Artificial intelligence in retail: 6 use cases and examples
Six use cases for AI in retail, including optimizing inventory management, improving forecasting, and personalization.
U.S. inflation rates may be cooling off some (especially compared to their 2022 spike), but many consumers are still feeling the effects of higher prices, making them extremely budget-conscious. They’re still spending, but more strategically—splurging on select purchases, while tightening their wallets elsewhere. This is a key challenge brands face as the top retail trends 2025 take shape.
This heightened caution and consumer skepticism will make it tough for retailers looking to win wallet share (while simultaneously managing the lingering effects of inflation themselves). To overcome the odds, they need to build trust and deliver standout shopping experiences—or risk joining the list of failed retail businesses.
In 2025, cooling inflation will help global retail sales volumes grow 2.2%, the fastest rate since 2021, according to an Economist Intelligence report.
But with consumer confidence remaining weak, retailers will need to execute on all fronts by integrating new technologies, adapting to new consumer preferences, and improving operational efficiency.
The days of one-size-fits-all retail are long gone. But here’s the thing: so is one-size-fits-all personalization. To actually engage customers, personalization needs to go beyond basic messaging and instead dive into deeply individualized experiences.
AI can improve personalization—at scale. AI has evolved from trendy tech into a powerful tool that retailers can use to understand and anticipate individual customer needs, preferences, and buying behaviors. They can move past chatbots and static product recommendations to AI that dynamically adapts to consumer behavior in real time.
For example, AI can analyze browsing habits, purchase history, and even real-time interactions on a retailer’s site to create a more immersive and relevant shopping experience. This level of personalization boosts customer satisfaction and drives loyalty, as shoppers increasingly gravitate toward brands that “get” them.
By embracing AI’s potential to deliver hyper-relevant product suggestions, curated content, and personalized offers, retailers can engage customers in a way that feels meaningful and unique to them.
In 2025, retailers leading the pack will be those who use AI not just as a tool, but as an integral partner in the customer experience.
As retailers use AI to deliver more personalized experiences, customers are becoming vigilant about how their personal information is used. Consumer trust has become a valuable, yet fragile currency.
This is a wake-up call for retailers: Building and maintaining consumer trust will be essential to using AI effectively in 2025.
Retailers must prioritize data privacy and invest in security to protect consumer information. This isn’t just about compliance with regulations like GDPR or CCPA; it’s about demonstrating a commitment to ethical data usage and transparency. Customers are more likely to engage with brands that are upfront about how their data is collected, used, and safeguarded.
Additionally, offering customers control over their data, such as the ability to manage their privacy settings or opt-out options, can help reinforce trust.
In 2025, data privacy and security are strategic differentiators. Retailers that proactively address privacy concerns and provide transparency will strengthen their relationship with customers, positioning themselves as trustworthy brands in an increasingly digital and data-driven environment.
Sustainability is a key trend for retailers aiming to align with consumer values and regulatory standards. In 2025, retailers will double down on sustainability by implementing advanced technologies to make their operations greener and more efficient.
To meet these demands, retailers are exploring ways to reduce waste, cut emissions, and create more sustainable supply chains. AI and automation play key roles here.
By using AI-driven forecasting, retailers can optimize inventory management to avoid overproduction and minimize waste. For instance, predictive analytics can help them accurately gauge demand, ensuring that shelves are stocked with what consumers want without creating unnecessary surplus. Some solutions even enable brands to track their carbon emissions across the supply chain, helping them monitor and reduce their environmental impact.
Beyond inventory, sustainability technologies are reshaping other aspects of the retail industry, including transparent sourcing that lets consumers trace products back to their origins, and energy-efficient operations.
As regulatory pressures mount, the need for sustainable operations will only grow. Retailers that invest in these technologies gain favor with consumers—and future-proof their businesses as environmental requirements increase.
Six use cases for AI in retail, including optimizing inventory management, improving forecasting, and personalization.
The lines between online and in-store shopping continue to fade as omnichannel integration becomes a top trend. Today’s consumers expect a seamless, unified experience across every touchpoint, whether they’re browsing on social media, shopping on a website, or picking up an order in-store.
For retailers, it’s not just about offering multiple shopping options; it’s about creating a cohesive journey that allows customers to move effortlessly between platforms.
Consumers are likely to abandon retailers that fail to deliver these seamless experiences. Features like buy-online-pick-up-in-store (BOPIS), inventory visibility across channels, and flexible returns have become table stakes in retail.
Technology that provides a 360-degree view of their inventory and customer data across channels can help retailers reach their omnichannel goals. AI tools and unified data platforms keep tabs on real-time demand, ensuring that stock levels are accurate and accessible regardless of where customers engage.
For example, some brands are exploring “phygital” (physical-digital) experiences that allow consumers to interact with products in-store in ways traditionally reserved for online shopping, such as AR-powered virtual try-ons.
As omnichannel expectations continue to rise, retailers providing a fluid, interconnected experience across channels will be far more likely to retain customers and drive sales.
Social media and e-commerce have converged, creating social commerce—a trend that’s fundamentally changing how consumers shop. In 2025, social commerce is expected to gain momentum, with platforms like Instagram, TikTok, and Facebook turning into powerful shopping destinations.
Social commerce lets brands meet customers where they are, providing shoppable content and direct purchase options that streamline the shopping journey. It’s especially popular in markets like China, where social commerce platforms such as WeChat and Taobao Live are leading the way, blending social engagement, live streaming and e-commerce to create a $3.565 trillion market.
Launched just a year ago, the TikTok Shop is now a major player when it comes to e-commerce revenue, with the social media giant hauling in more sales than competitors Shein and Temu in the days leading up to Cyber Monday.
This means that retailers need to rethink content strategy. Instead of traditional product listings, brands are creating interactive, visually compelling content that encourages sharing, commenting, and—most importantly—purchasing. Live shopping events, influencer partnerships, and user-generated content are just a few ways retailers can capture attention and drive sales.
By creating a sense of community and fostering real-time interactions, social commerce allows brands to engage consumers in a more authentic and impactful way than traditional e-commerce channels. As these platforms continue to innovate with new shopping features, they will be a crucial channel for retailers in 2025.
Social commerce is anticipated to surpass $1 trillion. A winning social commerce strategy positions your brand for growth.
As retailers push forward with AI, data quality has become a priority. Accurate data is essential for everything from personalized marketing to inventory forecasting, and it’s the backbone of effective AI applications. Yet, data quality remains a challenge for many retailers.
In 2025 clean, integrated data systems will serve as a launchpad for innovation—while bad data will be a liability.
The costs of bad data are high. For retailers, it can lead to missed sales opportunities, stock mismanagement, and failed marketing. AI relies on large volumes of accurate, timely data to generate valuable insights; without this foundation, even the most advanced AI solutions will struggle to deliver meaningful results.
For example, inaccurate inventory data can lead to overstocking or stockouts, which in turn affect customer satisfaction and profitability. A lack of reliable data can prevent retailers from getting the most of out AI to improve operations and customer experiences.
Clearly, retailers must focus on improving their data infrastructure. This means prioritizing data cleansing, integration, and management to ensure that information flows smoothly across systems and is accessible in real time.
Adopting unified platforms that consolidate data from various channels can help create a “single source of truth,” enabling more accurate demand forecasting, better customer insights, and smarter decision-making.
Despite the obstacles, retailers have a lot of growth opportunities ahead. Five years after the pandemic shuttered physical stores and drove e-commerce to record levels, the retail industry remains strong.
From AI-driven personalization to omnichannel integration, the trends defining retail in 2025 underscore the importance of adaptability, innovation, and customer centricity. Whether it’s by harnessing AI, prioritizing sustainability, or meeting consumers on social media, the retailers who stay agile will be the best positioned to thrive.