

Key insight: The competition will shift from who owns a job to who can effectively use AI; thus, upskilling in AI‑augmented workflows is critical.

6. International Governance & AI Risks

Dr Claire Melamed (UN Foundation) moved the conversation to the global governance arena. She noted that international AI discussions are fragmented, covering safety & existential risk alongside employment. While these threads overlap, she argued they should be treated as distinct conversations.

Claire suggested that governments should re‑apply familiar policy tools (skills development, social protection) to the AI context, but with heightened urgency and specific actions tailored to AI’s unique risks (e.g., data privacy, algorithmic bias).

She warned that many governments are reluctant to discuss costs, preferring high‑visibility projects (e.g., data‑center inaugurations) over concrete transition policies.

Policy gap: A shortage of leadership and accountability on AI‑related transition costs hampers effective governance.

7. Panel Consensus & Closing Remarks

The moderator attempted to close the session, summarising the collective take‑aways:

  • The transition requires clean labor markets paralleling clean energy markets.
  • Data‑driven tools (e.g., LinkedIn’s insights, Apna Jobs’ platforms) and institutional research (OpenAI’s surveys) are essential.
  • Collaboration across stakeholders (government, industry, academia, NGOs) is mandatory; no single actor can solve the challenge alone.

The panel ended with a series of thank‑you acknowledgements, underscoring the urgency: “All sorts of sirens and bells are going off…we have to wake up.”

Key Takeaways

  • Global redistribution mechanisms are needed because AI‑driven winners and losers often reside in different countries, making traditional tax‑based wealth transfer ineffective.
  • Migration (both demand‑pull and climate‑push) will be a major, politically sensitive lever in labor‑market adjustments.
  • Formal employment dominates the Indian economy (>90 %); disruptions to these higher‑skill jobs can cause severe multiplier effects across the broader economy.
  • Local, place‑based analysis is essential; macro‑level sector forecasts miss the nuanced decision‑making of workers and families.
  • OpenAI’s research and the 650‑company survey reveal that AI adoption is raising productivity across functions while slowing hiring, suggesting a shift toward AI‑augmented work rather than outright job loss.
  • Free upskilling resources (OpenAI Academy, certifications) can accelerate reskilling and improve employability.
  • Emerging Indian skill niches include Forward‑Deployment Engineering and Evaluation roles, critical for adapting AI to sector‑specific and multilingual contexts.
  • Governments should repurpose familiar policy tools (skills development, social protection) for AI, but must act swiftly and transparently on AI‑specific risks.
  • International AI governance remains fragmented; safety and employment concerns need distinct but coordinated conversational tracks.
  • Effective transition demands multi‑stakeholder partnership—government, industry, academia, and NGOs must collaborate intentionally to create “clean labor markets.”

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