UP.AIACT.IN
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28 Stakeholders. 4 Editors. 10 Sectors. 1 Uttar Pradesh.

India's first AI Transformation Report and Matrix on the State of Uttar Pradesh, India
The AI Transformation Matrix: Problem Statements
Powered by AIACT.IN, the matrix offers a consolidated version of 77 distinct recommendations in the form of "Sectoral Playbooks" from the UP.AIACT.IN Report 2026.
Sector
Private Data Centre Operation, Resource Planning
Sectoral Sub-issue
Sustainable Infrastructure and Resource Constraints
Problem Statement
- Traditional data centre planning treats water and cooling infrastructure as an afterthought, exposing inland states to severe structural failure since landlocked geographies cannot replicate coastal mitigation strategies like municipal desalination plants.
AI Intervention Layer, defined*
*India's IT Minister once said there are 5 layers of AI (there could be more or less). Hence it becomes necessary to define which specific AI layer was targeted in our policy recommendation for this problem statement.​
- Deployment of non negotiable WUE performance baselines within the single window clearance mechanism, requiring live compliance publishing within the first operational year.
Here's what we Recommend.
- Actively invite private data centre operators to establish facilities in identified UP zones, providing state offered incentives including dedicated power infrastructure access, land allocation at UPSIDA rates, and single window clearance. Study the cautionary Vizag precedent where Google's original 1 GW hyperscale data centre design was forced into a total cooling redesign to switch to air based cooling after its water based evaporative cooling proposed to consume between 7 and 19 million litres of freshwater per day.
Possible Mandate Recommended for the Uttar Pradesh State Government
- The state must treat water and cooling infrastructure as a first order planning constraint and embed a mandatory Water Usage Effectiveness standard of 0.36 to 0.48 L/kWh for all data centres above a defined capacity threshold as a publicly disclosed performance obligation.
Measurable Impact of our Recommendations
- Compliance data is published transparently on the UP government database within the first operational year, ensuring that data centre scale does not deplete regional water security.
Possible risks
- Failing to enforce strict landlocked water constraints, resulting in severe competition with regional agricultural or municipal freshwater allocations.
Possible Economic Spillover of the Policy Move
- Direct protection of public utility infrastructure by shifting resource optimization and cooling technology costs entirely onto the private operators.
AI Policy Severity Index*
*Derived directly from the 77 foundational structural challenges evaluated across ten industries within the UP.AIACT.IN Report, the AI Policy Severity Index functions as an evidence-based diagnostic tool designed to classify grassroots operational friction that emerges prior to the rollout of artificial intelligence systems.
Primary Severity Level
- Level 3: Technical & Data Infrastructure Bottleneck
Secondary Severity Level
Level 1: Systemic & Policy Ambiguity
Primary Stakeholder Group
Frontline Practitioners & Field End-Users, Technical Architects & Systems Engineers, Executive & Policy Decision-Makers
Stakeholder Hierarchy
Frontline Execution Layer
In which Chapter of the UP.AIACT.IN Report 2026 can you find this recommendation?
Chapter 7
Level 3: Technical & Data Infrastructure Bottleneck