Quantum Tiger
State AI Governance, Public Administration & Comparative Benchmarking Second Edition | Pro Bono Policy Contribution · September 14, 2026

West Bengal Artificial Intelligence Policy 2026–2029

From AI Adoption to State AI Capability — A Governance Architecture Benchmarked Against 9 Indian States

Original Publication: PDF Format
Download Original PDF Document ↓

// Authors & Affiliations

Quantum Tiger Research

Quantum Tiger Research

Applied Policy Division, Morning Bay Technology

Pro bono policy research group at Quantum Tiger providing independent, evidence-grounded frameworks for Indian government bodies and state administrations.

LinkedIn Profile →

// Executive Abstract

Following West Bengal’s June 2026 budget announcement of the West Bengal Impact AI Mission and GCC policy incentives, this report sets out a comprehensive governance architecture to move the state from consumer adoption to institutional capability. Benchmarking West Bengal against nine peer states (Odisha, Karnataka, Telangana, Tamil Nadu, Kerala, Rajasthan, Andhra Pradesh, Gujarat), the paper details 10 pivotal cabinet decisions, a 4-tier risk classification (Prohibited, High, Limited, Low), mandatory statutory AI Impact Assessments, and a Bengali-first public service delivery standard.

Research Methodology & Theoretical Framework

Comparative state policy benchmarking cross-referencing cabinet resolutions, GCC and data center policies, budget allocations, and MeitY/DPDP statutory guidelines across 9 Indian states.

Key Findings & Technical Breakthroughs

01

Institutional Gap: West Bengal announced its Impact AI Mission, but requires a statutory Mission Director, risk owners, and independent audit functions to avoid becoming a dormant press release.

02

Odisha & Karnataka Benchmarks: Transferable best practices include Odisha’s two-tier Taskforce/Cell structure and Karnataka’s Nipuna AI workforce skilling model.

03

Risk-Tiered Public Procurement: Classifies government AI into Prohibited, High, Limited, and Low risk, enforcing mandatory impact assessments on high-risk welfare systems before deployment.

04

Bengali-First Language Inclusivity: Mandates high-accuracy Bengali-language voice and text interfaces for all citizen-facing AI services to ensure digital inclusion outside urban English-speaking bubbles.

// Strategic & Operational Impact

Policy & Industrial Implications

Serves as an objective, pro-bono policy consultation draft for state legislators, administrative secretaries, industry bodies (NASSCOM, CII), and academic centers across West Bengal.

// Subject Classifications & Keywords

#West Bengal AI policy #state AI capability India #West Bengal Impact AI Mission #cross-state AI benchmark #AI risk tiering #Bengali AI language models

Related Quantum Tiger Research

Sovereign AI Infrastructure & National Compute Policy

Training vs Inference: Path to India’s AI Sovereignty

India’s enterprise AI adoption is mainstream (~87% enterprise adoption according to NASSCOM), but strategic sovereignty sits on the ability to train—not merely use or serve—large-scale models within national jurisdiction. This paper demonstrates that adoption does not equate to sovereignty. Without domestic foundation training capacity, model IP, training data, and strategic control remain offshore. We propose an actionable, funded 5-year program to establish 3–5 regional National AI Training Hubs, an IndiaAI Compute Credits facility, sectoral federated data trusts extending AI Kosh, and an Indian Sovereign Model Certification (ISM-Cert) framework.

Physics of Computation & Non-Equilibrium Thermodynamics

Thermodynamic Constraints on Artificial General Intelligence

Artificial General Intelligence (AGI) is commonly discussed as an abstract algorithmic construct. This paper argues that AGI must instead be understood as a physical system governed fundamentally by the second law of thermodynamics. We demonstrate that learning, reasoning, memory updates, and parameter optimization are inherently irreversible processes with unavoidable physical entropy production. Using Landauer’s principle (Emin = kT ln 2), statistical mechanics, and non-equilibrium physics, we derive lower bounds on the energetic cost of intelligence and establish a fundamental heat dissipation ceiling (Qmax) that constrains infinite model scaling.