As an increasing number of key sectors pull away from sustainability targets and commitments, Retail Systems news editor Alex Leonards speaks to two retailers who have deployed cutting-edge technologies to meet their sustainability goals, and examines the challenges they have faced on their journey towards greener operations.

2025 has marked a turning point for sustainability. The inauguration of Donald Trump in January has sent ripples across industries as the fossil fuel-backed US president attempts to deliver on his 'drill, baby, drill' agenda. Perhaps most notably, the US financial sector has taken a severe turn away from climate pledges, with multiple high-profile firms abandoning the Net-Zero Banking Alliance (NZBA), an UN-sponsored initiative set up by Mark Carney, the now prime minister of Canada.

The retail sector is confronting its own reckoning, grappling with the combined pressures of a public with declining disposable income and rising costs across the industry. These pressures have led some retailers to scale back their sustainability initiatives. Last month, Currys announced it was dissolving its board-level environmental, social, and governance (ESG) committee, while in the US, Target revealed that it would miss certain 2025 sustainability targets and ease its commitment to incorporating a higher proportion of post-consumer recycled (PCR) content in its packaging.

Yet a recent RPC study of senior legal and sustainability leaders from across the consumer brands and retail sector found that seven out of 10 decision makers have embedded their ESG strategy in their operations, and a similar number are confident in their firm's ability to stay on top of ESG regulatory developments.

A convergence of climate-related regulations – notably the CMA's new powers under the Digital Markets, Competition and Consumers Act 2024 (DMCCA) to act against misleading environmental claims – that demand quantifiable data rather than estimates, alongside growing consumer expectations of sustainable products and services, has led some of the UK’s top retailers to turn to new data-driven tools and AI technologies to meet their ESG goals across the entire supply chain.

Recent examples include the rollout of invisible UV tags by both Marks & Spencer and Ocado Retail – designed to trace milk carton packaging to recycling facilities. Meanwhile, Reiss has deployed an AI tool which verifies supply chain data to assess whether its products have a lower impact than the average alternative, and Midcounties Co-operative has implemented an AI-powered prompt markdown tool which aims to reduce food waste in stores.

Data-driven route optimisation

B&Q is one organisation on that growing list of British retailers harnessing data in new ways to meet their sustainability targets, with the home improvement giant recently launching an AI-powered transport optimisation platform trial as part of its goal to reach zero emissions by 2040.

The technology, developed by the company’s logistics partner GXO, analyses millions of route variations to identify the most efficient schedules. Early results from the trial indicate estimated savings of 240,000 kilometres and 150 tonnes of CO₂.

“What we found before with traditional routing platforms is that you tend to get a very one-dimensional view of the world,” Darren Hall, director of logistics at B&Q tells Retail Systems.

Instead, the new technology allows the business to understand nuances in the data it collects.

He gives an example of a driver transporting goods on the M25 at seven o’clock in the morning on a 70-mph road.

“With most routing software you’d think that you would actually be travelling at 70-mph but we know that the real average speed is probably about 20-mph at that time,” continues Hall.

Beyond introducing alternative fuels, the organisation has worked extensively on identifying how it can make its fleets more efficient, finding that the easiest way to do so is to simply take miles off the road.

“This is why we’re trialling this tool – it comes with a lot of benefits because the fewer miles we drive, the more cost- and energy-efficient we are,” continues Hall.

AI-powered visibility

B&Q is also using an AI-powered visibility tool that notifies the company of stock levels across multiple locations, how many weeks’ worth of inventory it holds, and where the stock is likely to be used.

“If we can minimise the amount of movement we have to do, then we're not burning fuel, we're not putting miles on the road,” says Hall.

The business is also using its supply chain visibility tool in collaboration with vendors so that they are aware of what its replenishment cycles are, which means the retailer can optimise inventory purchases and minimise reliance on external storage.

Additionally, it has deployed an intelligent tool which looks at where the company sources products for its store-to-home network.

“We have 53 stores where we do home delivery from so the product is closer to customers, therefore you don't have to drive so much and product becomes far more accessible,” he says, adding that the technology allows it to look at where the most efficient place to get product from is, whether that’s a central warehouse or a store.

Shifting staff behaviour

Hall tells Retail Systems that the business is rolling out AI-powered data tools to shift the way its teams behave, for example by exploring the driving style of its drivers.

“We know who our most efficient drivers are and those who brake harshly or accelerate a lot,” he explains. “And we can regrade the drivers based on their driving style and performance; incorporating gamification makes it really interesting for them.”

Drivers have access to a mobile app where they access their grade and compare with their peers.

“We're doing this because it increases our miles per gallon and reduces our footprint whilst making sure that we have safe and consistent colleagues on the road,” he says.

Warehouse layout

The retailer is currently using another AI solution which analyses warehouse layouts. It helps teams with planning across its roughly 4.5 million square foot of warehousing, for example, storing faster moving stock closer to the entrance and slower product further away.

“Our warehouses are vast spaces,” says Hall. “By optimising movement, you can really impact how staff need to move around the warehouse.

“The people, time, and cost benefit of that is clear, as well as reducing the movement of our forklifts and pump trucks that use energy to move around.”

Preventing unnecessary emissions in store

In store, B&Q has worked with Fujitsu to optimise energy usage after struggling with the vast amount of data produced by its building management sensors (BMS) and smart meters.

These systems send new data to the business every 15 to 30 minutes, creating a complex web of information across a varied network of stores of different sizes and locations.

“Since installing these systems five to six years ago, a huge number of sensors have started to fail,” Ben Richardson, energy and sustainability project manager at B&Q tells Retail Systems. “They fail at a set temperature, so it doesn't necessarily look like they have failed.”

To address this, B&Q is using AI analysis of its BMS to search for anomalies and patterns, with the technology suggesting fixes to help save money and prevent unnecessary emissions.

“The amount of data is quite staggering,” explains Richardson. “That data can be incredibly useful to help find and fix problems but if it's not used correctly, it can become part of the problem. Data without a purpose is just wasted.”

He has worked with Fujitsu on the project to make the best use of the data, with the first six months or so focused entirely on training the model to understand how the stores operate and helping it learn what the sensors should be doing.

“Algorithmic AI matches up data points and finds patterns, picking up policy violations, for example, heaters running that shouldn't be, which improves our ability to react quickly to the faults correctly,” he continues. “We're also finding that you can model different scenarios virtually, for instance cold spots in stores.”

When B&Q set off on this journey, the focus was on delivering invisible changes that staff or consumers don’t notice but that save energy that would otherwise be completely wasted.

“It's also useful to explain the impact of things because it's all real-time, which helps with discussions in stores around behavioural changes and how you can do things differently from a re-plan perspective,” he says. “For example, when you arrive to the store in the morning, perhaps you don't need to open the back shutter first thing.”

When it comes to changing in-store behaviour through initiatives such as leaderboards or gamification, Richardson explains that keeping the amount of data produced accurate can also be tricky.

“If you have a leaderboard and you start rewarding the incentive, as soon as there's an error in that data, people can be falsely rewarded and it becomes unfair, the trust is lost and it's very hard to regain,” he says. “That’s one of the pitfalls which we are carefully trying to steer around: how do you mesh the data and make sure you're not bringing in those errors?”

Centralising carbon data with AI

The challenge of managing vast quantities of sustainability data isn't unique to traditional bricks-and-mortar retailers. E-commerce businesses are also turning to AI to manage complex ESG metrics across their supply chains.

Butternut Box, which describes itself as Europe’s largest fresh dog food brand, is using AI-driven reporting and data modelling to form a central repository of scope 3 and ESG data after facing challenges in tracking sustainability metrics.

Up until now, the e-commerce subscription service’s carbon accounting has been located on a multitude of spreadsheets. Although the company has achieved some key sustainability wins, like cutting the carbon intensity of gas usage through innovative heat recovery technology, it knew that with the addition of a new manufacturing facility in Poland and rapid expansion into Europe it needed a more robust and dynamic approach.

“Specifically, using spreadsheets has meant that calculation of our carbon footprint and reporting of other ESG metrics was slow and cumbersome,” says Alisa Heimann, group sustainability manager, Butternut Box. “Data had to be manually uploaded from numerous sources, limiting the frequency of updates and increasing the risk of human error.”

Modelling its carbon impact was also limited to Heimann as group sustainability manager, creating an unnecessary bottleneck when carbon data was needed to support decisions across the business.

Butternut Box has rolled out the carbon management platform Sweep to provide automated data collection, which is removing the burden of dealing with dozens of spreadsheets of data.

“This also eliminates manual, error-prone processes, all of which can hamper progress and keeps sustainability managers like me away from the important part: analysing the data to support business decisions which create value for the company, like integrating lower-emission technologies into our production processes,” continues Heimann. “It is widening access to modelling carbon impact from just sustainability to other teams across the business such as our product development and procurement teams, enabling carbon to be an easy and natural part of recipe development and sourcing decisions from the start.”

As well as this, she explains it provides automated data cleansing to eliminate duplicates, errors and inconsistencies, saving hours of laborious cross-checking on one centralised data structure within the platform itself, which ensures all carbon and ESG data is in one digital space.

The opportunities and risks of AI

Heimann says that the main opportunity that the rollout of AI-driven reporting has provided is time, often one of the most common barriers to ESG progress today.

“If teams have to spend hours manually reviewing sheets of data and simply completing compliance exercises but never have the time to analyse the data for the benefit of the company, then a lot of potential value is missed!” she explains. “When all the ‘boring’ bits are automated, this bottleneck is removed.”

When asked whether advanced technology such as genAI or agentic AI has a place in B&Q’s sustainability and supply chain strategy, Darren Hall says that it gives the company an opportunity to think differently.

“I visited a warehouse recently where they don't produce any reports or dashboards,” he explains. “Employees just ask an AI tool what has happened in the past 24 hours; it will tell them what's happened, where they need to focus their attention, and where they can be more productive.”

Hall adds that the more retailers know about customer behaviour, products and how popular they are, and demographics across different areas, the more they can optimise purchasing and identify where goods are best placed.

“There is no point in sending lawnmowers into the centre of London, it’s a very obvious thing because people haven't got gardens there but there are these sorts of nuances across thousands and thousands of different SKUs that we sell across that we just cannot understand as individuals, whereas data and technology can really help us get a grip on this and make us more efficient,” he continues.

Heimann says that while AI brings huge efficiencies to ESG reporting, it must be applied thoughtfully.

“It wouldn’t be wise to develop an over-reliance on systems that lack transparency, or use large, energy-intensive models that end up undermining our sustainability goals,” she adds.

She explains that a targeted AI approach, where lean, purpose-built machine learning is used, technology is trained on trusted ESG data, and embedded robust security and compliance measures are implemented, is where real value can be added.

“This ensures we get accurate, secure and sustainable insights from our data, without the risks,” she continues.

Hall says that one of the biggest challenges associated with AI from a data or automation point of view is cultural.

“It’s the fear that it’s going to come along and take over people’s jobs – so we’ve had to really work to overcome some of this,” he tells Retail Systems. “It’s important to educate our teams so they know AI is there to support their roles, make their lives easier, and allow them to be far more strategic and future focused.”

Future plans

Looking ahead, Butternut Box is using data-driven technology in other areas as part of its sustainability strategy.

“We have just implemented a new weighing and reporting system across different points of our production line that has given us a more detailed understanding of the drivers behind our food waste figures and has already resulted in further reductions,” says Heimann.

At B&Q, it is exploring a new transport management system which will allow the business to give its customers more delivery slots. Hall says that eventually, after several implementation phases, this system could potentially give customers the option to choose a specific delivery time and let them know which ones are green slots.

“For example, if we’re delivering to your neighbour next Thursday, you could wait until then to have your delivery because that's a greener stop,” says Hall. “Giving that visibility to customers and the choice I think is one of the next evolutions in our transport planning.”

The company is also looking at rolling out heat mapping for its warehouses – a technology that visualises space utilisation patterns to identify underused areas.

“It's going to be really key for us to understand exactly how we operate,” he continues. “Being over spaced is a key driver of financial and energy waste for us.”

In the store, the home improvement retailer is looking at further ways to optimise, including seeking out partnerships to maintain and improve upon its existing efficiency gains.

And because its work with Fujitsu has helped reduce its emissions and costs, it can now reinvest into a programme of electrification at a faster pace. This has involved the rollout of on-site solar generation.

In the near future, it plans to expand on this, connecting all the different elements of its sustainability strategy – from electric heating to electric vehicle charging – to create a “symbiotic partnership”.

While some retailers are retreating from sustainability commitments in the face of economic pressures and shifting political winds, the experiences of B&Q and Butternut Box demonstrate an alternative path forward. By deploying AI and data-driven technologies, these organisations are not only meeting their environmental goals but also unlocking operational efficiencies that strengthen their business fundamentals.

The convergence of stricter regulations – demanding quantifiable data rather than estimates – and growing consumer expectations means that sustainability can no longer be treated as a separate initiative. It must be embedded into core operations, from warehouse layouts to delivery routing to carbon accounting.

Data and AI are becoming the enablers of this integration, providing the visibility and precision required to validate claims, build consumer trust, and differentiate in a saturated market.

With three-quarters of UK retailers still lacking targets on protecting nature, according to recent British Retail Consortium figures, the gap between leaders and laggards is widening. Retailers that consistently evolve with the latest data-driven sustainability tools will not only meet consumer expectations and regulatory responsibilities but also lead the way in building a more resilient, responsible industry that benefits all stakeholders.

In a year marked by sustainability retreats, the UK retail sector has an opportunity to chart a different course – one where technology transforms environmental ambition from aspiration into measurable action.

---