Agentic AI in customer experience

Agentic AI systems can handle complex tasks, combine processes, and solve problems without supervision. But what do they mean for customer experience?

What is agentic AI?

Agentic AI is the term given to a new breed of artificial intelligence model that’s able to proactively link tasks together to solve problems and complete tasks without needing human intervention.

That means going several steps beyond the ‘call and response’ paradigm that typical generative AI models employ – where AI is instead able to make decisions and take action based on information that spans websites, systems, and sub-goals.

This could be:

• Adjusting a booking if plans change
• Automatically surfacing and applying relevant deals
• Setting up a savings plan that dynamically draws money each month
• Identifying support agent training needs and auto-scheduling a coaching

The term agentic has a double meaning here. It’s being used to position the tools as AI equivalents of human ‘agents’, in the same way you might think of a person on the end of a customer support call. But it also denotes that these new AI models have a sense of agency – that they’re able to complete tasks without constant prodding and supervision.

Publicly available AI models have come on in leaps and bounds in a relatively short time, but the jump to truly agentic AI makes the technology more capable of being a true digital assistant.

This article explores the broader trend of agentic AI, how it’s redefining customer experience, and how that lays the foundation for fresh innovations like Qualtrics® Experience Agents™.

Agentic vs Generative AI

Generative AI describes any AI model capable of generating new content from prompts. That might be written word, as with Large Language Models (LLMs), images, or video.

Agentic AI systems use these abilities as one tool in their belt, but they also interpret context, learn from past interactions, and add other machine learning-based capabilities to control systems, speak to third parties, and extend their reach to solve more complicated problems. With agentic AI, issue resolution becomes less about asking for individual answers and more of an exercise in sending artificial intelligence off to connect the dots by itself.

In other words? It’s the difference between asking someone how to make a cup of tea and asking them to make one for you.

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What are the benefits of agentic AI?

Agentic AI can handle complex tasks using a mix of real-time data, natural language processing, and system interoperability. The big benefit is that it can link all this information to holistically solve problems and complete processes that gen-AI chatbots have previously needed prompting to do.

Exactly what an AI agent can do depends on the tool at hand, the setting, and the use case, but agentic abilities range from proactively surfacing insights from separate data sets, to using your browser to book a vacation for you.

OpenAI’s Operator, for example, is an agentic AI model that has its own web browser, meaning it can complete tasks like ordering your regular groceries, compiling research sources for a paper, or building an itinerary based on real-world events.

As we noted in our 2025 Global Consumer Trends Report, agentic AI systems are going to have a huge impact on a bunch of different industries – with customer experience management being a biggie.

When deployed intelligently, agentic AI allows brands to:

• Proactively solve problems before they arise.
• Deliver hyper-personalized interactions tailored to every customer.
• Create seamless, human-centric experiences at scale.
• Build trust and loyalty with deeper emotional connections.

Our research showed that 72% of executives believe AI will transform their approach to customer experience, while 69% expect it to significantly or completely change the way their industry operates over the next three years.

In many settings, agentic AI is what’s going to be driving that change.

AI agents are the difference between having to ask a model “What is this customer calling about?” and a system where the problem is solved automatically before things escalate. That way the question becomes a workflow: “This customer is calling about a billing issue, but the problem is that they haven’t updated their payment method. We’ve sent them a new payment authorization.”

The human benefit of AI agents

Customer queries are sometimes simple, but often they’re things that require a human to solve. So is agentic AI going to get in the way of tried-and-tested human know-how?

In reality, deploying and enabling AI agents to help can actually bolster that human connection. That’s because they’re more adept than ever at handling the mundane, day-to-day, routine tasks involved in customer support. And that frees up human agents to be where it matters most – those tricky, important customer interactions where the human touch is absolutely necessary.

CX use cases for agentic AI

In customer experience, agentic AI can be a game-changer for teams looking to help streamline their customer journeys and optimize the support process. Here, AI agents can be used in two separate ways:

Customer-facing AI agents

In a customer-facing scenario, agentic AI can use real-time data from websites and back-end systems to piece together complex answers to problems.

Let’s take a cellphone network as an example. Whereas a generative AI chatbot might be able to help a customer find the right webpage with deals for upgrading their phone and plan, agentic AI could use the customer’s purchase history, live deal information, and the online ordering system to suggest the best options for them – and then help them complete the upgrade process without leaving the chat.

Agent-facing AI agents

Agentic AI can be used internally to help human agents handle complex tasks – like linking customer data to personalized offers, or proactively fixing issues as they’re raised. These back-end workflows let human support agents do what they do: delivering empathetic, people-centric service.

Agentic AI systems are fast becoming the backbone of customer experience because they’re able to piece information together and take relevant action in real time. And that makes them an incredible asset to human support teams.

Agentic AI use cases

The hallmark of agentic AI is proactivity. AI systems that can gather and act on siloed data are great for getting ahead of issues and taking steps to stop

eCommerce and supply chain management

Agentic AI can pick up abandoned carts and take measures to encourage the customer to complete their purchase – whether that’s by sending them a relevant offer, or automatically firing off a timely reminder email.

Supply chain management, meanwhile, becomes an automated process with agentic AI systems. Using real-time supply data, AI systems can automatically reorder stock, and let customers know when new inventory is set to arrive.

Operational efficiency

AI agents can bring together real-time data from a bunch of sources to scale operational resources up and down automatically. That could be server scaling for peak demand periods, or it could be helping to manage staff rosters based on vacation schedules.

Itinerary management

In the travel sector, agentic AI systems can make bookings – even from across websites and systems – bundle up and send detailed itineraries to customers, and even update things when they change. That includes keeping tabs on live flight delays or even extreme weather.

Anti Fraud measures

AI is already in use in the anti-fraud industry, but agentic AI can make things smarter. Instead of reacting with simple yes/no protocols to possible fraud flags, artificial intelligence can draw from people’s purchase histories to make more informed decisions.

So while a banking customer might have their card blocked for making an outlandish purchase, an agentic AI could override that rule if it knows that the customer has been saving for it in a separate pot. Or, on the other side of that spectrum, agentic AI could go beyond simply blocking a customer’s debit card by getting a replacement sent out automatically.

Hyper-personalization

By combining insights from customer segments, real-time market trends, purchase histories, and customer behavior, you can deliver incredibly tailored, personalized offers that resonate on an individual level. Agentic AI can automate all that by delivering bespoke offers right to people’s email inboxes or app notifications – without anyone lifting a finger.

Self-service updates and workflows

Self-service knowledge bases tend to be static info dumps that need to be periodically updated. Agentic AI systems can change that (streamlining the self-serve experience) by using information from every customer interaction – direct or indirect – to continually update FAQs and resources. Agentic AI tools can also trigger workflows that direct users along the right path for their particular issue.

Meet Qualtrics Experience Agents

Agentic AI isn’t some far-flung idea. It’s already here – and already in action at some of the world’s biggest companies. For customers, that means incredible experiences that feel personal, agile, and proactive. For brands, it means being able to prioritize which customer queries absolutely need human agents, and which are more routine tasks that can be delegated.

For organizations looking to prioritize proactive, intelligent customer experiences, Qualtrics Experience Agents are the next giant leap. Our intelligent, interconnected Experience Agents will soon be added to the Qualtrics XM Platform® to drive more action in all the moments that matter to your customers and employees.

Unlike alternatives that are designed to complete more operational tasks, Qualtrics AI Experience Agents will:

• Listen across the entire customer journey – and interpret context – to resolve issues in real time by leveraging survey, call, chat, and digital experience analytics data.
• Understand frustration, and take action instantly without customers needing to ask.
• Detect real-time sentiment, understand personal history, and apply brand and industry data to shape each interaction in ways that others can’t

The result? Higher customer satisfaction, faster resolutions, lower cost-to-serve, and engagements that truly enhance customer relationships.