AI in Customer Experience: The Top Use Cases to Explore

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Imagine a world where every interaction a company has with a customer is quicker, more convenient, and more personalized than ever before. That’s what AI in customer experience has to offer.

For years, companies have leveraged artificial intelligence to access deeper insights into customer behavior, streamline and automate tasks, and improve team efficiency. Now, the rise of more advanced forms of AI, from conversational and generative AI, to autonomous agents, is introducing us to a world of new opportunities.

Analysts like Metrigy predict around 65.7% of inquiries will be resolved by AI throughout 2025, and as technology vendors introduce new ways to make advanced AI more accessible, (such as the pre-built agentic AI solutions from AWS, Salesforce, and Microsoft), demand will only continue to grow.

Here, we’ll examine some of the top use cases for AI in customer experience, and explore some of the unique tools business leaders can experiment with today.

The Top Use Cases for AI in Customer Experience

It’s worth noting that the use cases for AI in customer experience are still emerging. Only a few years ago, we had a limited number of AI analytical tools, and basic chatbots that could only respond to pre-determined questions with simple answers. Now we have generative AI, conversational AI, large language models, and even agentic AI.

For contact center leaders, and companies focused on customer experience (CX), the opportunities are practically limitless. Here are just some of the most significant use cases businesses can consider exploring to upgrade customer satisfaction, business efficiency, and more.

1. Predictive Analytics: Enabling Proactive Service

One of the most exciting applications for AI in customer experience comes from the ability for AI tools with machine and deep learning capabilities to effectively “predict” the future. Based on historical and real-time data, AI tools can rapidly anticipate customer needs, customize their services to suit them, predict trends, and even enhance decision making.

Predictive analytics tools help companies to deliver more proactive, targeted experiences that improve customer satisfaction and loyalty. As an example, fashion retailer Motel Rocks uses Zendesk’s AI platform to identify the intent of customers, predict their needs, and direct them to the right agent.

With the right technology, companies can even take this functionality a step further, identifying potential customer requirements and challenges before customers ever get in touch.

For instance, Five9’s range of artificial intelligence tools allows organizations to analyze customer conversations across all channels (voice and digital), and pinpoint trends, opportunities, and bottlenecks. It can even offer insights into the best times to follow up with customers or share new information with them about products and services.

Combined with IoT (the Internet of Things), AI tools can even monitor crucial systems in different environments (such as the energy or engineering space), and detect potential signs that a machine might suffer a malfunction. This allows companies to take a proactive approach to fixing issues, or informing customers about downtime before it happens.

2. Sentiment Analysis: Understanding Customer Emotions

Sentiment analysis is another cutting-edge application for AI in customer experience, allowing businesses to understand the emotions and feelings of their target audience. AI-powered tools can gather insights from things like a customer’s tone of voice, or the worlds they use, to show business leaders and contact center agents which customers are at risk of churn, or showing dissatisfaction. This can help businesses take proactive approaches to reducing churn and turnover.

Sentiment analysis can even help agents to improve the outcomes of conversations in real-time. For instance, Dialpad’s Live Sentiment analysis tools can instantly detect signs of positive or negative sentiment. Once they assess a customer’s “mood”, the bots can offer agents real-time guidance on how to improve the outcome of a conversation or de-escalate an issue.

These bots can also send instant alerts and notifications to supervisors, helping them to step in and handle a complex conversation before it escalates further. On top of that, with sentiment analysis tools, companies can gather deeper insights from customer feedback, allowing them to make more intelligent decisions on how to improve retention and loyalty rates in the future.

3. AI in Customer Experience: Streamlining Interactions

Probably one of the most obvious use cases for AI in customer experience, involves using intelligent tools to streamline interactions. Intelligent tools can eliminate a lot of the complexities that might lead to a sub-par interaction with an organization. For instance, when a customer calls a contact center an intelligent IVR system built into a CCaaS platform can immediately identify the needs of the caller, and route them to the correct agent or department.

Some tools can even simplify call transfers and escalations. For instance, the Verint Interaction transfer bot can summarize the conversation a customer has had with a company so far, and pass that information along to the next agent, preventing the client from having to repeat themselves.

AI tools can also:

Assist agents throughout the call: AI agent assist tools, like Salesforce Einstein AI can surface data from multiple different sources during a conversation. They can help agents to troubleshoot issues faster, find quick responses to customer queries, and even deliver responses at speed with suggested replies.
Minimize communication issues: AI solutions can automatically translate and transcribe conversations over the phone, making it easier for teams to communicate with global audiences, and people with poor phone signals.
Detect automation opportunities: By pinpointing commonly asked questions and issues, generative AI tools can help contact center leaders discover automation opportunities. For instance, the AI Insights tool from Five9 can suggest knowledgebase articles and FAQs businesses can create to improve the self-service experience.

4. Automating Discussions with Bots and Assistants

Chatbots and virtual assistants are another of the most commonly referenced use cases for AI in customer experience. They’re becoming increasingly crucial in a world where 90% of customers expect instant responses from companies, and many clients want to be able to connect with companies across various channels, from chat, to voice, and SMS.

Today’s AI-powered chatbots and assistants are becoming increasingly sophisticated, thanks to the use of machine learning, generative AI, and conversational AI technology. Modern bots don’t just respond to questions by detecting keywords and matching them to a pre-configured response.

They can understand customer intent, maintain context throughout a conversation, and even complete a range of tasks autonomously. We’re even seeing a rise in agentic AI solutions, like the Salesforce Agentforce bots, which can be customized to handle various different customer service tasks.

These bots can do a range of things to help customers, without the need for human input. For instance, the Service agent can identify a customer problem, troubleshoot an issue, implement a fix, update CRM data, and more, all on its own.

Some bots can even adjust to changes in customer intent on the fly. For instance, the Conversation Booster by Nuance uses generative AI to allow users to carry out various self service tasks in the same discussion, from scheduling appointments, to making payments.

5. AI in Customer Experience Personalization

Studies show that 71% of consumers expect personalized interactions whenever they communicate with a brand, and 76% feel frustrated when they get a “generic” experience. AI makes it easier to hyper-personalize interactions at scale.

For instance, tools like Salesforce’s Service GPT can pinpoint the nature of a customer’s query, then sift through data about that customer to deliver a personalized response specific to their needs, and interests. Similar AI-powered tools can analyze user behavior, purchasing history, and signals expressed during a conversation to align their recommendations to each user’s preferences.

These bots can automatically suggest products and services that might be relevant to a customer, based on their history. They can also advise agents on the best way to handle a call or service request, based on what they learn throughout the customer’s lifecycle.

AI solutions built into CRM platforms can also help companies take a personalized approach to nurturing leads. For instance, HubSpot’s Breeze collection of AI tools can support companies in identifying the right time to connect with a customer, and the right channels to use. They can automate follow-up processes and create message content personalized to each customer too.

6. Improving Agent Efficiency and Productivity

Even as demand for AI in customer experience continues to grow, the success of any contact center still depends on how efficient and productive its agents are. We’ve already mentioned some of the ways that AI can make agents more efficient. For instance, tools like Zendesk’s Agent Replies system can assist professionals as they type responses to common questions.

However, there are numerous other ways AI can transform agent performance, such as by automating:

Notetaking processes: Taking notes is often essential for delivering excellent customer service. It’s how companies gather valuable information they can use to personalize future interactions. However, taking notes during a call can be difficult. Vendors like Sprinklr offer AI tools that automate the process, allowing agents to stay focused on the discussion.
Call wrap-ups: Aside from taking notes throughout a conversation, most agents need to complete various tasks at the end of each call – such as updating contact summaries on a CRM platform. Generative AI tools like the Genesys Copilot can automate this process, allowing agents to move onto new calls faster, reducing waiting times.
Creating valuable content: As mentioned above, generative AI tools are excellent at creating content that can support the customer experience. These tools can create everything from knowledge guides, and FAQs, to scripts for sales teams, or onboarding materials.

7. Optimizing Workforce Management and Training

Aside from improving the overall performance of agents in a contact center, AI in customer experience can help businesses to get more out of their teams, by enhancing workforce management. Tools like Dialpad’s AI-powered workforce management tools can use historical data to predict the best scheduling strategies for customer-focused teams.

These tools even come with proactive planning solutions, and can make real-time adjustments to suggestions based on current demands. Beyond that, AI-powered tools can help companies make the most out of their times by automating quality assurance insights.

Verint’s AI tools, for instance, can track metrics related to call quality, such as customer satisfaction rates, transfer rates, and more, to identify potential issues that companies might need to overcome. They can even offer valuable insights into the training requirements of each team member.

For instance, the Manager Assist tool for Amazon Connect can generate automatic performance summaries for each agent-customer conversation, and suggest potential coaching strategies. There even agent assist bots that can deliver coaching insights to employees in real-time, providing them with a consistent way to upgrade and improve their performance.

8. AI in Customer Experience Compliance, Safety and Security

As well as providing feedback to agents throughout a conversation, and alerting supervisors to issues linked with negative sentiment, AI tools can also help to boost compliance. Intelligent monitoring tools can be trained to track potential compliance issues, like an agent failing to inform a customer when a call is being recorded.

AI tools can also monitor for potential safety and security risks. Increasingly, many companies are beginning to embed AI algorithms into the tools they use to validate customers, using them to identify people based on biometric factors that are difficult to replicate.

These tools can also track conversations and customer actions for signs of suspicious behavior, alerting security teams to potential risks. AI tools could even help companies to comply with a wide range of other regulations – beyond those linked to data security and privacy.

For instance, with AI-powered tools in the contact center, organizations can potentially monitor their energy usage, sustainability, and ESG initiatives. This could be increasingly important in the years ahead, as governments and industry leaders continue to prioritize sustainability.

9. Collecting in-Depth Insights with AI

Finally, if there’s one thing that AI excels at in any environment – it’s collecting, analyzing, and optimizing data. As companies strive to deliver more personalized experiences to customers at scale, without compromising on data security issues or efficiency, AI is becoming increasingly important.

It allows organizations to rapidly track a wide range of metrics, from how well agents are performing in their tasks, to how often they’re adhering to compliance standards and best practices. AI can also be extremely useful at sourcing direct insights from customers.

For instance, tools like the “Sprinklr Survey” solution leverages strategy documents and brand guidelines to build customer questionnaires that can be sent to customers automatically across a range of channels. Once customers complete these surveys, large language models can sort through huge volumes of data, and pinpoint potential opportunities, trends and challenges.

AI solutions can even help to more effectively predict customer satisfaction scores and NPS scores. The Dialpad AI-powered CSAT tool, for instance, automatically collects CSAT score data across all conversations, and starts producing predictive insights right out of the box.

With these tools, companies will no longer need to rely exclusively on surveys that customers might not want to fill out to keep their finger on the pulse of customer satisfaction.

Discovering the Opportunities for AI in Customer Experience

Although AI in customer experience will never eliminate the need for real human beings to handle certain customer interactions, it’s impossible to ignore the potential. As artificial intelligence grows increasingly more advanced, it’s ability to make customer service teams more efficient, improve customer satisfaction, and even reduce operational costs is growing.

The key to getting the most value out of this technology, is making sure you select the right vendor to power your AI transformation. Here at SaaSCom, we excel at objectively supporting companies in making the right decisions for their technology needs.

Whether you’re looking for an AI-powered application for your contact center, an intelligent CCaaS solution, or something brand new, we can help. Plus, we’ll ensure that your digital transformation strategy doesn’t come at the expense of your sustainability initiatives.