Conversational AI in Retail: Benefits & Examples

The retail sector is no stranger to digital transformation. E-commerce has permanently changed the retail landscape, presenting a new range of opportunities and risks. Above all, however, is the impact of digital evolution on customer behavior.

Related Content: 

1. AI Agents: Transforming eCommerce & Retail Customer Service
2. Conversational AI in E-Commerce: Benefits & Examples
3. eBook: AI Agents for eCommerce & Retail

Today’s customers have more options than ever before when it comes to choosing how and when they shop. In an era where ordering items online is easier than buying from a local store, retailers must cater to steep customer expectations to create valued shopping interactions or risk being left behind. 

An EY report analyzing the future of retail found three core customer demands that you need to address if you want to remain competitive and continue to win sales. 

1. Invisibility: Customers want seamless buying experiences where retailers fit into their lives with as little friction as possible. For subscriptions and repeat orders, customers are willing to allow AI/automation to take control so they have even less to do themselves. 
2. Indispensability: Customers want to buy from retailers who can improve their lives by optimizing their shopping experience and bundling products, services, and discounts around customer needs. 
3. Intimacy: Retail is a two-way relationship, and customers want brands to make them feel valued by providing them with experiences that resonate with them and suit their lifestyles. 

The rise of Artificial Intelligence (AI) will play a key role in helping retailers meet changing customer expectations. The value of AI in the retail market is already significant, estimated to be $11.83bn as of 2024 – and experts predict meteoric growth over the next few years, with market value reaching $54.92bn by 2033. 

Of all the forms of AI you can explore, Conversational AI offers the most potential for retailers who want to better service customers in an evolving, ever-demanding world. 

In this guide, we’ll explore what Conversational AI is, how it works for retailers, and the best ways you can implement this technology into your existing team to help you succeed in a fiercely competitive future.  

Key Takeaways

1. A combination of Conversational AI and Generative AI powers human-like, context-aware agents across voice and text, automating high-volume and low-complexity tasks while escalating seamlessly to humans.
2. Customer experience lifts come from faster answers, real-time multilingual support, and true self-service (orders, returns, FAQs) across channels—reducing friction and wait times.
3. Agents access CRM/history to tailor recommendations, trigger proactive outreach (recalls, offers), and stitch together end-to-end buying journeys.
4. Agent Assist handles ID&V, transcription, summaries, and next-best actions—freeing human teams for complex cases and improving morale.
5. Proven retail use cases include WISMO/order status, returns/refunds, KYC/ID&V, product Q&A, in-store/online shopping assistants, and intelligent routing—driving measurable efficiency gains.
6. Recommendations include starting small (e.g., ID&V), ensuring integrations with CRM/commerce/back-end systems, and aligning/briefing staff—then scaling capabilities and Agentic AI for greater impact.

What Is Conversational AI In Retail?

Conversational AI is a type of AI that deals with Natural Language Understanding (NLU). It is used to hold conversations with users across text and voice channels, and it is capable of recognizing intent and understanding context. Conversational AI is not a standalone technology and is usually paired with Generative AI, which is a form of AI that generates text and content.

Learn more about each of these technologies and how they work together in our guide here.

For retailers, Conversational AI can power a customer-facing AI Agent that engages users in human-like conversations. This agent takes over the vast majority of the low-complexity, high-demand tasks that burden your human service team. The AI can work both reactively and proactively, fielding inquiries or reaching out to customers for matters such as returns or product recalls. 

As well as being able to hold conversations, the AI can also take the actions most appropriate to the conversation – whether that be updating a customer’s address at their request or alerting your customer service team if it recognizes a need for human intervention. 

Benefits of Conversational AI in Retail

Conversational AI brings a compelling array of benefits to retailers, with the capacity to support vital service processes whether you operate in a traditional retail model or solely practice e-commerce. 

Enhances Customer Service Offering

The majority of customer service calls for retailers can be separated into two categories: general queries and order issues. An AI Agent built with Conversational AI is capable of fielding the vast majority of both, which means your customers won’t have to wait on hold and can either get a direct resolution or have the mundane aspects of the call taken care of before being handed to a human agent.

By making it easier for customers to contact your business, ask questions, or have their issues solved, Conversational AI dramatically improves customer satisfaction without the significant cost of hiring new teams. 

Conversational AI works across both text and voice to further support customer preferences, meaning they can contact your team using their preferred approach. AI Agents also translate in real-time to offer multilingual support for customers speaking their native language. 

Implements Versatile Self-Service 

Self-service isn’t a new concept in the world of retail. You may already have self-checkouts in your physical stores – but it’s also a growing concern for digital consumers. Where possible, customers value being able to engage in self-service to accomplish basic tasks without the need for assistance. 

The key task is to balance the utility and empowerment of self-service against potential frustration or friction. You need a system that provides options for customers to accomplish tasks on their own but can also recognize when said user needs further support and take the appropriate action to provide it. 

An AI Agent provides a multi-channel self-service option that users can interact with across whichever device they choose. The AI Agent can then either answer questions directly, take the relevant action, or alert a human team member to intervene. This all helps contribute to a feeling of empowerment for the customer, who can take action immediately and either get their problem solved or be transferred to a human agent without having to wait on hold or resubmit basic identification. 

Augments Human Workforce

Though many employees may fear the idea of adopting AI because they think they’ll be replaced, the opposite is true: Conversational AI actually assists your existing employees in many different ways, which we’ll explore in the use cases section further in the guide. 

In doing so, AI Agents actually improve your employees’ overall productivity levels and reduce the labor associated with mundane tasks like identification and verification. With AI on their side, your team can better focus on more complex and rewarding cases. This makes managing and scaling your team more cost-efficient, improving job satisfaction and morale. 

Empowers Better Personalization 

Conversational AI is personal by nature – interactions will be highly specific to each conversation. The AI Agent is integrated with your backend systems and can view a customer’s CRM record, identify previous contact cases, and use all of this information to personalize the interaction further. 

Personalization goes beyond simply customizing dialogue to reference a customer’s name or other specific details. In retail, customers want businesses to anticipate their needs and tailor products and service offerings around them. 

An AI Agent can help support this by engaging in proactive conversations with users, gathering information about their needs, and then developing tailored recommendations or buying advice. 

Creates Seamless Buying Journeys

Friction is the enemy of any retailer. If a customer has to jump through too many hoops or encounter challenges in order to buy a product, they’ll simply switch tabs to the next competitor’s website. An AI Agent can exist as a top-level layer to tie a customer’s buying journey together, eliminating friction and ensuring a smooth journey from awareness to purchase and even providing post-sale support. 

Offers Proactive Support

Retail is about connecting with your customers. Being proactive is a key part of the marketing process, reaching out to customers to inform them about new offers or product launches – but proactivity is also important in customer service, too. 

Conversational AI allows you to practice personalized, proactive customer support. The AI Agent can notify a customer about a product recall, ask them for feedback, or even offer them a new deal. The customer can then take the appropriate action through the AI Agent, rather than opening a new window or switching devices. 

Conversational AI vs AI Chatbots: What's the Difference?

A chatbot is a term used to describe pre-AI chat interfaces that allow for limited customer interactions locked to pre-defined responses. Conversational AI is a type of AI that facilitates conversational capabilities, utilizing Natural Language Understanding (NLU) to build smarter chatbot technology. 

Where early chatbots were limited to scripted, rule-based dialogues, modern AI Agents now leverage Conversational AI and natural language understanding to interpret human language more flexibly. With the addition of Generative AI, they can produce contextually accurate responses, retain information for short and long-term, and even ‘learn on the job’.

Agentic AI Agents are a further evolution of automated agents. They are goal-oriented and powered by LLMs, enabling them to understand context, plan actions independently, and execute tasks without requiring every process to be scripted in advance. 

NiCE Cognigy’s Composite AI approach combines the strengths of both—using structured conversational AI where precision is critical, while seamlessly handing off to Agentic AI when flexibility and contextual reasoning are needed. 

Read our guide to learn more about the differences between chatbots and Conversational AI. 

Use Cases of Conversational AI in Retail

The retail sector offers many opportunities to better interact with customers, both in-person and online. Conversational AI can improve some of the core processes in your business, with use cases that include: 

Order Information

One of the most common types of customer query for retail service teams is known as a WISMO (“Where is My Order?”) request. To solve the customer’s problem, teams need to check order information, identify the issue, and potentially take further action, such as querying your logistics partners to confirm delivery details. All of this eats up time, reducing efficiency and potentially frustrating customers. 

Conversational AI gives you a way to automate the majority of your order-related queries. The AI Agent can take all necessary details, look up the order in your CRM, and either respond directly or flag the case for further attention. Throughout this, the agent will be conversing with your customers to ensure they feel supported.  

The AI Agent can also help process returns or refunds. It can take the necessary information from a customer and even guide them through photographing a faulty item/proof of return. This reduces friction because a customer doesn’t need to go through multiple stages and can complete the entire return in the same interaction. 

For example, online glasses retailer Mister Spex introduced an AI-powered agent that streamlines customer service across multiple touchpoints. The solution verifies customers directly over the phone, handles fully automated WISMO inquiries, and sends out follow-up emails without the need for human intervention. By connecting seamlessly to the company’s CRM, the AI Agent retrieves the necessary knowledge to provide accurate answers, while also forwarding calls to the right support agents based on customer intent.

The impact has been significant. Mister Spex now achieves a 70% caller verification rate and saves around 30 seconds per call. More than half (52%) of WISMO requests are resolved entirely through AI, while 96% of calls are routed intelligently to the correct support team. Additionally, 88% of return label requests are automated via phone, demonstrating how the AI Agent has transformed efficiency, accuracy, and customer experience.

KYC/ID&V

One of the most obvious use cases for Conversational AI is in the role of ‘Know Your Customer’ style identification and verification processes. Asking customers for basic information to confirm their identity and potentially further evidence to verify them happens in almost every customer service case – which means it represents a huge time burden for agents. 

Conversational AI is more than capable of automating this process, alleviating the strain on your human employees. AI can even add value to the process by conversing with users through each stage, rather than forcing them to recite details flatly. 

Once verified, the AI Agent can route the case to a human agent who will have all the prerequisite information needed to resolve it. 

Mister Spex has also proven the effectiveness of this approach, as the AI Agent initiates ID&V, which reduces errors compared to verifying names or emails over the phone. Once verified, it connects directly to the CRM to retrieve order details and seamlessly transfers to human agents when necessary.

Question & Answer Support

Customer service cases aren’t always related to existing orders. Often, your team fields calls where a customer asks basic questions about product information, opening hours, stock availability, etc. 

There’s a fine balance to strike between available resources and being able to answer these queries in a way that makes a customer more likely to buy. An AI Agent is the perfect automated solution, giving your customers a resource that they can ask questions to at any time and through their preferred contact method. 

Škoda uses a NiCE Cognigy AI Agent that recommends car models through intuitive questioning, asking about things like comfort versus speed preferences, trunk size, and budget, while also answering FAQs, helping customers book test drives, and securely routing leads to dealers with encrypted information. By leveraging both LLMs and structured product knowledge, the AI delivers accurate and engaging interactions that enhance the customer experience.

Agent Assist

Conversational AI isn’t just about AI Agents interacting directly with customers. Agent Copilot allows your AI Agent to support existing employees and improve the quality and speed of their service.

During a customer interaction, the AI Agent will automatically transcribe the user’s input and, if required, translate it. It will pre-verify the user and provide full case context to your human team. Once the call is completed, the AI Agent will even create a summary and log it for the agent, further removing another time-intensive, manual task and helping them be more efficient. 

Bosch Power Tools has integrated NiCE Cognigy’s Agent Copilot to support contact center agents in real time. The AI Agent actively listens to calls, retrieves relevant information, and suggests next-best actions to guide agents through customer interactions. It also performs sentiment analysis, transcribes conversations, and completes wrap-up tasks by saving all information directly into the backend system, streamlining workflows and boosting efficiency.

Shopping Assistant

Retail customers have already embraced virtual assistants and live chat support as a result of the e-commerce boom. You can use Conversational AI to build a valuable self-service shopping assistant that helps customers shop online or in-store. 

From directing users to the right area in a store to personalizing recommendations based on size or style preferences, your AI Agent helps streamline the buying journey to improve the likelihood of a successful conversion. 

Henkel, the parent company of haircare brand Schwarzkopf, proves the effectiveness of AI Agents in augmenting the shopping experience. The AI Agent supports customers with haircare routines, product selection, and other personalized advice that enhances the customer experience and boosts brand loyalty.

Best Practices for Conversational AI in the Retail Sector

Feeling ready to explore AI integration in your retail business? Here are some best practices you should implement in order to give yourself a good foundation for growth and avoid costly mistakes. 

Start Small & Scale

Retail is a complex business model that involves many different customer service processes, from basic product queries to tracking down lost orders or issuing refunds. 

To implement AI Agents effectively, start with a lower complexity use case and scale from there. For example, ID&V and KYC are often an ideal starting point for brands adopting AI Agents because they are repetitive and easy to automate. An AI Agent can quickly verify details like zip codes or account numbers when integrated with backend systems, ensuring compliance while reducing errors. This makes the use case low-risk but high-impact.

The immediate benefits of this relatively low level of integration include faster solutions for customers, improved accuracy (e.g., when typing in numbers), and time saved for human agents by removing repetitive verification steps.

Automating ID&V and KYC delivers quick ROI while gaining stakeholder buy-in for more advanced AI use cases.

Assess Existing Systems

An AI Agent is best thought of as a meta layer that sits above your existing systems and processes and can interact with them to best support a customer’s needs. For example, the AI Agent should be able to verify customer information against their CRM details and then access your database to track down their order. 

To accomplish this, you’ll need to ensure your legacy systems are suitable for AI. Some retailers have bespoke tech that may cause issues, but most standard tools and technology are easily integrable. 

For example, if your brand uses Salesforce, then integration of Voice Gateway is an excellent way to augment your sales professionals by using Conversational AI to provide them with an intelligent, personal assistant who can support them with instant, flexible responses during sales interactions. 

Regardless of your tech stack, it’s always best to involve your development team in any conversations with an AI provider to help reduce the chance of problems. 

Brief Your Employees

Human customer service teams fear AI because of misunderstandings. If you’re considering an AI Agent, you should brief your team and demonstrate how it can improve their workflow and improve their lives.

Agent Copilot is an excellent example of this, as it helps reduce anxieties and also ensures the team can utilize the AI more efficiently when you go live. Copilot improves the working lives of human agents by automating laborious, time-consuming processes, and collecting relevant and accurate information. This means human teams can focus their attention on the more complex and often rewarding parts of their roles and make a real difference to customers’ lives. 

Use NiCE Cognigy to Implement Conversational AI Solutions for Your Retail Business

Cognigy.AI is an expert AI provider that works with retail clients across the globe. We bring powerful automation to enterprise brands to cut costs, increase agent efficiency and improve overall business performance. 

Seeing is believing, so book a demo with our team today. 

Frequently Asked Questions

What Are the Risks of AI in Retail?

The main risks of using AI in retail are related to data privacy. Businesses need an AI provider who can work with them to ensure all data is stored safely and securely in compliance with local regulations.  

How Is AI Used in a Retail Store?

AI can be used in different ways in a retail store. Often, it enhances buying experiences by acting as a shopping assistant that directs customers to products, answers questions, or provides guidance. 

How Can Conversational AI Help Improve Customer Experience?

Conversational AI provides a means to field customer queries quickly and speed up effective outcomes. AI improves customer experiences by removing the need for hold queues and providing 24/7 access to efficient customer service.