Generative AI and Sustainability: A Shared Responsibility

In 2024, the world generated or consumed around 402 million terabytes of data daily. In the US, which makes up 40% of the global market, the demand for data centers is projected to rise from 17 GW in 2022 to 35 GW by 2030. This surge highlights the rapid advancement of technology.

Generative AI, a pioneering technology transforming business operations, is one of the most influential advancements in this rapid evolution. By automating business operations to creative content creation and designing highly personalized customer experiences, Generative AI empowers companies to innovate on an unprecedented scale. However, this technological advancement has significant consequences, especially in increasing the environmental footprint.

Data centers that support these technological advancements currently consume 1% of global electricity, a figure that is expected to increase. Additionally, their development requires significant energy consumption.

A study conducted by Columbia University indicated that training the "GPT-3" model with 175 billion parameters consumed 1,287 MWh of electricity, resulting in carbon emissions of 552 metric tons. This is equivalent to the emissions produced by driving 123 gasoline-powered vehicles for one year or equivalent to the annual power consumption of 130 US homes. Training an AI model equivalent to GPT-3 can cost up to $4 million, with some companies incurring nearly $200,000 per month solely on power consumption. The environmental impact of AI systems is considerable, as they contribute to climate change and generate more carbon emissions than the airline industry.

As generative AI drives unprecedented innovation by processing vast data, which requires substantial energy consumption, the essential question extends beyond its potential. It also encompasses whether we can leverage its capabilities without undermining the future of our planet. The challenge is not whether to pursue generative AI but how to do so responsibly. Balancing progress with sustainability is imperative: ensuring that today’s advancements do not deplete tomorrow’s resources is urgent.

What Are Tech Giants Doing About It?

At Tech Mahindra, we see the energy demands from these data centers growing exponentially, fueled by the increased adoption of AI. Global Capex investments are expected to reach $350 billion by 2026. The industry must move beyond isolated initiatives to collaborative approaches to make a meaningful difference. Adopting renewable energy at scale, advancing technologies like quantum computing, and collaborating with governments on sustainability policies are crucial steps. Mandatory measures like carbon offsets, sustainability quotas and holding companies accountable for the environmental costs of AI innovation could accelerate this shift.

This isn’t just about balancing emissions - it’s about ensuring that today’s breakthroughs don’t become tomorrow’s burdens. Businesses must embed sustainability into their core operations, creating a framework for responsible and sustainable AI growth that benefits both the planet and future generations. Tech giants are tackling the power consumption challenge of Gen AI through various innovative approaches.

Sustainable Energy Sources

Google, Amazon, and Microsoft are investing in alternative energy sources like solar, wind and nuclear energy to power their data centers, reducing their reliance on fossil fuels and lowering their carbon footprint. This shift towards cleaner energy sources is crucial, as data centers are projected to consume up to 21% of the world's electricity supply by 2030. Companies like Google and Microsoft are investing in carbon offset projects to compensate for their emissions. They are also funding research initiatives focused on sustainable computing and AI.

AI Model Optimization

Tech giants also focus on optimizing AI models without compromising their performance to reduce their energy requirements. This includes developing more efficient algorithms, pruning unnecessary model parameters, and using early stopping techniques to halt training when optimal performance is reached.

Energy-Efficient Computing and Hardware Innovations

MIT's Lincoln Laboratory researchers are developing techniques to reduce power consumption, such as power-capping hardware, which can cut energy usage by 12-15%. They're also exploring novel tools that can stop AI training early, resulting in an 80% reduction in energy used for model training.

Nvidia is working on more efficient GPU designs, including liquid cooling, which can reduce energy consumption and increase performance. Their GPUs are also designed with power limitations, allowing data centers to cap power usage without significantly impacting performance. Google and Microsoft are developing specialized AI hardware, such as TPUs and FPGAs, designed to be more energy efficient. Researchers are exploring new memory and storage technologies, such as phase-change memory and spin-transfer torque magnetic recording, that can reduce energy consumption.

Where Do Governments Fit In?

Governments play a crucial role in ensuring the sustainable growth of Gen AI by implementing policies, regulations, and initiatives that promote clean energy-related innovation.

Lessons from History

History shows that unchecked technological growth often prompts government intervention to restore balance. Renewable energy subsidies sparked a global shift to cleaner power, and safety regulations after industrial disasters saved countless lives. Even cryptocurrency, once unregulated, now faces controls aligned with societal priorities.

The stakes are higher with Generative AI. Its widespread adoption and resource demands risk environmental harm and inequality. The question is no longer whether governments should act but how quickly and effectively they can ensure AI serves the greater good.

Deploying an effective regulatory framework

Governments can require environmental impact assessments for large-scale AI deployments to ensure they do not harm the environment. The EU AI Act - with fines of up to €35 million for unsafe practices – is a positive step but only a starting point. Fragmented regulations across regions hinder progress and leave critical gaps. A global regulatory framework prioritizing sustainability and energy efficiency is vital. Governments can establish standards for data center efficiency, such as Power Usage Effectiveness (PUE) ratings. For example, the US EPA's ENERGY STAR program provides certification for energy-efficient data centers. Government and Industry, in partnership, can detail guidelines for energy-efficient AI hardware and software. For instance, the European Union's Horizon 2020 program funds research into energy-efficient AI.

A unified global standard could incentivize AI to minimize its environmental footprint, ensure that its development is safe, ethical, and sustainable, and pave the way for lasting progress.

Scaling for Impact through Investment and Funding

Regulations must be enforced and empowered. Governments can drive change through tax breaks for energy-efficient AI, green tech research grants, and renewable-powered data center subsidies. These incentives help businesses cut costs while fostering sustainability. Governments can implement carbon pricing mechanisms for AI deployments to encourage companies to reduce their carbon footprint. Direct and indirect investments in green AI infrastructure, such as data centers powered by renewable energy sources, can quickly bring about the desired change to pivot to renewable sources of energy.

The goal is to mitigate harm and reshape AI as a force for environmental good. Scaling these measures globally ensures generative AI fulfills its promise without compromising our planet.

Jointly developing or mandating targets for renewable energy for Big Tech companies.

Governments can set targets for renewable energy adoption in AI data centers. For example, Google has committed to powering 100% of its data centers with renewable energy by 2025. Governments can also incentivize companies to purchase green power for their AI operations. For instance, Amazon's Virginia data centers are powered by 100% renewable energy thanks to a power purchase agreement with a local wind farm.

The Bigger Picture: Collaboration Is Key

Imagine governments and tech companies uniting to ensure every AI breakthrough aligns with sustainability. Public-private partnerships pool resources, share expertise, and set clear benchmarks, turning sustainability into a shared goal. Through programs like Sustainability as a Service, Tech Mahindra collaborates with governments and enterprises to set sustainability benchmarks and enable greener operations, ensuring that generative AI benefits businesses and the planet.

Future-Forward Policies

What if AI systems powering your favorite apps were also eco-friendly? Future-forward policies can make this happen by incentivizing low-carbon AI models and subsidizing renewable-powered data centers. Such measures would embed sustainability into innovation, ensuring every step forward is also a step toward a greener future. Accountability of carbon impact at every application level will help bring awareness and an environment-first approach.

Building Trust Through Transparency

Trust drives sustainable progress and grows through accountability. What if every company using generative AI reported carbon emissions or underwent environmental audits? Such transparency would ensure compliance and build confidence that AI growth is responsibly managed, fostering a future where innovation and ethics thrive together.

Charting a Sustainable Path for Generative AI

Generative AI promises to transform industries and enhance lives, but its environmental impact demands urgent attention. Tech Mahindra addresses this dual challenge through renewable-powered data centers, energy-efficient AI models, and its Sustainability as a Service offering. This comprehensive solution integrates cutting-edge technology with sustainable business practices, enabling organizations to meet their ESG and climate goals. The AgentX offering exemplifies responsible innovation, balancing AI advancements with resource conservation.

Collaboration is vital. Tech Mahindra’s emphasis on public-private partnerships and forward-thinking policies highlights the importance of aligning technological progress with environmental priorities. Such programs provide actionable frameworks for businesses to enhance energy efficiency, reduce carbon emissions, and create greener business models.

The objective is not solely to innovate but to do so responsibly. With organizations such as Tech Mahindra leading the way in sustainability, we can collaborate with our ecosystem partners and clients to enable their Generative AI-related aspirations and innovations while safeguarding the planet for future generations.