AI-Data Skills Framework
A common language for mapping skills,
roles, and pathways for India's
emerging AI-data workforce.
The AI-Data Skills Framework (AISF) identifies, names, and standardizes the skills of workers who train, label, annotate, review, and maintain the datasets powering artificial intelligence systems.
It maps skills and competencies across five professional personas to India’s National Skills Qualification Framework (NSQF) and National Credit Framework (NCrF), creating a base for industry-aligned curricula and making acquired expertise more visible and portable across learning and earning opportunities.
A joint initiative by
INR 10,300 crore
Committed over five
years to the India AI
Mission and Centres of
Excellence for AI.
(PIB Research Unit 2025)
USD 1.7 trillion
AI could add as much
as this to India’s
economy by 2035.
(PIB Research Unit 2025)
16%
Approximate share of the
world’s AI talent currently
hosted in India.
(Prosus, BCG and MeitY 2026)
1 million workers
Projected size of India’s
data annotation and
labelling workforce by 2030,
as the sector’s market
value crosses USD 7 billion.
(NASSCOM 2021)
A competency framework for India's AI-data workforce
The AI-Data Skills Framework(AISF) identifies, names and standardizes these kills of the human work force that
trains, labels, annotates, reviews and maintains the datasets powering artificial intelligence systems.
It is intended as abridge governance system for an emergent occupation: a digital trade powered by human curation.
Skill Identification
Recognizes workforce skills and competencies outside conventional job classifications and mainstream skilling systems, making previously invisible expertise visible and valued.
Skill Mapping
Maps skills across five personas to NSQF and NCrF, enabling industry-aligned curricula and portable pathways for learning, credentials, and earning.
Shared Vocabulary
Establishes common skill categories for employers, workers, and skilling providers, supporting recruitment, training, assessment, credentialing, retention, and career mobility.
AI-data workers occupy a distinct professional lane
AI-data workers collaborate closely with data scientists, machine-learning engineers and other AI specialists,
but perform a different set of functions within the AI ecosystem.
AI-Data Workers
They supply foundational reality and ethical logic to AI systems, relying on human cognitive and contextual judgement to translate reality into actionable logic and help AI stay accurate, safe and reliable.
Where specialists fit: ML engineers, data scientists and other AI specialists focus on the computational engine - code, algorithms and infrastructure. They build how AI computes; AI-data workers govern what AI understands.
Five personas across the AI Data value chain
The personas map to NSQF/NCrF bands, but they should not be interpreted as a guaranteed linear career ladder.
Progression may occur through specialization or people-management pathways.
A shared framework across the AI-data ecosystem
The AISF is designed for stakeholder groups, each using the framework for a different part of the AI-data ecosystem.
POLICY PLAYBOOK
Government & Regulators
Serves as a technical blueprint to map AI-data roles to NSQF/ NCrF levels, becoming a basis for curriculum design and to NCO-2015 codes, capturing this workforce in national statistics.
INDUSTRY AND CIVIL SOCIETY PLAYBOOK
Industry and Civil Society
Provides a standardized, community-centered framework to design training, enable flexible work arrangements, strengthen skilling and career pathways, uphold worker dignity, and generate transparent, auditable metrics for diverse stakeholders.
AI Data Workers
Grants a formal occupational identity, and the basis for portable, recognized credentials that have the potential to unlock long-term job security.
BACKGROUND
About the Initiative
The AI-Data Skills Framework (AISF) builds on The/Nudge’s Common Digital Skills Framework (CDSF) and is part of Sanmati 2.0, a collaboration between the Gender x Digital (GxD) hub and The/Nudge exploring women’s participation and opportunities across India’s evolving digital value chain.
CONTRIBUTORS
TECHNICAL LEADS
Sabeena Mathayas, Mahima Taneja
RESEARCH TEAM
Deepti, Vaidehi Sahasrabhojanee
Additional Resources
Master Report
The comprehensive report bringing together the AI-Data Skills Framework, research findings, and key insights from the initiative.
Worker Experience Paper
A closer look at workers’ experiences, pathways, and perspectives within India’s emerging AI-data workforce.
Our Collaborators
