Circular and Progressive: Using AI to Manage E-Waste

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“India strongly advocates the P3 (Pro Planet People) approach and remains committed to sharing its experiences and learnings with the world in its journey towards a ‘Circular Economy,” declared the Indian Prime Minister (PM) Narendra Modi in March 2025. Addressing the crowd gathered at the 12th Regional 3R and Circular Economy Forum in Asia and the Pacific, PM Modi highlighted the importance of ‘reduce, reuse, recycle’ (3R) and circular economy principles for ensuring resource efficiency and sustainable urban development.

There is a particular urgency to apply these principles to the management of e-waste. India, currently the third-largest producer of e-waste after China and the United States (US), generated nearly 3.8 million metric tonnes (MMT) in 2024representing a 100 percent surge over the mass of e-waste produced in the past decade. This is largely a result of increased disposable incomes, enhanced technology adoption,  and faster urbanisation.

India is currently the third-largest producer of e-waste after China and the United States, and generated 3.8 million metric tonnes (MMT) in the fiscal year 2024.

Households account for 70 percent of the e-waste generation in India, whereas businesses account for the rest. Although figures are available for the types and proportion of household e-waste (demonstrated in the second figure below), a comparable breakdown for business-produced e-waste is hard to estimate. The latter includes items such as—industrial refrigerators, centralised air conditioners, commercial washing machines, industrial printers and copiers, lab equipment, desktops, and servers—most of which have shown a steady rise in usage.

Source: Compiled from Fortune and Redseer data

The challenge of recycling or safely disposing of the mounting e-waste is now officially global. The World Health Organisation (WHO) has noted that of the 62 MMTs of e-waste produced globally in 2022, only 22.3 percent was documented or catalogued as being ‘formally collected’ and ‘recycled’. This is especially worrisome because informal e-waste recycling efforts pose serious health risks, with children and pregnant women at the forefront. Millions of women and child workers in the informal collection and recycling sector globally may have already been exposed to hazardous e-waste.

Traditionally, the inability to scale up material recovery and separation has been a major impediment to e-waste recycling efforts in India and elsewhere. A steady feedstock of recyclable material, appropriate technology to sort and process the waste, and a reliable downstream market for the recycled material must be carefully aligned. This coordination is difficult to manage and is further complicated by the need to operate at an industry scale—where ‘materials are accessed at the right time, price, and quality’.  

Deploying AI

The advent of Artificial Intelligence (AI) has started to transform e-waste management in several countries. However, its deployment for this purpose in India is still at a nascent stage. The ‘National Strategy for Artificial Intelligence’ (2018) makes a fleeting mention of waste management in the context of smart cities, noting that AI integration and smart solutions could help ameliorate the ‘improper disposal of waste’. The Strategy does not elaborate any further on this, but certain municipal bodies, startups, and other firms have in fact begun to experiment with AI to tackle the e-waste menace, with encouraging results.

In this context, employing AI to improve e-waste collection marks the first step. The Bhopal Municipal Corporation, for example, has built an AI-powered system that collects real-time data from sensors and Global Positioning System (GPS) trackers placed on its waste collection trucks. It analyses waste loads, types, and possible truck routes,  resulting in a 30 percent increase in collection efficiency—with positive implications for subsequent e-waste segregation—and significant fuel savings.

So far, India’s core strength appears to be in the area of using AI to sort e-waste and identify materials for recycling.

Thus far, India’s core strength lies in using AI to sort and segregate e-waste and identify recyclable materials. As the founder of Metastable Materials—a lithium-ion battery recycling company—says, “AI-powered sorting systems with advanced image recognition accurately identify and categorise e-waste, improving material recovery efficiency. X-ray fluorescence technology, combined with AI, analyses the elemental composition of e-waste, enhancing the recovery of valuable metals like gold, copper, and rare earth elements.”

These approaches have gained considerable traction. The Pune Municipal Corporation (PMC) employs AI-driven sorting technology at waste processing facilities. Drawing on machine learning (ML) and computer vision, the PMC’s system identifies recurring patterns in materials, automatically sorts recyclables from non-recyclables. Over time, it has recorded a 95 percent accuracy rate in distinguishing plastics, metals, and organics. Robotics is another domain being harnessed to support e-waste management, with the Ahmedabad-based startup—Ishitva Robotic Systems (IRS)—building an AI-based robot called ‘Sanjivani’ (lifeline) that sorts and segregates up to five tonnes of waste per hour. Not only does an agent such as Sanjivani tackle issues of speed or accuracy, but it also saves human sorters from otherwise inevitable health hazards.

In response to the demand for e-waste solutions, a vibrant ecosystem of startups and partner institutions has mushroomed. They have a variety of competencies—from using AI to separate dangerous substances from e-waste before the recycling process, or operating state-of-the-art recycling facilities themselves, to offering cloud-based platforms that connect waste generators with authorised recyclers, and providing office liquidation and data destruction services. These initiatives aim to manage electronic assets more responsibly and build a safer and healthier environment.

While AI is increasingly viewed as the next frontier in smart e-waste management, many commentators have urged caution. The use of generative AI and Large Language Models (LLMs) could itself cause volumes of e-waste to increase exponentially. According to a recent study published in Nature Computational Science, e-waste generated by large language models (LLMs) alone—including all computer resources required to train AI across sprawling data centres—could reach at least 2.5 million metric tonnes annually by 2030. As Indian startups such as Sarvam AI (which has been selected by the central government to build India’s first AI model), Krutrim, and CoRover.ai look to build their foundational LLMs, the mechanisms they put in place for recycling their waste will be crucial.

Conclusion

As World Environment Day 2025 approaches, stakeholders must remind themselves of the dangers of e-waste and the need to work together to find solutions that prioritise safety, sustainability, and efficiency. The Indian government recognises the importance of the issue, and its 2016 E-Waste (Management) Rules, and its subsequent revisions, provide a framework for ‘mainstream[ing] and modernis[ing] the recycling industry with the help of the Ministry of Electronics and Information Technology.’ As this modernisation process advances, the country must seize opportunities to scale up AI solutions, while remaining sensitive to the new waste-related risks associated with AI. 

As the modernisation of the e-waste recycling industry progresses, India must seize opportunities to scale up AI solutions, while remaining sensitive to the new risks AI poses.

The examples in this article demonstrate that targeted AI applications can sort e-waste in bulk, improve material recovery for recycling, and optimise waste collection routes. Nonetheless, India can strive for significantly more in this regard. Nearly 80 percent of the environmental impact of most electronic products is determined at the design stage when materials are selected to make them. AI could help identify alternate materials for prototyping, testing, and creating products that contain a larger proportion of recyclable materials and are better aligned with the tenets of the circular economy. More broadly, AI should be better integrated into supply chain management practices of device and electronics manufacturers to help them streamline operations, minimise material usage, and reduce e-waste generation. Companies must internalise the idea of shifting to circular supply chains.

Addressing the perils of e-waste has become the need of the hour. With emerging alliances between policymakers, city authorities, industry representatives, and researchers, alongside the launch of public awareness campaigns focusing on immediate actions and longer-term behavioural change, India is on its way to tech-enabled circularity.

Anirban Sarma, Director, Centre for Digital Societies, Observer Research Foundation.

• Climate, Food and Environment
• Urbanisation in India
• Urbanisation
• Climate Change
• India
• ai for e waste management
• ai in e waste management
• e waste
• e waste in 2025
• e waste management
• e waste management using ai

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