How AI Is Powering More Sustainable Retail Supply Chains

Sustainability is increasingly on the mind of every retail and CPG executive. For many, it’s part of their company values. For some, it’s a legal requirement. For all, it’s intertwined with a desire to achieve greater efficiency, reduce waste, and deliver long-term value.

A focus on sustainability has never been more urgent as the impact of our actions on the environment becomes ever more apparent, from the growing frequency of extreme weather events to a “red alert” warning from the U.N. weather agency.

In addition, consumers are increasingly sensitive to retailers’ environmental initiatives, and greater sustainability often translates to increased efficiency as well, meaning efforts to reduce your environmental impact aren’t just good for the planet, they’re good for business.

Of course, achieving sustainability and efficiency is easier said than done. The persistent attitude, especially among retailers and CPGs, is that you can only improve sustainability by sacrificing margins. That couldn’t be further from the truth, and in fact, the right approach can ultimately save you money.

That’s not to say that implementing new sustainability practices is easy. It can be complex and difficult to track CO2 emissions or reduce waste. Which is why, increasingly, companies are leveraging AI to do the heavy lifting. We’ve reached a tipping point in the development of AI that brings powerful new capabilities to every company, making leaps in sustainability possible that might have been much more costly and time-consuming to implement even five years ago.

Let’s look at how AI is reshaping the push for sustainability and driving new value for customers and stakeholders.

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Sources of inefficiency and emissions in your supply chain

When looking across your supply chain for opportunities to become more sustainable, waste is often a good place to start.

Fresh retailers manage a supply chain of short-shelf-life products that can quickly spoil. About 30% of food in American grocery stores is thrown away, and the cost of wasted food in the retail sector is estimated to be about twice the amount of profit from food sales. The approximately 16 billion pounds of food waste per year also has a big impact on the environment: manufacturing food that will ultimately go to waste causes nearly 10% of the world’s emissions.

Waste is more likely when consumer demands shift as quickly as they do today. Retailers have to factor in seasonality, promotions, diverse sales channels, and disruptions. In a recent survey, 79% of CPG companies said day-level planning was crucial for accurately forecasting and responding to consumer demands. Without accurate forecasting, inefficiencies can increase emissions at various stages in the supply chain, such as transporting goods unnecessarily.

Replenishment too has always been a vexing and complex task. Adapting to unexpected spikes in demand, minimizing stockouts, and avoiding the risks of overstocking and markdowns can be difficult to coordinate. Done right, however, replenishment can reduce handling, storage, and wastage costs across the supply chain that contribute to CO2 emissions.

All of the above inefficiencies can increase a company’s carbon footprint (as well as costs), but it can be hard to quantify the exact emissions. Companies in the EU and California need to figure out a way to do so, with the new Corporate Sustainability Reporting Directive (CSRD) in the EU and California’s SB 253 requiring companies to track their Scope 3 emissions, which are the result of activities that indirectly affect their supply chains. For retailers, the biggest portion of Scope 3 emissions comes from purchased goods, but tracking the impact is notoriously difficult.

These are just some of the opportunities to eliminate waste and add efficiency, and one of the reasons they’re such intractable problems is because they’re complex to analyze and optimize. This is where AI offers new avenues to optimize your supply chain and operations to achieve sustainability as well as cost savings.

How AI improves sustainability in retail supply chains

AI actually refers to a number of different technologies. Two of the most relevant for retail are generative AI and specialized AI. Generative AI is best for collecting, summarizing, and distributing knowledge, while specialized AI uses algorithms to perform specific functions beyond the ability of humans, like finding patterns in vast troves of data. Both offer solutions to major sources of inefficiency.

• Forecasting with machine learning. The best way to spot consumer trends and preferences that affect your inventory is using AI to analyze demand data to triangulate patterns in demand, such as seasonality or trends. AI can also consider business decisions like upcoming promotions, and factor in the influence of external events, from holidays to storms.
  AI can make connections that no human could, giving retailers a more accurate and up-to-the minute picture of demand that can avoid transporting and potentially wasting inventory and driving up emissions in the process.

• AI-directed inventory flow. Algorithms can find the most optimal process for efficient shelving, factoring in inventory levels, product availability, spoilage, backroom stock, and more to coordinate efforts that avoid overstocking and waste. With AI, stores can more accurately choose replenishment days, which makes it possible to receive more of the same products in one shipment for a more efficient and sustainable approach.

• Dynamic pricing. Algorithms can direct pricing to more efficiently manage markdown and clearance, moving inventory that can be economically and environmentally costly to stock for too long. By using AI to adjust prices and entice consumers, stores can avoid unnecessary waste.
• Greater CO2 emissions visibility. Algorithms can match CO2 emissions data to products without a major investment of time and effort. Using AI, tracking and reporting the emissions of purchased goods for regulatory compliance becomes much faster, simpler, and easier. Companies also gain the knowledge they need to reduce their carbon footprint and attract consumers increasingly in search of sustainable products.

By making data actionable, AI allows retailers to have more control over what they stock and when, ensuring an efficient operation that avoids waste, reduces costs, and improves sustainability.

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The future of AI and sustainability

Improving sustainability is about collective action, and as more retailers and CPG manufacturers begin using AI tools to optimize their supply chain and operations, we can begin to see the impact of widespread and dramatic improvements to efficiency.

By adopting these intelligent solutions, businesses can simultaneously drive both profitability and sustainability, turning what was once a challenging balancing act into a source of value for everyone.

As AI technologies continue to advance, we’ll see an even greater potential for optimizing efficiency. By embracing AI-driven supply chains and operations now, companies can reduce costs, meet regulatory requirements with ease, and lead the charge toward a more sustainable future.

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