Artificial intelligence is often seen as a growing energy concern, particularly as data center demand increases globally. The rising energy demands are a proven fact, with data center electricity consumption expected to double by 2030, but that is not the full picture when it comes to AI’s potential impact on sustainability.
When harnessed correctly, artificial intelligence has immense potential to not only help organizations understand their sustainability impact, but to accelerate emissions reduction across industries. AI tools can be one of the most powerful options we have to help organizations drive towards sustainability goals when used strategically.
Executive Director of Global ESG & Regulatory Compliance, Lenovo.
Through rapid measurement, data collection and analysis, AI tools can help us seize opportunities to create efficiency in every part of a business, from design, to manufacturing to logistics.
Complexity of measuring emissions and other life cycle impacts has been a major drawback in understanding them and managing them. However, used correctly, AI can not only reduce waste and emissions, it can uncover even more opportunities to reduce environmental impacts while capturing new opportunities and accelerating business growth.
Smarter Manufacturing Through Real-Time Intelligence
Artificial intelligence and digitalization can be game-changers when it comes to delivering real-time intelligence in the manufacturing process. Many sustainability teams struggle with the fact that different teams and IT systems with important data can be siloed within the organization, making it cumbersome to create a holistic understanding of an enterprise’s carbon impact.
AI tools paired with sensors within factories offering real-time data offer the opportunity to take a second-by-second view of a manufacturing site’s environmental impact, an approach exemplified by platforms such as Lenovo’s ESG Navigator.
Sensors in factories can capture real-time data on everything from temperature to water and emissions. AI-powered systems can instantly detect inefficiencies such as energy leaks or excessive heat, rather than waiting for manual reporting cycles, which helps avoid unnecessary costs as well.
AI in the Supply Chain: Predictive Efficiency Reduces Carbon
In the supply chain, AI holds the promise to be genuinely revolutionary. AI-driven advanced scheduling tools can help predict where parts are needed, offering teams real-time information on when and where they are needed, and how to get them there most efficiently.
By anticipating production requirements, these tools can reduce excess inventory, avoid air freight in favor of lower-emission ocean transport, and minimize waste and cost from overproduction and scrapping of excess materials and goods.
These gains may not sound significant on their own, but over time they can add up to measurable carbon reductions. Supply chain AI tools are also critical to tackling the most challenging part of corporate sustainability goals: Scope 3 emissions from an organization's value chain.
For most organizations, the biggest emissions impact is Scope 3. By anticipating demand, organizations can begin work to curb these emissions, a vital part of emissions reduction.
Empowering Customers to Make More Sustainable Choices
Artificial intelligence tools will also be vital to helping customers understand their carbon impact and empowering them to act more sustainability. The latest AI tools offer information on the real-world impact of decisions, meaning customers can have data-driven insights into the carbon footprint of purchasing decisions over the long term.
Customers want information about the real climate impact of their decisions, and in the coming years, AI tools will be able to deliver this faster and more precisely based on location, specific use information, and other factors.
Design Decisions Informed by Data, Not Guesswork
Electronic products are extremely complicated. Even understanding the carbon impact of a whole product across all phases of its life cycle is very difficult, and this is where new AI tools can help customers make sense of the complex data around a product’s carbon impact.
There’s an enormous amount of data involved in understanding the environmental impact of a product across its life cycle, from what materials are selected to how products are designed for longevity, and AI tools are going to be ever more important in better understanding the real impact of different design decisions on products both now and in the future.
New AI tools are already helping manufacturers compare the total carbon impact of different materials and design choices. They can compare different hinges from different suppliers, for example, working out the carbon impact of each with AI doing the evaluation faster than earlier tools, allowing designers access to information about trade-offs during the development process.
AI is already helping to identify more sustainable design alternatives, meaning that manufacturers can make decisions to curb emissions and material use while products are still on the drawing board.
Responsible AI as a Sustainability Imperative
One of the keys to establishing AI as a ‘force for good’ and a driver of sustainability is to ensure that AI is implemented responsibly, which requires strong governance, ethics, and long-range thinking about the impact of technology.
Within Lenovo, our Responsible AI Committee includes leaders across multiple parts of the organization including sustainability, legal, and technology, ensuring that AI solutions are developed with a view to transparency, explainability, and human oversight.
Collaboration is the New Climate Currency
Collaboration is vital to reaping the benefits of sustainable AI. This is something that requires the technology community to come together and participate in voluntary discussion and pacts, such as the European AI pact and UNESCO’s Recommendation on the Ethics of Artificial Intelligence. Organizations need to be informed participants, and work with other organizations to establish standards and new ways to work.
Standards such as the Science Based Targets initiative's Net-Zero Standard help to establish a common language as companies, government and organizations continue their emissions reduction journeys.
Many standards and frameworks are adapting or will need to be adapted so that efficiency gains from AI tools can be accounted for in their methodologies, ensuring that any gains are both comparable and real. Organizations need to ensure they are working closely with partners to align to common goals and principles of measurement.
Conclusion: Efficiency Is the Bridge Between AI and Sustainability
Through intelligent and intentional deployment, AI systems can be a driver of efficiency. AI, guided by human values, can be a defining tool that helps organizations accelerate towards their goals for a more sustainable future.
Check out our list of the best Enterprise Resource Planning (ERP) software.
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