AI for NAAC Accreditation: NAAC introduces AI-driven accreditation system to transform higher education in India

AI For NAAC

The National Assessment and Accreditation Council (NAAC) is set to roll out a revolutionary AI-powered accreditation system in August, replacing traditional physical inspections with digital verification and machine learning-based assessments. This initiative aims to streamline the accreditation process, enhance transparency, and expand coverage to over 90% of higher education institutions (HEIs) in India within the next five years.

NAAC Chairman Prof. Anil Sahasrabudhe revealed that the new framework will eliminate peer team visits, which often led to delays and integrity concerns. Instead, the process will rely on verified documents, AI-driven data analysis, and crowdsourced stakeholder feedback.

The reforms are based on recommendations by a committee led by former ISRO chief K. Radhakrishnan, formed in November 2022 to revamp India’s accreditation ecosystem. Currently, only 40% of universities and 18% of colleges in India are NAAC-accredited. The new system seeks to bridge this gap while ensuring credibility.

Two-Tier Accreditation: Basic & Maturity-Based Graded Levels

The revamped framework introduces two key components:

Basic Accreditation – Institutions will be classified as either "Accredited" or "Not Accredited" based on performance across 55 parameters for universities, 50 for autonomous colleges, and 40 for affiliated colleges. Minimum qualifying scores are set at 50% for universities, 45% for autonomous colleges, and 40% for affiliated colleges.

Maturity-Based Graded Accreditation (Levels 1 to 5) – After securing basic accreditation, institutions can opt for higher tiers, where parameters increase in complexity. Existing NAAC-accredited institutions (with A, A+, or A++ grades) can directly apply for maturity-based levels.

Note: Physical visits will only be required from Level 3 onwards, conducted in a hybrid (online + on-site) format to minimize manipulation risks.

AI & Stakeholder Verification Ensure Transparency

A key innovation is the AI-powered credibility scoring system:

• Institutions submit documents, and AI cross-verifies data using machine learning.
• A randomly selected panel of 100+ stakeholders (faculty, industry experts, retired VCs, NGOs) evaluates authenticity.
• Each institution starts with a default credibility score of 0.5, which increases with validation or decreases if discrepancies are found.
• Institutions submitting fake documents face a three-year accreditation ban.

(With inputs from ANI)