To date, most retailers who adopted artificial intelligence (AI) have done so purely to boost profits. However, now we are seeing a whole new driver for uptake, as there’s a growing realisation that it can be used to help retailers become more sustainable as well. The good news is that these two drivers are not as separate as they might first appear: AI can make decisions that achieve sustainability and profits at the same time.
Initiatives designed to drive profit and sustainability have always been linked. In fact, PwC research revealed that using AI to make decisions about environment-related areas, such as agriculture, water, energy and transport could add more than $5 trillion to the global economy over the next decade. This is a relatively new concept, so hasn’t quite hit home for many businesses, with many incorrectly thinking they need to choose either profitability or sustainability.
Use cases for AI and automation in transport and logistics
There’s a particularly good opportunity for AI to drive positive change on both fronts within the retail sector. By measuring the probability of need, demand and consumption, AI can help reduce waste by preventing products from expiring and avoiding holding onto products that become redundant due to seasonal trends. Doing this also reduces the likelihood retailers will purchase stock that goes to waste, and limit the number of journeys involved in moving and storing items – all of which would pose a direct cost to the business, and the environment.
Having spent years building the necessary experience to do their jobs, it’s not surprising to see retail leaders believing they can do a better job at reading the data than a machine. The growing urgency with which we need to become more sustainable is changing all of that, however: this has only become a key C-suite topic in recent years, thereby making the ‘experience’ debate redundant.
This new purpose for AI and machine learning (ML) simply cannot be ignored. They provide a tangible way for retailers to start reducing their carbon footprint and impact on the environment, so those retailers who may have previously ignored the profitability promise of AI now have another driver to change.
A ‘Buy one, get one free’ deal?
It doesn’t need to start with sustainability, for greener behaviour can also come naturally as a result of using AI to make better business decisions. One of the most obvious examples of this would be ordering the perfect amount of each item, and reducing waste as a result. With items that have a short shelf-life, this both reduces the risk of stock running out (damaging customer experience) and also lowers the amount of items that need to be thrown away (bringing negative impact to environment, and the bottom line). Here, retailers are simultaneously saving money and reducing carbon footprints, as well as getting on the front foot more and making money. They don’t have to mark down items to sell them; customers find the items they need are on the shelves, and profits should go up in line with sustainability.
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Make your move, and deliver long-term
Within some organisations, it can be hard to get formal buy-in for initiatives that drive sustainability because they tend to pay off in the future, rather that straight away. This being said, you could argue it would be much more damaging for a business to be seen as ‘dragging its feet’ on green issues, than starting its journey to sustainability and potentially not quite getting it right first time.
All members of the C-suite should understand the importance of sustainability to the organisation, so getting them around a table to discuss this will be a great step in the right direction. With everybody on board, they can get to work, but they must be careful not to fall at the last hurdle – having stated a case that AI can drive sustainability and profits at the same time, they must make certain they can actually deliver on this promise. This means they must ensure they only use algorithms that are flexible, so they are able to meet the range of financial and sustainability targets that the organisation has set out. By ensuring this fluidity is built in, they can be confident in feeling the benefit over the longer term, regardless of how many times the goalposts shift in the future.