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What is AI in retail?

AI in retail is the use of artificial intelligence to improve retail industry operations, enhance customer experience, and optimise merchandising, demand forecasting, and supply chain management.

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How AI is changing the retail industry

AI is already influencing most retail experiences—creating seamless shopping experiences that customers love. When a shopper visits an online shop, AI ensures they're greeted with personalised offers based on their past purchases. If they’re interested in a product, AI can even provide helpful updates, such as notifying them when stock is low. In grocery shops, AI plays a vital role in keeping shelves stocked with a wide range of products, ensuring the thousands of different products are fresh and available for customers' needs.

To stay competitive, retailers must take both customer experience and operational efficiency to a new level—and, increasingly, they’re looking to AI tools to help them get there. In fact, it’s anticipated that the use of artificial intelligence in retail will grow from US $11.83 billion to $54.92 billion by 2033.

AI technologies such as machine learningmachine learning and natural language processingnatural language processing are behind innovative shopping features that engage and delight customers—and entice them to come back for more. AI technologies such as and are behind innovative shopping features that engage and delight customers—and entice them to return for more. Meanwhile, advanced demand forecasting and predictive analytics tools allow retail businesses to revolutionise their use of data to fuel informed decision-making. Real-time insights help them streamline operations, reduce costs, and keep pace with volatile markets by building responsive and resilient supply chains.

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What are the use cases of AI in retail?

The use of AI in retail commerce is revolutionising both online and brick-and-mortar retail spaces, creating a more efficient and personalised customer experience while boosting profits for retailers. The primary use cases are:

Personalised recommendations

By analysing your purchasing history data using AI, retailers can provide tailored recommendations and cross-selling offers that are relevant to customers—making it more likely they’ll want to make a purchase. When visiting an e-commerce site, they may be greeted with personalised product suggestions or receive an e-mail with a promotional offer for a product they’ve previously bought.

24x7 customer service

AI for customer service is a game changer, helping retailers deliver smoother, more efficient assistance to customers whilst reducing service costs. Virtual assistants using generative AI technology allow customers to “talk” to a chatbot that can manage enquiries, provide product information, and even assist with placing orders. And with chatbots working 24/7, customers can get the answers they need—whatever time they shop.

Inventory management

Using predictive analytics, retailers carry out highly detailed demand forecasting based on historical sales data and trends. More accurate forecasts allow retailers to optimise inventory levels, cutting costs by carrying less stock while minimising the risk of empty shelves. Where stock is running low, retailers such as Harrods Limited and COOP Group use AI-based inventory replenishment solutions to automatically reorder stock. According to SAP Value Lifecycle Manager, improved product availability can result in up to 30% less revenue loss due to stockouts, while retailers can slash inventory costs by up to 25% by avoiding overstocking.

Pricing optimisation

Dynamic pricing enabled by AI helps retailers adjust prices in real time to manage promotions and maximise profitability. Prices may change based on demand, stock levels, or what competitors are charging. They may also vary depending on the time of year or previous buying behaviour. For example, if a customer makes purchases on a regular basis, they may get better deals—encouraging repeat purchases and increasing brand loyalty.

Delivery logistics

AI-based route planning helps retailers reduce transportation costs and improve delivery times. By optimising routes, retailers get products to customers faster and cut fuel consumption. Intelligent route planning solutions also help logistics teams adapt to changing traffic conditions to ensure that deliveries arrive on time.

Fraud detection

AI plays an increasingly important role in retail security. Retailers use advanced analytics to monitor transactions for unusual activity, helping to detect and prevent fraud. AI-enabled biometrics provide secure customer authentication to reduce the risk of unauthorised transactions. And in-store, AI-based surveillance systems highlight suspicious behaviour, preventing losses from theft.

How does AI benefit retail businesses?

AI in the retail industry offers a wide range of benefits for businesses, enabling them to run operations more efficiently and grow profits while engaging more closely with customers and building brand loyalty. Here are some compelling reasons why retailers need AI:

Improved customer experience

Tailored product recommendations, individualised marketing messages, and customised offers developed using AI-based analysis of previous buying behaviour and preferences provide customers with highly personalised shopping experiences. This improves the overall customer experience, encouraging higher average spend and increasing customer lifetime value, satisfaction, and loyalty.

Better decision-making

AI helps retailers analyse vast amounts of data across sales, marketing, and operations to deliver strategic decision-making information in real time. Whether choosing which merchandise to sell at a particular shop or which logistics supplier to use for an urgent delivery, AI-based insights help retail employees make the right decisions to achieve the best business outcomes.

Improved operational efficiency

By forecasting demand more accurately, optimising delivery routes, and predicting potential disruptions, AI helps retailers run more efficient and resilient supply chain operations. This means that they can get the right products to customers at the right time, reducing the risk of lost sales and increasing sales revenue.

Lower costs, increased profits

More efficient operations deliver cost efficiencies that have a significant impact on a retailer’s bottom line. Automated supply chain processes bring significant cost savings, while AI-based inventory management reduces holding costs for excess stock. Meanwhile, dynamic pricing allows adjustment of prices in real time to more accurately reflect fluctuating production costs, allowing retailers to maintain and grow profits.

Enhanced productivity

With AI automating routine and repetitive tasks such as data entry or order processing, staff become more productive. Having more time to focus on higher-value activities such as resolving complex customer enquiries makes work more fulfilling for customer service agents.

Accelerated innovation

Using AI in retail commerce helps businesses innovate faster to stand out from the competition, launching new business models and offering new services such as personalised shopping assistants or smart search functionalities. And with deeper insights into customer behaviour and preferences, retailers quickly adapt to new market trends to gain a competitive edge and win more business.

Sustainable business

Sustainability is a crucial consideration for many customers when making purchasing decisions. AI helps retailers achieve sustainability goals by calculating and tracking sustainability data such as carbon emissions. Retail companies then introduce more sustainable business practices, optimising supply chains to minimise environmental impacts.

Best practices for using AI in retail

While AI delivers numerous benefits, retailers also face challenges in successfully integrating AI into their operations. Consider these best practices for effective adoption and mitigating potential risks:

Define clear objectives

Before jumping headfirst into an AI implementation, it’s important to identify specific retail business areas where AI can make a difference—such as improving the customer experience, reducing stock levels, or targeting advertising more precisely. It’s a good idea to scale up gradually, beginning with pilot projects to validate the effectiveness of AI solutions and using the results to refine the implementation approach.

Ensure data quality and accessibility

To get maximum value from AI technology, retailers should establish a unified data infrastructure to eliminate data silos and improve accessibility, whilst investing in data cleansing to help ensure data quality. It’s also crucial to choose a data management system that can scale when needed to handle peak loads and seasonal variations.

Meet privacy and compliance requirements

Retailers using AI must respect the privacy of individuals’ personal data by complying with a plethora of regulatory requirements, such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). A robust data security strategy is also required to safeguard customer information.

Manage change

The switch to AI-based processes can feel like a big jump. For this reason, it’s important to engage with retail employees early on to communicate the benefits of AI initiatives and provide training to help them adapt. Encouraging employees across different departments to come up with new use cases for the technology fosters a culture of innovation where employees embrace AI in retail operations.

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The future of AI in retail

With the potential to transform nearly every aspect of the industry, the future of AI in retail looks promising. Key developments expected in the next few years include:

Hyper-personalisation

Retailers are set to provide even more individualised customer experiences by using AI to analyse data from a wide range of sources, including social media, browsing history, and purchase patterns. Going several steps further than traditional personalisation to refine segmentation and targeting, hyper-personalisation analyses a wide range of criteria such as customer behaviour, preferences, historical interactions, and real-time contextual clues.

Cashierless shops

Imagine walking into a shop, picking up what you need and walking out again without having to queue to check out and pay. Aiming to simplify and enhance the shopping experience, cashier-less shops allow customers to make purchases without the need for a traditional checkout experience involving human cashiers. A concept that’s becoming more widespread in the retail industry, it’s seen in shops that use AI-enabled sensors, cameras, and computer vision to track the items customers pick up and automatically charge them when they leave.

Smart shelves

Increasingly found in retail outlets such as grocery shops or supermarkets, smart shelves combine AI with sensors, radio-frequency identification, and Internet of Things–based technology. Providing retailers with real-time analytics on demand and stock levels so they can replenish products more efficiently, smart shelves streamline store operations, improve inventory management, and enhance the customer experience by eliminating stock shortages.

Augmented reality (AR)

AR offers the potential to deliver immersive and engaging shopping experiences without customers having to leave their homes. Examples include virtual try-ons that help people understand what an outfit will look like on their body type or 3D visualisations that show how items of furniture will look and fit in their homes.

Robotics

The use of AI-based robotics in retail is a growing phenomenon, helping businesses streamline operations and improve customer service. In store, robots might clean floors or restock shelves, while robotic kiosks help customers find specific products or check stock availability. At warehouses and distribution centres, retailers achieve game-changing efficiencies by using robots to pick, pack, and sort items for shipping or monitor inventory levels.

How can you benefit from AI in retail?

AI in retail is set to bring about significant change that is already enhancing customer experiences, improving operational efficiencies, and driving sustainable business practices.

By successfully integrating AI into your retail operations, you’re better positioned to meet the changing demands of customers and win more business in increasingly competitive markets.

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