RETHINKING EMPLOYABILITY: IS NEP 2020 RELEVANT FOR INDIA’S AIDRIVEN FUTURE?

Authors : Pushpa Akshaya Miriyala , Armaan Sareen , Shravani Tharanath

Abstract :

India’s flagship welfare schemes – Pradhan Mantri Awaas Yojana-Gramin (PMAY-G) and POSHAN Abhiyaan, represent landmark commitments to rural housing provisioning and nutritional security respectively. Yet persistent gap separates the administrative growth outputs with substantive development outcomes. This paper undertakes a qualitative output-versus- outcome analysis of both schemes, interrogating structural gaps between quantitative delivery metrics – houses sanctioned, anganwadi coverage, beneficiaries enrolled and lived realities of human capability enhancement. The study critically examines how implementation accuracy, convergence deficits, workforce vacancies, community level absorption mediate the translation of output impact to welfare impact. Data from NFHS-4&5 trends, CAG audit observations, POSHAN tracker data bring a systemic mark: output saturation co-existing with outcome stagnation. The paper argues for realigned evaluation that centres nutritional security and housing quality as primary indices of scheme effectiveness over mere physical completion rates.

KEYWORDS :

Maternal Morbidity, Open Defecation (ODF), Aspirational Districts, Anganwadi Health Workers (AHW), Take Home Rations, Growth Monitoring Promotion Sessions.

Authors : Linda John Obiorah, Banavath Ananditha, Mrinalini Menon, Paridhi Passi, B. R. Sanjeev Naick

Abstract :

Artificial Intelligence (AI) is proving to be a crucial technology to enhance public service and governance. This paper examines how governance frameworks and institutional capacities shape AI adoption and management within government systems. By adopting a qualitative comparative case study analysis, using India and Nigeria as primary cases and South Korea as a benchmark for successful AI governance implementation, this paper examines the governance and institutional preparedness of AI in the public sector and identifies practical lessons on building governance structures and institutional foundations for responsible AI adoption. The analysis suggests that India possesses a more evolved framework for AI governance, enforced by the National Strategy for Artificial Intelligence (2018), and the India AI Mission (2024), a well-developed digital public infrastructure, and a strong focus on the development of skills and training. The National Artificial Intelligence Strategy (2024) indicates Nigeria’s growing institutional commitment to AI, as well as notable strides towards preparedness. South Korea is introduced as a benchmark, representing a more advanced AI governance model that offers concrete lessons for developing economies. Despite these disparities, the common concerns include the disconnect between policy aspirations and policy implementation, difficulty in developing specific AI laws, and concerns about accountability, transparency, bias, privacy and digital inclusion. The study calls for specific AI legislation, autonomous regulatory bodies, and more effective data governance between developing countries. It contends that institutional building and the institutionalization process are key to having responsible, sustainable and adaptive AI governance in the Global South, and that governance progress must be measured against concrete indicators like enforcement action, institutional capacity, digital literacy rates, public accountability and operationalization of independent bodies rather than policy adoption alone.

Keywords:
Artificial Intelligence Governance, Institutional Readiness, Public Sector AI, Digital Governance, AI Regulation.

Authors : Mannat Siwach , Siddhant Pandey , Priyanshi Jha , Mishka Singh , Tarandeep Kaur , Rajnish Katare

ABSTRACT

Artificial Intelligence, as a disruptive force, is bringing unprecedented changes in the skills and competencies required for a graduate to become employable in today’s day and age; however, India’s National Education Policy (NEP) 2020 has come forward as a framework for strengthening higher education through the inclusion of multidisciplinary learning, skill development, practical exposure, and increasing alignment with industry requirements. This paper examines whether these strategies remain sufficiently responsive to an evolving AIdriven labour market. The study employs a mixed-method approach, combining a review of existing literature with primary questionnaire-based research. On the survey responses of students and professionals, the study applies descriptive statistics, frequency distributions, percentages, and mean scores to assess perceptions of implementation, AI readiness, and emerging skill requirements. Further, it uses a thematic analysis to compare the emerging patterns with themes identified in the literature. The findings indicate that although NEP 2020 provides a relevant framework for developing multidisciplinary and future-oriented competencies, gaps remain between its intended provisions and students’ practical exposure to AI-related skills, industry requirements, and employability preparation, suggesting that the policy is conceptually relevant but insufficiently aligned with emerging AI-era requirements. The study recommends increased emphasis on effective policy implementation and a shift in the core framework towards AI literacy, upskilling and greater integration of digital and data capabilities within higher education.

Keywords
National Education Policy 2020, Employability, AI Literacy, Multidisciplinary Learning, Higher Education, Future-ready Skills