How is AI shaping the retail sector?
Retail firms are continuously searching for cutting-edge tactics to set themselves apart and experience rapid growth in today's brutally competitive retail landscape. One such strategy that has emerged as a powerful tool for retail brands is artificial intelligence (AI). With the advent of AI, more and more retailers are adapting different AI softwares to enhance their business. Stuart Higgins, partner at BearingPoint tells us about how AI helps reshape and impacts businesses. He also explains the organisational and financial benefits of AI.
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Can you tell me about yourself and your experience in the retail industry?
I am a partner with BearingPoint, a leading Management and Technology Consultancy, and I have responsibility for the Consumer Goods and Retail sector in the UK. Prior to joining BearingPoint, I had a long career working in both Consumer Packaged Goods businesses and Retail businesses for Companies including H.J. Heinz, Boots the Chemist, Halfords and Thresher Group.
How do you think the use of AI is reshaping the retail industry and to what extent?
In recent years, the retail landscape in the United Kingdom has been transformed by the advent of generative artificial intelligence (AI) technologies. Generative AI, a subset of artificial intelligence, focuses on creating and generating new content, such as images, text, and even entire product designs. Its ability to learn patterns and generate original content has revolutionised the way retailers operate, enhancing customer experiences, optimising supply chains, and streamlining business processes.
What are the organisational and financial benefits of AI technology for retail businesses?
The impacts of AI within retail are its ability to complete existing retail tasks faster, more effectively and to a lower level of detail than is practical with a human workforce. So the financial and organisational impacts of the technology will be far reaching. The financial benefits will tend to group into three broad areas – reduction in people and associated employment costs, increased productivity from remaining employees, and finally, increased sales through the use of AI to improve business efficiency. For example, in forecasting and replenishment, re-design customer journeys to attract more customers and encourage them to spend more, and in the design of innovative new products.
How does the use of AI impact retail business?
All aspects of retail can and will be impacted by AI. When we look at how AI can be incorporated in logistics, Co-op and Tesco have both partnered with Starship Technologies to conduct trials of autonomous delivery robots. These small delivery robots use AI and computer vision to navigate sidewalks and deliver grocery orders to customers’ homes. Similarly, DHL has been piloting autonomous forklift trucks in some of its operations in the UK. These driverless forklift trucks utilise AI and computer vision technology to navigate warehouse environments, pick up pallets, and transport them to the designated locations under the control of the warehouse management system. The AI algorithms help the trucks adapt to dynamic environments and optimise their movements for efficient material handling.
In Store, Currys has used AI by trialling robots in some of its UK stores to help customers navigate their extensive product ranges. The new ‘Kettybot’ has been launched at four stores across the UK and will use unique AI technology to function. During the trial, KettyBot will be ready and waiting to greet customers at the door, allowing them to use the large touchscreen to select the product area they would like to visit.
Contact Centre Chatbots are another type of AI which are designed to provide a realistic conversational experience for humans. Chatbots have the ability to process human language (written or spoken) and can then provide responses of varying complexity based upon a series of pre-determined, ‘scripted’, problem pathways. However, their current uses are strictly limited by the scripted nature of their programming and so are limited in their current deployment to answer simple questions like “when will my order be delivered”, with more complex questions still requiring human intervention..
Additionally, store assortment planning is becoming one of the focus areas of generative AI in UK retail. Historically, retailers have had to cluster stores into ‘like’ groups of stores in order to plan which products they want to sell in which locations. This is a complicated, manual task and one that, by necessity, tends to lead to sub-optimisation of the end result.
AI brings with it the capability to both ‘educate’ the algorithms using many more databases of information, such as individual store footprints, weather patterns, local demographics, competitor mix, online sales presence, local events, etc… and at the same time to have the computing power to do this at an individual store level – providing much lower levels of granularity and tailoring the assortment to the needs of an individual store. Examples of retailers pioneering this capability in the UK include Tesco, M&S, Sainsbury and Boots.
Lastly, the use of AI in HR. I was recently talking to the MD of a recruitment business who has been experimenting with the use of AI in crafting job interviews. His challenge to me was to ask ChatGPT to design a series of interview questions to put to candidates for a technology related role I was recruiting for and it came up with a really credible interview design. Other central functions, like finance, will also be significantly impacted by AI as a result of automating routine tasks such as invoice matching and payment.
How would AI improve inventory or supply chain management for small businesses?
Generative AI has already proven to be a game-changer for supply chain management in some retailers within the UK retail sector. By analysing historical sales data, market trends, and external factors such as weather patterns and social media sentiment, AI algorithms can generate accurate demand forecasts. These forecasts allow retailers to optimise their inventory levels, minimise stockouts, and reduce overstocking. Additionally, generative AI can optimise supply chain route planning, streamline logistics, and even identify potential bottlenecks or inefficiencies in the distribution process. As a result, retailers can significantly improve operational efficiency, reduce costs, and enhance customer satisfaction by ensuring products are readily available when and where they are needed.
Morrisons wanted to increase on-shelf availability through improved demand planning and replenishment, based on analysis of customer behaviour at every store, along with automating the store ordering process. Traditional store replenishment based on manual ordering by in-store teams was time consuming, not always accurate and created availability inconsistencies between stores. By working with Blue Yonder, Morrisons have implemented an AI based forecasting and replenishment tool to automate store replenishment across c. 30,000 skus and have driven a c. 2.5% sales increase as a result of improved on-shelf availability and customer service.
It is easy to see how the advent of publicly available, low cost, AI solutions will eventually be able to help even the smallest businesses to reduce costs and improve efficiency by using AI based demand forecasting and replenishment to optimise their supply chains.”
Will the use of AI in the retail industry impact jobs?
The impact of technology on jobs is a complex and nuanced topic. Technology can both reduce and increase jobs, depending on the type of technology, industry dynamics, and workforce adoption. Technological advancements, particularly automation and artificial intelligence, have the potential to replace certain jobs that involve routine, repetitive tasks and AI technologies will move the job threat deeper into businesses. On the other hand, technology has the potential to create new jobs and industries. Technological advancements often give rise to new opportunities, requiring new skills and expertise. For example, the growth of the digital economy has led to the emergence of jobs in areas such as data analysis, software development, digital marketing, and cybersecurity.
Historically, technological advancements have resulted in a net increase in jobs over the long term. While certain jobs may be replaced, new industries and opportunities tend to emerge, leading to the creation of different types of jobs. However, the pace and nature of technological advancements could leave some sectors at risk of immediate job loss before complementary roles emerge elsewhere, and retail could be one of those sectors.
In the short to medium term, the job roles in retail most likely to be adversely impacted by AI include cashiers, inventory managers, warehouse Workers, customer service representatives and traditional data analysts
What level of automation do you anticipate the retail sector to reach over the next five years?
There is an overarching question about the adoption of AI in retail and that is ‘will businesses allow its adoption?’. Every company has its own core values, which it tries to stay true to, but sometimes, when looking for revolutionary change, you have to ask whether the existing people within the business are capable of accepting that change or whether every function is, in effect, set up not to allow change to happen because they are worried about violating a policy or taking a risk.
Ultimately, the adoption of AI in retail won’t just be about the capability of AI to revolutionise retail, it will be whether people resist its adoption and whether, by the time they recognise it as being inevitable, the competition has moved on and stolen the market.
Perversely, this could mean many retailers ‘outsourcing’ their AI adoption to third parties to avoid the inertia of managing change within their existing operations.