Generative AI and Environmental Sustainability: Navigating the Benefits and Challenges

Artificial Intelligence (AI) is transforming industries across the globe, revolutionizing how we work, create, and innovate. Among its most exciting branches is generative AI, which can produce everything from images and text to video and audio. For brands, marketers, and CPG packaging, the potential is immense. Yet, while the promise of AI is captivating, we are only beginning to understand its full impact, particularly when it comes to the environment.

Amid discussions about how AI will reshape society – whether through streamlining workloads or raising concerns about job security – one key area remains under-explored: AI’s environmental footprint. Will the environmental costs of AI outweigh its potential to drive sustainability, or can we strike a balance? At SGK, we’re deeply invested in both sides of this equation, working to ensure AI becomes part of the solution, not the problem.

The positive impact of AI on environmental sustainability

In the quest for environmental sustainability, different industries face unique challenges. For the packaging industry, for example, the focus is on reducing ink usage, adopting recyclable materials, and transitioning to sustainable substrates. In regions hit by soaring temperatures, the priority shifts to managing energy demands efficiently during extreme weather events. AI has the power to speed the transition to better solutions across these needs.

AI’s ability to process vast amounts of data rapidly makes it an invaluable tool for identifying patterns, predicting outcomes, and proposing innovative solutions that may be missed through traditional methods. In industries where sustainability practices are evolving to meet new regulations, shifting consumer demands, and ambitious corporate sustainability targets, AI offers an edge. It can help companies optimize supply chains, reduce waste, cut emissions, and improve energy efficiency. With such a variety of topics to be addressed, AI can help even seasoned sustainability professionals to speed research and narrow in on appropriate innovations. 

Imagine being able to predict the environmental impact of a product before it’s even made or using AI to streamline production processes, cutting down on resource use in ways previously unimaginable. This is where AI shines – allowing organizations to act swiftly and make smarter, data-driven decisions that benefit both business and the planet.

The environmental costs of AI

The environmental benefits of AI, however, must be weighed against its considerable costs. AI systems, especially generative models, require enormous computational power to operate. Training these models consumes vast amounts of energy, contributing to a significant carbon footprint. Furthermore, the hardware used to run these models – such as GPUs – carries its own environmental burden, from resource extraction to the e-waste generated at the end of its lifecycle.

The difference between building (training) and using (deploying) an AI model is stark, but both processes demand significant energy resources. We’re acutely aware of these challenges and are actively working to minimize our energy consumption and carbon output.

Mitigating AI’s environmental impact

Mitigating the environmental impact of AI starts with smarter, more efficient use of the technology. One effective strategy is utilizing shared platforms for AI computing, which eliminates the need for energy-draining, always-on dedicated servers. For example, we rely on the AWS Bedrock platform, a shared server environment that allows us to perform AI queries securely while significantly reducing our energy footprint.

Where dedicated servers are necessary, we implement energy-saving measures such as scaling down computing power during periods of low demand. This agile approach helps to reduce energy demand and cut operational costs. Additionally, SGK is exploring the use of smaller, task-specific AI models that are less computationally intensive but can still deliver results that meet business needs. By matching the right AI model to the right job, we pursue true triple bottom performance, all while delivering business and client needs.

Pushing the conversation forward

As a leader in the use of AI and generative AI technologies, SGK is committed to driving the conversation about AI’s environmental sustainability. We believe that AI has the potential to contribute meaningfully to global sustainability efforts, but we also acknowledge its environmental costs. By leveraging best practices – such as using shared platforms, optimizing energy consumption, and adopting smarter AI models – we can balance the benefits of AI with its environmental responsibilities.

AI is a powerful tool, and when used thoughtfully, it can be a force for good in advancing sustainability. SGK is dedicated to being part of that journey, helping both our clients and the industry at large navigate this balance and maximize AI’s potential in the green transition.