Artificial Intelligence (AI) has arrived in a big way in almost every field and at all levels—from individual needs to community, city, and country. India ranks third globally in AI vibrancy, talent concentration, and real-world adoption. There are regular discussions about recent advancements and new innovations in revolutionary technologies which can help humans solve their complex problems. AI is playing a crucial role in research and development, leading to the creation of efficient and innovative solutions. From healthcare, education, transportation, and environment to computation, AI has made progress to address and help face local-global challenges.
However, AI also brings challenges in terms of conservation and management of natural resources, especially water, which is fundamental to the existence of life on earth. In the rising climate crisis, water crisis has become a serious issue to solve. This raises an important question: How can AI assist in water conservation and consumption, and what will be its implications? We look at the opportunities and challenges of AI tools and applications with examples of application of AI in managing water.
AI in Water Quality Monitoring
To calculate the Water Quality Index (WQI), one needs to check for multiple parameters. The process is laborious and has limitations resulting in inaccuracy in determining the WQI. The recent developments in AI tools for assessing water quality have the potential to provide significant improvements. It may reduce the computation power, efforts, cost and increase the accuracy of WQI as it can calculate and compute multiple parameters easily.
In future, the combination of AI and remote sensing may help and change the methods of collecting data using satellite data and on-site sensor data. For instance, a study carried out on monitoring data from Thailand (for 2016–2021) shows possibility to reduce the number of parameters for WQI calculation from 13 to four, using ANN and the Bootstrap method.
AI for Leak Detection and Water Distribution
According to experts, AI has the potential to revolutionize the future of water and wastewater systems. AI algorithms can detect changes in real time to check for quality and quantity besides identifying potential contaminants or public health hazards such as pollution plumes, waterborne pathogens, and more. AI can also be used to detect these problems and give us solutions to solve them easily.
To conserve water, preventing and minimizing wastage of water in all spheres is crucial. AI can help identify and prevent leaks in water distribution systems by analyzing data from sensors and meters. AI algorithms analyze the data and can detect anomalies in water flow and pressure indicating possible leaks. It can also check for areas in the pipeline where leaks can occur. This approach can save a significant amount of water and reduce the cost associated with leaks.
AI in Water Conservation and Smart Water Consumption
To preserve and conserve water, AI can help optimize water usage by analyzing data from various sources, such as weather patterns, soil moisture levels, and crop water requirements. It can utilize this data to gain insights and to make decisions on water allocations, from farming to industry, besides helping construct infrastructure accordingly.
AI can also help people calculate their daily usage of water at home and work. During the Water Foundation course at Ahmedabad University, there is an exercise in which students are asked to calculate their daily usage of water in their house. Apps like Water Calculator and Filo help observe and calculate water footprint including how much water one wastes. This can make people aware and realize the need to optimize the usage of water to conserve.
AI in Policy Making and Resource Management
To study water resources, one needs a lot of data which requires a huge amount of time and resources. It is hard to constantly observe and detect any changes occurring in the water resource as one can only observe a representative sample but not look into the entire system. To solve this problem, one may use AI which can help predict the outcomes and help calculate complex problems using the dataset currently present for any water resources.
AI can also assist in managing water resources more efficiently by analyzing data on water availability, usage patterns and population growth. Using AI algorithms, the government authorities can get insights from the data and take informed decisions on water allocation to different areas. When one of the water body resources is getting dried up due to daily usage of water, government can start preserving these bodies and set limits to water usage. For example, the city of Tucson, Arizona implemented AI technology in 2020 in an effort to be more proactive in managing its water system, consisting of over 4,600 miles of distribution water main pipes.
Real-World Applications of AI in Water and Sanitation Sectors
Currently, in practice in India, there are some examples of the use of AI tools, machine learning and LLMs in the water and sanitation sectors. They are:
- Safe Water Optimization Tools to combat severe water stress by predicting demand, detecting leaks, and managing quality. Several key platforms and technologies currently operating are Aquaen by Fluxgen, SmartTerra, Smart Bhujal, and CLUIX C012.
- Faecal Sludge Snap App is an app for Faecal Sludge Management system that safely collects, transports, and treats faecal sludge. Some examples include SUJOG-FSSM in Odisha, SaniTrack in Maharashtra, Faecal Sludge Snap App, and Volaser (volume-laser).
- WASH AI in India includes Sanitation Robotics, CSIS note.
These tools used in different sections is not an exhaustive list. "...deep learning has the potential to solve challenges by filling in spatial and temporal data through training to improve its predictions about surface water".
For example, 25% of the world's public-sector wastewater treatment plants (WWTPs) now use AI.
Water Consumption by AI Data Centers
Until this point we have discussed the application of Artificial Intelligence Technologies which can be beneficial in water conservation, consumption monitoring and resource management. However, for establishing and operating these industries using AI technologies, a significant amount of land space, infrastructure and natural resources are needed. There are consequences of building data centers for AI on natural resources including significant impacts on water bodies.
AI and its data centers require clean and treated water to cool servers and produce the electricity that powers them, besides to avoid blockages and the growth of bacteria in pipes. In the case of Google-owned data centers, only 20% of withdrawn water is discharged back to the water treatment plants while the rest of water is lost to evaporation. In 2022, Google, Microsoft, and Meta used an estimated 580 billion gallons of water to provide power and cooling to data centers and AI servers. That's enough water to meet the annual needs of 15 million households.
Large data centers can consume up to 5 million gallons per day, equivalent to the water use of a town populated by 10,000 to 50,000 people. Even a mid-sized data center consumes as much water as a small town. According to a study by Centre for Nature and Climate, the news at World Economic Forum tells that recent estimates suggest that accelerated AI adoption could result in an additional 4.2 to 6.6 billion cubic metres of water withdrawal by 2027, including onsite cooling and offsite electricity generation. This projection underscores the need for urgent action.
Indirect Environmental Impacts of AI
While AI could be instrumental in carrying out Environmental Impact Assessments (EIA), the use of AI technologies itself needs EIA. In addition to the direct impacts of AI technologies on water as discussed above, there are indirect consequences. AI technologies depend on powerful hardware such as GPUs, servers, semiconductors, and electronic components. When these devices become outdated, they generate electronic wastes like lead, mercury and cadmium which are toxic and if not disposed of properly, the wastes contaminate rivers, groundwater and soil.
The construction of large AI data centers requires land cleaning, large infrastructure and urban development and alteration of nearby water systems. This can disturb wetlands, rivers and aquatic habitats. For example, a 2025 environmental report noted that an Amazon data center project in New Carlisle would destroy approximately 10 acres of wetlands. AI powered data centers also contribute to greenhouse gas emissions and these large emissions can disturb the water cycle and can cause defects in seasonal changes thus affecting climate change. Current estimates suggest that data centers generate approximately 180 million metric tons of indirect carbon dioxide every year.
Ethical Concerns of AI
The modern data center—a windowless facility housing thousands of AI chips and servers that devour massive amounts of electricity and millions of gallons of water for cooling—these massive server (AI) farms are quietly reshaping our energy grids and local environments in several ways from energy consumption to water usage and environmental impacts. A powerful statement from Lincoln Institute sums up the ethical concern around AI: "A low hum emerges from within a vast, dimly lit tomb, whose occupant devours energy and water with a voracious, inhuman appetite. The beige, boxy data center is a vampire of sorts—pallid, immortal, thirsty. Sheltered from sunlight, active all night. And much like a vampire, at least according to folkloric tradition, it can only enter a place if it's been invited inside".
The AI took centre stage in the just concluded G7 Summit in France. When the UN predicts that AI will double data centre power and water consumption by 2030, we know that AI can be both an opportunity and a serious challenge to water conservation and consumption.
On one hand, AI has the power to transform how we currently monitor water quality, and how we detect leaks, wastewater management and resource allocation. Through predictive analysis, remote sensing, and real-time monitoring, AI can help governments, farmers, industries and individuals to make informed decisions to reduce water wastage and improve efficiency. On the other hand, the rapid growth of AI can be destructive for water bodies and can raise environmental concerns. The enormous amount of water usage required to cool servers, the rise of electronic waste, greenhouse gas emissions and the destruction of ecosystems due to infrastructure expansion makes AI itself to be a destroyer of the world. Therefore, the issue here is not whether AI is good or bad, but rather how responsibly humans choose to design, implement and regulate it.
A balanced approach to use these AI based technologies is that governments, industries and individuals should ensure that the AI systems are powered with the help of renewable energy sources. The water lost during cooling and evaporation should be thermodynamically preserved and reused again. The government should implement policies which encourage recycling of electronic waste, protection of wetlands and ecosystems and transparency regarding the environmental impact of these AI technologies.
AI should and cannot replace human responsibility. Instead, it should help humans to strengthen it and help them do their work easily. AI can be crucial for securing water resources for future generations. It depends on humanity's ability to maintain a balance between innovation and environmental responsibility which will help us in water conservation, consumption and management.
Looking at the opportunities and challenges, the 'AI for Good' (alias, AI for Social Good) precisely advocates intentional use of AI and machine learning technologies to solve global challenges with focus on improving human well-being, promoting equity, and driving positive social and environmental impact, particularly by aligning technology with the UN Sustainable Development Goals.
Only time will tell how far the AI applications advance and how deep that appropriates the natural resources. The water crisis is already looming across the world, India being among the worst hit. However since India is aiming to be global hub of data centers, there is something to be wary about—water and land besides well-being of humanity and biodiversity. Communities across US, Europe, Latin America and Southeast Asia are resisting such projects over their heavy demand for water, electricity and land.
Amidst the growing opposition to data centres across diverse geographies and different political ideologies, India choosing to be global AI hub in pursuit of its development anxiety is inviting heightened water anxiety in the days to come. The poor monsoon of 2026 will augment that water anxiety. There is an urgent need for advising the development-obsessed government for rethinking on its decision to be AI global hub while there are innumerable tasks on hand for local water conservation and management, which are more social issues than technological for AI to address. The community resistance on the proposed Google-Adani hyperscale data center at Adavivaram-Mudasarlova in Vishakhapatam's ecologically fragile regions because of the large-scale hill cutting, deforestation and intensive construction besides lack of environmental clearance is a case in point. It is worth questioning 'development' and 'digital progress' coming at the cost of a living landscape of hills, wetlands, forests, fishing communities, villages and millions of people whose survival depends on ecological balance.
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Manas Pandya is a Bachelor's student at Ahmedabad University and an intern at WforW Foundation; Dr. Mansee Bal Bhargava is an entrepreneur, researcher, educator, speaker, and mentor
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