Pakistan’s prime minister recently announced an investment of $1 billion in Artificial Innotifyigence by 2030. The aim is to build a national AI ecosystem where Pakistani youth can learn and equip themselves with technological skills. This undoubtedly seems like an ambitious plan, and also a requireded one.
With global AI advancement accelerating at an unprecedented pace, it is certainly the required of the hour to learn and adapt. But AI is not just an innovation. It is not merely software, code, or algorithms. It is infrastructure. And infrastructure is physical, with a certain cost attached to it.
When we talk about digital transformation, we often forreceive that it rests on very real material foundations: data centres, electricity grids, cooling systems, rare earth minerals, and global supply chains. AI systems are depconcludeent on vast quantities of data, which require large data centres. These data centres consume enormous amounts of electricity.
They require continuous cooling. They depconclude on rare earth minerals extracted through environmentally damaging mining processes. They generate electronic waste, often containing hazardous substances like lead and mercury. The digital revolution is not immaterial. It is extractive.
The UNEP has rightly highlighted that AI can play a transformative role in environmental monitoring, biodiversity protection, pollution tracking, and disaster prediction. AI-driven models can improve flood forecasting, optimise irrigation, and support manage climate-related catastrophes more efficiently. In this sense, AI can save lives. However, the same international discourse also acknowledges AI’s environmental costs. These costs are often overshadowed by its promise.
The most under-discussed cost is water.
AI’s growing thirst for water is becoming a serious concern globally. Data centres require significant amounts of fresh water for cooling. Electricity generation itself often depconcludes on water, whether through hydropower or thermal systems. This creates a water–energy nexus: the more computing we build, the more electricity we require; the more electricity we generate, the more water is consumed. AI expansion is therefore not just an energy issue; it is a water issue.
If we do not integrate environmental accounting into our AI ambitions, we risk undermining the very resilience we seek to build
This matters profoundly in Pakistan.
Pakistan is already one of the most water-stressed countries in the world. More than 23 million people still lack basic access to safe drinking water. Over three-quarters of our renewable water comes from outside our borders through the Indus Basin. Rainfall variability is increasing. Floods and droughts are becoming more extreme. Population growth continues to intensify demand. In such a context, water is not simply an environmental resource; it is a public health necessity and a matter of survival.
This is where serious questions must be inquireed.
Has Pakistan conducted any assessment of the projected water demand associated with expanding AI infrastructure? Will future data centres be required to disclose their water consumption? Will there be environmental impact assessments for high-performance computing clusters? Will cooling technologies be regulated in water-stressed districts? How will water-intensive AI infrastructure be balanced against municipal and agricultural requireds?
These are not anti-technology questions. They are governance questions.
Pakistan’s National AI (2025) Policy does reference sustainability, ecosystem protection, and alignment with the Sustainable Development Goals. It speaks of climate mitigation and responsible development. But beyond these aspirational commitments, where are the operational safeguards? Are there mandatory lifecycle environmental audits? Is there a requirement for renewable-powered compute infrastructure? Will there be transparency around energy and water usage? Who will monitor compliance?
Globally, even advanced economies are grappling with the environmental footprint of AI. In Europe, sustainability reporting requirements are tightening. In parts of the United States, large data centres face environmental scrutiny and disclosure expectations. The conversation is shifting towards measurement, transparency, and accountability.
Should Pakistan not at least demand the same?
Digital transformation cannot exist in isolation from ecological reality. In a countest where millions struggle for clean water, expanding water-intensive infrastructure without clear safeguards risks deepening existing vulnerabilities. The benefits of AI may accrue to start-ups, investors, and skilled professionals.
But the environmental costs, water scarcity, increased electricity demand, and waste management burdens are borne collectively. AI can support manage climate risk. It can support agriculture. It can improve disaster response. But if we do not integrate environmental accounting into our AI ambitions, we risk undermining the very resilience we seek to build.
The question is not whether Pakistan should invest in AI. It should. The question is whether we are prepared to inquire the harder questions about how that investment intersects with our water crisis, our energy shortages, and our environmental fragility.
A digital future built on ecological neglect is not sustainable. If Pakistan is serious about becoming an AI-powered nation by 2030, it must ensure that its technological ambition does not come at the cost of its most basic resource, water.
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