Artificial Intelligence (AI) has revolutionised how not-for-profits operate, boosting productivity and helping mission-driven organisations achieve more with fewer resources. AI tools have become indispensable in the nonprofit sector, as shown in a 2022 McKinsey survey, which reveals that AI adoption has more than doubled over the past five years, underscoring its widespread impact.
However, as we embrace the benefits of AI, it’s equally important to recognise its environmental implications. AI’s reliance on energy-intensive data centres significantly contributes to carbon emissions, making it essential for organisations to balance innovation with sustainability. This concern is particularly pressing since June 2024, when 107 countries accounting for approximately 82% of global greenhouse gas emissions have adopted net-zero pledges. Additionally, the Race to Zero campaign has inspired over 9,000 companies, 1,000 cities, and other institutions to commit to cutting global emissions in half by 2030.
Not-for-profits can lead the way in integrating AI responsibly. Even tech giants like Microsoft, which has pledged to be carbon-negative by 2030, face challenges as their AI advancements strain sustainability goals.
In this blog, we’ll explore how not-for-profits can leverage AI technologies for maximum impact while optimising their use to minimise environmental harm. From understanding the carbon footprint of AI to actionable strategies for greener tech adoption, we’ll cover all the essentials to help your organisation balance innovation and sustainability. Let’s dive in!
Understanding the Connection Between AI and Carbon Emissions
To fully grasp its environmental impact, we must first understand how AI works. Artificial Intelligence refers to systems designed to perform tasks that typically require human intelligence, such as problem-solving, learning, or creating content. Among the most transformative advancements in AI are large language models (LLMs) and Generative AI.
Large language models like ChatGPT are trained on vast datasets to process and understand human-like language. Generative AI goes a step further by creating entirely new content based on the patterns it has identified during training. You can learn more about AI and how it works by visiting our AI for charities guide.
Behind these incredible capabilities lies a significant challenge: data centres. These facilities are the backbone of AI operations, housing the hardware and software needed to train and run complex models. Data centres require extensive network and storage infrastructure to ensure uninterrupted and high levels of performance.
However, this infrastructure comes at an environmental cost. From uninterruptible power supplies (UPS) to ventilation and cooling systems, data centres consume vast amounts of energy and contribute significantly to carbon emissions.
The Carbon Footprint of AI
As transformative as AI is for not-for-profits, its environmental impact cannot be ignored. From the energy-intensive processes of training large models to the infrastructure of data centres, AI’s carbon footprint is a pressing concern. Let’s explore two primary causes of AI’s carbon footprint:
- Energy-Intensive Processes Like Model Training and Operation
- Data Centres’ Reliance on Electricity and Cooling Systems
Energy-Intensive Processes Like Model Training and Operation
AI models require immense computing power to function. Training these models involves processing vast amounts of data through algorithms, which demands powerful hardware and extended operational hours. A recent study from Cornwell University shows how Generative AI systems can use approximately 33 times more energy than machines running task-specific software. This staggering energy consumption translates directly into higher carbon emissions, particularly if the energy comes from non-renewable sources.
Data Centres’ Reliance on Electricity and Cooling Systems
AI operations depend on data centres, massive facilities designed to handle enormous amounts of data and traffic with minimal latency. These centres are vital for supporting several operations, such as data storage for charities, private cloud applications, data backups, and powering machine learning and AI tools many charities rely on.
However, data centres are significant energy consumers. Their hardware and software infrastructure require constant electricity, while advanced cooling systems prevent overheating from the high computational workloads. As reported by Forbes, the rapid growth of AI workloads further intensifies this energy demand, placing greater strain on data centres to provide more computational power with lower latency.
AI’s Potential for a More Sustainable Future
Many experts believe AI is a powerful ally in the fight against climate change. One thing is certain: AI can dramatically scale and accelerate initiatives to reduce emissions and promote sustainability.
One of AI’s greatest strengths lies in its ability to analyse vast amounts of data quickly and efficiently. AI-powered tools can help uncover hidden patterns, connections, and inefficiencies. For example, AI-driven climate models can deliver highly accurate predictions, enabling policymakers, businesses, and not-for-profits to make informed decisions and adapt strategies to changing environmental conditions.
AI is also a great tool to identify opportunities to reduce carbon emissions in supply chains, energy consumption, and resource management. Tools like Microsoft Sustainability Manager demonstrate how generative AI can streamline data collection, improve reporting accuracy, and create bespoke calculation models to assess environmental impact.
Additionally, AI’s predictive capabilities allow for better optimisation of energy systems, ensuring power is allocated more efficiently and reducing waste. For example, machine learning algorithms can anticipate peak energy usage and adapt resource allocation to minimise unnecessary emissions. These advancements open the door for not-for-profits to adopt greener operations without compromising their service delivery.
By leveraging AI strategically, mission-driven organisations can balance innovation with sustainability, ensuring their fundraising efforts align with the broader goal of a healthier planet. With the right tools and strategies, AI can be a game-changer in the journey toward a more sustainable future.
Why Nonprofits Should Care About AI’s Carbon Emissions
AI and sustainability in the nonprofit sector go hand-in-hand. For charities, caring about AI’s carbon emissions is a matter of ethics, finances, and reputation. Here’s why mission-driven organisations should pay attention to the environmental impact of the technology they use:
- Ethical Responsibility and Alignment with Core Values
- Financial Costs of Unsustainable Practices
- Public Perception
Ethical Responsibility and Alignment with Core Values
Nonprofits create positive change, but ignoring the carbon footprint of AI systems could directly contradict these missions, potentially harming an organisation’s reputation and eroding donors’ trust. Aligning operational choices with a charity’s core values strengthens its ethical foundation but also reassures supporters that their contributions are driving responsible change.
Financial Costs of Unsustainable Practices
Energy-intensive AI operations and reliance on data centres can quickly lead to soaring energy costs. By taking steps to reduce their carbon footprint, such as optimising AI usage and improving energy efficiency, nonprofits can lower these costs over time. Sustainable practices are an investment in long-term financial health, enabling charities to direct more resources toward their core missions.
Public Perception
Donors, partners, and beneficiaries expect nonprofits to lead by example in sustainability. Being proactive in addressing AI-related carbon emissions not only strengthens an organisation’s reputation but also positions it as a forward-thinking leader in the sector.
How Can Charities Reduce AI’s Carbon Emissions?
Nonprofits have a unique opportunity to adopt sustainable practices and reduce the environmental impact of AI while leveraging its benefits. Here are some practical ways to use AI tools for nonprofits efficiently and minimise their carbon footprint:
- Use Energy-Efficient and Sustainable Servers and Data Storage
- Optimise AI Workloads
- Use Local Computing When Possible
- Favour AI Tools by Net-Zero Carbon Emissions Companies
1. Use Energy-Efficient and Sustainable Servers and Data Centres
Choosing energy-efficient servers and storage devices is a great first step. Sustainable data centres can also help by using renewable energy sources to reduce dependency on fossil fuels. Additionally, cooling these facilities with liquid cooling or free cooling instead of traditional energy-intensive chillers can significantly lower emissions. Nonprofits that make these responsible choices will not only minimise their environmental impact but also align their operations with their mission to promote a greener world.
2. Optimise AI Workloads
Not every organisation needs massive AI systems. Many nonprofits can meet their goals with smaller, customised AI models tailored to their specific needs. Flexible payment options, like “pay as you go,” help charities keep costs down while being more eco-friendly. This approach not only saves energy but also reduces costs to allow nonprofits to scale AI usage based on their actual needs.
3. Use Local Computing When Possible
Running AI tasks directly on local computers that support AI can be both environmentally friendly and cost-effective. By avoiding reliance on large data centres, charities can save energy, process tasks faster, and maintain better control over their data security. Local computing is a practical way to embrace AI innovation without the high environmental price tag.
4. Favour AI Tools by Net-Zero Carbon Emissions Companies
Partnering with companies at the forefront of tech research and sustainability is another impactful step. This will also keep your charity’s legacy technology up-to-date. For example, Google has powered its data centres with renewable energy since 2017, achieving net-zero carbon emissions. Its AI solution Gemini, reflects this commitment to sustainability. Similarly, Microsoft aims to become carbon-negative by 2030 and is developing AI tools with this mission in mind. By choosing AI providers with strong sustainability goals, nonprofits can indirectly reduce their environmental footprint while supporting ethical practices.
Closing Thoughts
AI friend or foe? As AI continues to transform the nonprofit sector, it’s vital to acknowledge both its potential and its environmental impact. From energy-intensive model training to the reliance on large data centres, AI can leave a significant carbon footprint.
However, by adopting sustainable practices like using energy-efficient servers, optimising workloads, utilising local computing, favouring net-zero carbon emissions and creating a sustainable IT strategy, nonprofits can reduce this impact without sacrificing the benefits AI brings to their missions.
Addressing AI’s carbon emissions not only supports global sustainability efforts but also helps nonprofits manage costs, enhance public trust, and maintain their reputations as leaders of positive change. By making thoughtful choices and adopting greener technologies, nonprofits can strike the perfect balance between innovation and sustainability.
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