NAAC’s New AI-Driven Accreditation System Set to Transform Indian Higher Education from August 2025

Introduction: A New Era of Academic Accreditation Begins

In a landmark reform for Indian higher education, the National Assessment and Accreditation Council (NAAC) is all set to roll out a revamped accreditation system in August 2025. This new model replaces physical inspections with AI-powered evaluations and digital verification, ensuring a transparent, efficient, and scalable approach to assessing academic institutions.

The changes are designed to support the goals of the National Education Policy (NEP) and expand accreditation coverage to over 90% of higher education institutions (HEIs) across India in the next five years.

From Manual to Machine: NAAC Leverages Artificial Intelligence

The current accreditation framework, which relied heavily on peer team visits, has long been criticized for complications, potential biases, and credibility concerns. The new AI-driven model removes this dependency, especially at the basic level of accreditation, by focusing on:

  • Machine Learning Algorithms to analyse institutional data.

  • Online Verification of Documents in place of in-person inspections.

  • Crowdsourced Stakeholder Validation via a pool of qualified experts.

According to NAAC Chairman Prof. Anil Sahasrabudhe, this approach improves credibility and fairness while eliminating manipulation in the assessment process.


Accreditation Structure: Two-Tier Framework with Clear Progression

The new system is divided into two tiers:

1. Basic Accreditation

  • Classifies institutions as either “Accredited” or “Not Accredited”.

  • No physical visits required.

  • Evaluation is based on parameter thresholds:

    • Universities: 55 parameters (50% required for accreditation).

    • Autonomous Colleges: 50 parameters (45% threshold).

    • Affiliated Colleges: 40 parameters (40% threshold).

2. Maturity-Based Graded-Level Accreditation

  • For institutions that meet the basic criteria.

  • Includes five levels (Level 1 to Level 5).

  • Each level introduces more complex and aspirational benchmarks.

  • Physical/hybrid visits begin only at Level 3 and above.

Institutions already accredited under previous systems (grades A, A+, A++) may apply directly for maturity-based accreditation.

How AI Validates Institutional Data

The credibility of submitted information will be determined through a unique AI-enabled stakeholder validation model:

  • A default credibility score of 0.5 is assigned to each institution.

  • The system generates a set of questions based on submitted documents.

  • These are sent to ~100 randomly selected stakeholders from a verified national database comprising:

    • Professors and educationists

    • Retired Vice-Chancellors

    • Industry professionals

    • NGO leaders and bureaucrats

Stakeholder responses will increase or decrease the institution’s credibility score on a 0 to 1 scale.

Moreover, credibility of assessors will also be evaluated using AI algorithms. Repeated inaccuracies or biases from assessors can lead to their disqualification from future panels.

Penalty for Misrepresentation

NAAC has taken a firm stance on data manipulation:

  • Institutions caught submitting false or forged documents may see their credibility score drop significantly.

  • In serious cases, institutions can be barred from reapplying for accreditation for up to three years.

Prof. Sahasrabudhe added: “We believe in trust, but with verification.”

Integrating NEP 2020 Vision

The revised framework aligns closely with National Education Policy 2020, incorporating elements such as:

  • Support for Innovation and Research

  • Multilingual and Inclusive Education

  • Multiple Entry-Exit Options

  • Sustainability Parameters

  • Internationalisation of Indian education

Even foreign universities establishing campuses in India will be eligible to apply under this new structure.

Why It Matters: The Accreditation Gap

Currently, only:

  • ~40% of universities

  • ~18% of colleges
    are accredited under the existing system.

This gap severely affects student trust, employer recognition, and international collaborations. The new model’s emphasis on accessibility, automation, and accountability seeks to bridge this divide quickly and efficiently.

Conclusion: A Digital Leap for Academic Excellence

The introduction of NAAC’s AI-driven accreditation model is a transformational step for Indian higher education. It shifts the focus from outdated manual assessments to a data-backed, tech-enabled, and transparent ecosystem of quality assurance.

The education sector must now gear up for this digital accreditation wave, which promises to be faster, fairer, and more future-ready.


Location: Pune, Maharashtra, India

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