Consumers these days are becoming increasingly aware of AI and other technology used by brands and retailers. Especially amid the loudening conversations surrounding security and ecological footprint, it’s crucial to ensure your AI initiatives are having the right impact and that your brand is following ethical practices.

Let’s explore three ways to reimagine technology retail and ensure that you’re building a sustainable experience for shoppers around the world — and how you can implement AI that’s thoughtful and “green.”

Shopper expectations from brands and retailers and their AI implementations

Particularly among younger generations of shoppers, a brand’s sustainability practices and effect on climate change are slowly becoming critical to build trust. Research shows that when these younger shoppers believe a brand cares about its environmental impact, they’re 27% more likely to purchase from that brand than older generations are. They’re also 15% more likely to choose it over competitors and pay a higher price for the brand’s products. And remember, younger consumers are fast becoming the group with the most purchasing power.

As brands and retailers implement more AI-powered technology, it’s crucial to pick AI that does more good than harm. In this age when states in the US are urging people to use less air conditioning even during heat waves, it’s important to note that AI has a significant impact on global warming: At the rate we’re embracing AI, it could very well be on track to consume as much power as the whole country of Ireland. Not only that, AI is “thirsty”: Training AI models, producing hardware for AI and running and cooling data centers all pollute and consume billions of liters of water.

With all this in mind, let’s look at how we can incorporate sustainable engineering to keep our AI “green.” With these practices, you can give your customers a great experience with your brand and also help you score their loyalty and trust.

Use less data

LLMs are not always the best solution for your needs. For a lot of use cases, models that are trained on domain- and industry-specific datasets are a lot more accurate and perform significantly better. Not only that, they end up consuming way less energy and water than larger models. 

For example, for multilingual customer support, consider Language I/O’s automatic AI-powered translation: We use datasets focused on your individual brand and unique needs to create accurate, context-aware translations. LLMs, on the other hand, would not give you as much accuracy since they’re more general purpose and focused. This means that they consume a lot of energy just to give you inaccurate and inconsistent results.

Ensure data security

Security is fast becoming a major part of the sustainability conversation. Data breaches don’t just ruin your brand’s reputation and cost brands and retailers millions of dollars in losses; they could also damage your customers’ trust. There have been data breaches that have directly harmed the environment by putting customers at risk. Shoppers have also become more cautious surrounding data security and privacy and demand transparency around AI: 72% of customers say it’s important to know a company’s AI policies before making a purchase.

At Language I/O, we prioritize security and ensure that customer data is protected. We also maintain a zero-trace environment. In other words, we don’t store your customer data at all. The servers on which large amounts of data are stored consume power and have high carbon emissions. Having less data is yet another sustainable practice that also helps us avoid data breaches.

Keep up labor sustainability

Research predicts that AI could displace 300 million full-time jobs — up to two-thirds of jobs in the US and Europe — which would further worsen social inequalities. Maintaining and respecting workers’ rights even during innovation is crucial. Instead of expecting AI to outperform humans and eliminate manual labor completely, a better way to look at it would be in a supporting role: Good innovation empowers employees instead of replacing them and produces new ways of working. 

Language I/O, for example, helps your current employees get accurate and instant translations right where they work so that they can support customers in any language. While our AI translation platform eliminates the need for more hiring, customer service representatives’ jobs are secure and their experience is enhanced — all this while brands and retailers are also lowering costs.

A final note on sustainability in retail

Apart from using these best practices when implementing technology, it’s also crucial to use recyclable materials for packaging, provide carbon-efficient delivery systems and cultivate a culture of resale and reuse. Several leading brands are now investing in a circular economy and encouraging their customers to buy second-hand products or even rent instead of buying. And it’s not enough if you raise awareness within your organization; ensure that you hold your suppliers and partners accountable as well. 

Your shoppers expect full transparency from you when it comes to AI and sustainability. With the right kind of AI technology, make sure to communicate with them in their language — whether it’s their native tongue or their social values — to earn their trust and boost loyalty. 
Improve shopper experience globally by offering multilingual customer support that’s powered by ethical AI. Reach out to us to speak to a Language I/O specialist and get a demo.