Why AI in Retail?

Artificial intelligence is reinventing the retail landscape. For example:

• Computer vision is helping retailers gain near-real-time insights about shopping behaviors and inventory, enables such functions as frictionless checkout and can help boost loss prevention efforts for brick-and-mortar stores with increased monitoring and alerting.
• Machine learning is helping to streamline inventory management practices.
• Conversational AI is being used to augment customer service, provide personalized shopping assistance, and accelerate drive-through ordering at fast food restaurants.

Retailers that harness AI to connect with customers and operate more efficiently will be better positioned to thrive in today’s AI-powered world.

Benefits of AI in Retail

Retailers are facing increased pressures and dramatic changes to the industry due to postpandemic impacts. Supply chain distortion, shifts in what and how customers buy, and ongoing labor shortages have exposed the limits of status quo capabilities and areas where retailers are behind the curve. AI-enabled digital initiatives are helping retailers adapt to the new realities of today’s customers and business needs.

AI in retail is helping to augment employee capabilities in several ways:

• Driving sales: AI-enabled tools can help increase sales and customer conversion rates by optimizing and personalizing the buying journey.
• Increasing visibility: Retailers need to know the status of merchandise—location, availability, and inventory—as well as store traffic patterns and activity, customer habits and preferences, and where employees can focus on higher-value-added activities. AI-powered tools that enable data capture are the foundation of a broader, more accurate view of the retail operation, providing visibility into the supply chain, inventory, and on-site retail locations.
• Operational and supply chain efficiency: From supporting customers through their buying experience to monitoring, automating, and optimizing the intelligent supply chain, retailers can use AI to maximize operational efficiencies in inventory transit, warehouse storage and distribution, and retail sites.
• Understanding the customer: AI-enabled tools can help build customer segment profiles to facilitate increasingly granular insights into customer experiences, including individual habits, needs, and preferences. These insights can help inform marketing initiatives, promotions, loyalty-based incentives, and campaign road maps.
• Enhancing customer experience: Retailers want strategies to make their connection with consumers “frictionless,” meaning more paths available for purchase, greater functionality, and expanded communications for interactive engagement and relationship building. Customers want omnichannel search and purchase flexibility to accelerate interactions and personalized attention. AI in retail can assist customers with brand engagement, customer service inquiries, and problem resolution, ultimately fostering customer loyalty.
• Counteracting complex structure: Given the nature of retail—with multiple brands, blended franchise and corporate structures, frequent acquisitions, numerous distributed sites, and a blend of online and brick-and-mortar operations—there can be significant organizational and operational complexity. Intelligent AI-based tools can help unite, streamline, and simplify processes for integrated management capabilities.

Challenges with AI in Retail

While AI in retail holds unparalleled promise, it can also bring challenges to be addressed:

• Responsible AI: Foundational to all AI in retail strategies is a commitment to using responsible AI for transparency, accountability, inclusivity, and governance. Taking the extra step to apply responsible AI earns brand trust, employee confidence, and customer loyalty over time.
• Potential customer tolerance limits: Retailers need to be sensitive to their customers’ perceptions about digital tracking strategies for marketing and in-store operations. It is important to consider alignment with their brand promises and reputation when considering new AI in retail ideas.
• Data privacy: Adding a new digital tool, device, or partner means at least some degree of sharing customer data and opening new sources of potential breaches. Security must be a top concern when choosing a solution or partner or implementing new technologies.
• Organizational investment: Upgrading and adding new technology can be a significant initiative, as all systems need to integrate seamlessly for optimal results. Staff training is also key to success. Working with a technology partner to align your business needs and existing infrastructure with right-fit, AI-based solutions can help you plan your investment road map to limit disruption and drive greater return.

AI in Retail Use Cases

Increasingly, retail businesses are considering how AI technologies, such as computer vision, deep learning, or generative AI, can help them anticipate and respond to customer needs better as well as differentiate their brand in crowded and competitive spaces.

Create Frictionless Shopping and Checkout

Retailers, from small boutiques to multinational superstores, strive to offer convenient and personalized shopping experiences. However, with the rise of tech-savvy consumers, mere convenience is no longer sufficient.

Today’s customers now expect frictionless shopping and checkout experiences. Intelligent AI technologies and software solutions can help to streamline most interactions with the retailer. For example, human cashier‒free checkout, smart self-checkout systems, and integrated video analytics that identify products when a barcode is missing or unreadable can help to eliminate the need for employee assistance.

By automating most transactional interactions and routine tasks in a retail environment—like price checks, customer service, and self-guided directions—customers gain a more convenient, streamlined experience, and employees are more available to help customers at critical points in the shopping journey.

Provide Memorable, Personalized Customer Experiences

In addition to seeking out frictionless shopping, customers desire experiences tailored to their preferences. For retailers, AI-enabled technologies can help personalize customer engagements:

• Digital signage embedded with computer vision can serve up just-in-time advertising for a particular audience.
• Endless aisle kiosks let customers see more products available at other locations to support omnichannel retail strategies. They also enable cross-selling and upselling opportunities.
• Digital and touchless kiosks recognize speech and gestures, allowing for hyperconvenient checkout options, self-service wayfinding, or in-store product research.
• AI can collect and analyze data about customer shopping habits and preferences to help inform product promotions.
• AI-enabled POS systems can capture data about customer purchases to generate new product recommendations, support a loyalty club, or deliver upsell offers during checkout.

Personalization likewise benefits retailers, as capturing and analyzing all this data leads to more-accurate segmentation and experiences that are tailored to individual customer’s patterns and preferences. All help to build brand loyalty, improve customer retention, and grow bottom-line revenue.

Improve Demand Forecasting and Merchandising

The more retailers understand customer behaviors and trends, the better they can meet demand and present the best products at the right time. AI in retail can help improve demand forecasting, inform pricing decisions, optimize product ordering and placement, and track data from online channels to inform e-commerce and digital promotion strategies.

AI in retail can also help recognize customer intent and optimize the buying journey accordingly. For example, heat mapping in retail locations uses computer vision to show which products attract attention, are picked up, are returned, and where the customer goes after leaving the shelf. Retailers can use this intelligence, especially when combined with transaction data, to create experiences that promote higher visibility of and engagement with products and plan store traffic patterns for effective visual placement.

Boost Loss Prevention Efforts

Product loss and theft—also known as retail shrink—is a rapidly growing challenge for today’s retailers. In 2022, retail shrink cost United States‒based retailers nearly US$112.1 billion in losses.¹ By integrating AI, retailers can leverage object detection, motion analytics at the self-checkout station, and digital sensors to support loss prevention. When used with computer vision, these checkout systems can help mitigate product loss in near-real time.

Improve and Automate Inventory Management

Maintaining an accurate inventory is a major challenge for retailers. By connecting more parts of their operations and applying AI, retailers can gain a comprehensive view of stores, shoppers, products, and their supply chain to help with inventory management.

Responsive retail AI technologies make it possible to collect and process information from vast, diverse sources for better near-real-time inventory visibility, accurate product availability, and time-to-delivery information. This facilitates shifting inventory to the best channels/outlets to maximize sales.

For example, smart shelves can quickly identify low- or out-of-stock items, pricing errors, and what customers select for purchase. Inventory robots can alert staff to misplaced items for current inventories and automatically fill orders from the warehouse. As a result, retailers can run stores more efficiently and free up associates’ time to focus on improving the shopping experience.

AI-enabled warehouse automation yields new efficiencies through warehouse control systems. For example, using tags and sensors for product and logistics data and edge AI to collect and process data in near-real time enables faster shipping decisions with less error. Retrospective analytics can ensure product consistency and identify areas for process improvements. Connected fleet logistics technologies ensure visibility from the distribution center to retail site delivery.

The Future of AI in Retail

The nature of retail is to bring customers the latest products they want with fresh omnichannel buying experiences, both physical and online. Opportunities for new and innovative ways to deliver on this will continue to expand as data capture and insights from AI grow.

GenAI will continue to help reduce employee busywork and routine tasks, freeing staff to focus on higher-value-add responsibilities like relationship building and customer problem-solving.

AI technologies will continue to provide greater visibility into supply chain logistics, building in resilience for adapting to circumstances like vehicle maintenance, traffic challenges, and shifting inventory needs from store to store.

Altogether, AI in retail will become more embedded, delivering highly personalized, interactive experiences and recommendations to customers. This will create a world of new possibilities and opportunities for businesses to authentically connect with their customers, turn their data into powerful new insights, and take operations to the next level.