How AI Can Make Businesses More Sustainable

From banking to healthcare and from the restaurant industry to fashion and everything in between, the world’s top businesses are hopping aboard the artificial intelligence (AI) hype train. And with good reason — proponents of this fast-growing technology laud its potential to optimize, innovate, and transform the industries it touches. But as world leaders gather for COP28 in Dubai, it begs the question: how can AI make businesses more sustainable? 

AI has emerged as a transformative force reshaping industries and offering a plethora of opportunities to fortify sustainability practices in a wide range of industries. In response to environmental, social, and corporate governance (ESG) reporting, AI may be a powerful ally, redefining operational landscapes and fostering eco-friendly practices. From optimizing supply chains to revolutionizing waste management, its multifaceted applications of AI could pave the way for a more sustainable future.

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Enhancing ESG Reporting with Generative AI

While AI reporting is still new, its potential to keep up with the ever-evolving ESG landscape is huge. Generative AI doesn’t just accelerate processes; it ensures comprehensive strategies across diverse global landscapes. Its ability to analyze and synthesize vast amounts of data in real-time offers a better understanding of sustainability metrics, enabling businesses to make informed decisions aligned with their environmental goals. 

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“Enterprise generative AI-based platforms not only track, measure, and summarize business information more quickly and accurately, but also provide a coherent ESG reporting strategy across geographies,” explained Jeff Wong, Global Chief Innovation Officer at EY, one of the world’s largest professional services networks.

Wong believes that these generative AI platforms aren’t merely data repositories; rather, they craft coherent narratives, enabling businesses to navigate the intricate realm of sustainability reporting with finesse and accuracy. 

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Fostering a Circular Economy

Creating a more sustainable world goes much further than developing planet-friendly packaging and greener fuels. A growing body of evidence points to the need for a circular economy, or a system based on the reuse and regeneration of materials and products. 

Recycling is one part of that equation — and, AI could have a hand in improving both waste management and recycling processes. Recycling is complicated. 

Unclear rules mean that oftentimes, unrecyclable trash often ends up in the recycling plant. But, AI can help automate sorting and prevent contamination. One such example of AI in action at the recycling plant is EverestLabs, which utilizes AI to identify up to 200 objects in 12 milliseconds.

“Because of AI, because of the robotic arms, we have seen plants recover 10%, 20%, 30% more than what they have been doing previously,” JD Ambati, CEO of EverestLabs, told CNBC. “They have been losing millions of dollars to the landfill, and because of AI, they were able to identify the value of the losses and deploy robotic arms to capture that.”

This not only amplifies recycling efficiency but also fosters a circular economy. AI-driven systems streamline existing processes and pave the way for innovative approaches to minimize waste and maximize resource utilization. Beyond traditional waste management paradigms, these technologies enable businesses to rethink their strategies, reducing their environmental footprint and promoting a sustainable ecosystem.

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Supply Chain Optimization

Knowing which products will sell well, and which ones won’t, is all part of the retail game. Companies can analyze relevant data to help them make crucial decisions about what, and how much to order, predict price changes of raw materials, and more. 

Or, they can let AI take the wheel. By leveraging AI, businesses gain a holistic view of their supply chains, optimizing inventory management, reducing waste, and aligning operations for efficient production, thereby contributing to sustainability efforts. Its predictive capabilities enable businesses to forecast and prepare for changes, minimizing unnecessary waste and ensuring efficient resource allocation.

Amcor, the biggest packaging company in the world, has already begun experimenting with a platform called EazyML, which leverages AI for predictive purposes, CIO reported. 

“The early results we have are quite promising; much more than we expected,” said Joel Ranchin, the company’s global CIO. “If you can predict change, you can better anticipate your raw material needs and supplement them ahead of time if necessary.” 

These predictive capabilities help businesses forecast and prepare for changes, minimizing unnecessary waste and ensuring efficient resource allocation. 

In addition, AI can leverage data to help develop new, more sustainable products. “Large datasets can be analyzed to identify sustainable design and packaging for the shipment of these new products. AI can look for ways to use more renewable materials in the new product development process, aiding in improved sustainability,” Derek Martinez, National Director of Presales Systems Engineering at Konica Minolt, told Forbes.

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Energy Consumption

As the business landscape navigates the complexities of sustainability, it emerges as a formidable catalyst for change. Its integration into business processes offers innovative solutions to combat environmental challenges while propelling businesses toward a greener, more sustainable future. AI can monitor real-real energy and resource consumption via sensors, helping companies optimize their energy use and thus reduce their carbon footprints.

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Conclusion

AI’s capabilities when it comes to aiding in more sustainable business practices seem promising. However, amidst its promising potential, acknowledging the evolving nature of ESG objectives is crucial. These goals are constantly under the influence of local laws, cultural nuances, and global trends, necessitating a nuanced approach. Moreover, it’s imperative to confront the environmental impact of AI itself. The substantial energy demands of machine learning algorithms, as evidenced by a University of Massachusetts Amherst study, paired with AI’s proliferation across industries, underscore the importance of balancing technological advancements with ecological considerations.

While it’s clear that AI's integration into business processes could bolster sustainability, it’s a journey filled with promise and challenges, requiring not only technological advancements but also a conscientious effort to ensure that its promises of transformation don’t come at the cost of the planet.

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Sources 

Forbes

Reuters

CIO

CNBC

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This article was originally published by Certainty News [Link to Article]