AI in Retail: How Smart Stores Are Selling More

AI is changing the competitive retail landscape in real time. It’s helping stores personalise customer experiences, speed up operations, and make smarter, data-informed decisions.

Retailers are betting big on the future of artificial intelligence (AI), with 75% of retailers saying that AI agents will be essential for a competitive edge by 2026. The innovations happening in AI are transforming how businesses engage with customers, from promotions and product search to checkout and service.

With this in mind, you may be wondering how your business could use AI to create more meaningful retail experiences. In this guide, we’ll explain what AI means for retailers today, covering real-world use cases, the benefits, and how to get started.

Wondering where to invest in AI? Start with the pain points you’re already aware of. From customer experience to operations, AI can guide you to improve what’s not working and find new ways to optimise your business. Here are four common ways retail businesses are using AI.

AI is helping retailers offer a more personalised, seamless shopping journey, from how people find products to how they’re supported long after the sale.

Personalised recommendations: AI uses customer profiles, service queries, and loyalty data to deliver targeted offers, auto-generate product descriptions, and create personalised marketing messages.

Enhanced shopping journeys: With conversational site search and voice recognition, customers can now talk to your website like they would to a store associate. AI makes it easier for shoppers to find what they need (and what they didn’t know they wanted).

AI-powered customer service: AI-powered chatbots and virtual assistants understand natural language, provide instant support, and power self-service options like returns. They also draft responses in your brand voice and flag issues before they affect customers.

Personalised marketing: AI helps marketing teams move faster by providing support for writing personalised emails, creating targeted promotional offers, and segmenting customers based on real-time data.

AI helps retailers run leaner and smarter, making decisions based on data, not guesswork.

Demand forecasting: Using sales history, market trends, and real-time data, AI can predict demand more accurately, helping you order the right inventory to get ahead of what shoppers will want.

Inventory management: By tracking stock levels and customer trends, AI helps avoid both overstock and stockouts, ensuring the right products are always on hand.

Supply chain optimisation: AI can run scenarios to help you understand how changes in pricing, promotions, or logistics might affect demand and revenue. This modelling will help you make more informed choices for the future of your retail business.

Pricing optimisation: From offering on-site dynamic pricing to one-click checkouts and auto-renewals, AI helps you set the right price at the right time to maximise your revenue.

AI is being used by all the major retail brands to simplify their daily operations, saving time and freeing up teams to focus on high-impact work like the customer experience or business growth.

Automated tasks: AI automates repetitive work like generic content, email drafts, and promotional offers, cutting down manual effort and increasing speed to market.

Streamlined processes: AI helps speed up your work by removing extra steps, reducing wait times, and making each stage of the shopping experience simpler for the customer.

Generative AI is giving retailers new tools to engage with customers in real-time, while also powering content creation teams behind the scenes.

Content generation: Marketers use generative AI to quickly create branded emails, product descriptions, and social posts, all aligned with their brand's voice and tone.

Real-time customer engagement: AI monitors customer behaviours and triggers relevant interactions, like a personalised message when someone is about to drop off or an offer to bring a lapsed customer back.

AI is already showing up in retail in unnoticeable, practical ways. Here are four examples of how businesses are using it to improve how they sell and connect with customers.

Classic Australian footwear and clothing brand R.M.Williams uses AI and machine learning to elevate product recommendations – not just online but also when talking to customers directly. This resulted in a 34% increase in revenue and a 20% lift in online conversion rates.

Australian-based Freedom Furniture has embraced AI-driven search and personalisation in its ecommerce marketing to enhance the customer's shopping experience. By implementing an AI-powered search platform, Freedom Furniture offers customers more relevant product recommendations, which led to a 5.5% increase in average order value .

Fisher & Paykel began using Salesforce’s AI to ease the pressure of high service demand and take the load off their team. With AI-powered self-service in place, they’ve cut call times by 50% and expect 65% of routine cases to be handled without requiring a real person.

Global sportswear brand Nike is using AI and augmented reality in its Nike Fit app to improve how people shop for shoes. The app scans each user’s feet to recommend their ideal size, helping take the guesswork out of online shopping. Nike said this has not only improved the customer experience but also helped bring return rates down.

These examples showcase the range of ways AI is being used in retail. Now let’s look at the bigger picture and how it can help you and your business thrive.

Using AI in retail can grow revenue and relationships. By automating data collection, analysis, and delivery, retail artificial intelligence solutions help you act on insights faster and more efficiently, while levelling up both the employee and customer experience. Here’s how.

AI can integrate and automate access to real-time customer data so employees can make informed decisions in the moment. When all departments use the same data, it’s easier to collaborate, and takes less time to act.

Since every team member can see how a shopper interacts across marketing, commerce, and service — within applications and dashboards — they can quickly and seamlessly pick up where the last customer interaction left off, removing friction for both shoppers and employees.

With retail AI, you can create detailed customer profiles that serve as strategic planning tools. They help you understand the customer journey at every touchpoint, so you can reach out to customers with relevant communications, targeted promotions, and efficient service. Using the profile data, AI can help you identify when a shopper’s engagement declines so you can reach out with offers that bring them back into the fold.

Look at your sales pipeline and identify what’s slowing you down. This might be a place that customers begin to drop off, or a big problem you’ve been tackling for years. Note this down and prioritise where you want to test and implement first.

Start by pulling together the data you’ve already collected, which could be from customer purchase history, service logs, email engagement, or data from within your CRM.

Within this data, look for patterns. When do people buy, what do they click, and what do they ask for? This helps you spot what’s working, where people are dropping off, and what your team needs to respond to faster.

Once you’ve chosen what you want to improve, look for a tool that’s built for that job. Whether it’s personalisation, faster service, or better reporting, the right platform should slot into what you’re already using and make things simpler for your team, not more complicated.

Before you invest in an AI tool, check that it integrates with the platforms you already use, like your CRM, ecommerce platform, or service desk. If your tools can’t talk to each other, you’ll spend more time fixing problems than solving them. A connected setup saves time, reduces manual work, and gives you a clearer view of the customer journey.

It can be tempting when you notice everything to fix to do it all at once. Instead, pick a single test so that you can run clear tests and get actionable results. You’ll also want to set benchmarks before you start, so you can track how it’s performing. For example, you might test personalised product recommendations on one product line and track how that impacts your click-through rate over a month.

Before rolling out your new AI, show your team how it works, what it changes, and why it matters. Keep the training simple, make space for questions, and focus on how it helps them do their job better. The more buy-in you have from the start, the better the results will be in the long term.

Retailers are already using AI to make things quicker, more personal, and easier to manage. The most important step is starting with what you know, your existing data, your biggest pain points, and the tools that already work for your team. From there, it’s about testing what works and building on it.

Salesforce Retail Cloud can help you bring together your data, customer touchpoints, and tools to create a better experience for both shoppers and teams. Learn more about what it can do for your business here.