AI In Customer Experience: Leaders Are Placing Big Bets In 2025 (New Data)

Artificial intelligence has transformed CX at every level. With the ability to automate sophisticated decision-making processes, save millions a year cutting waste from routine tasks, and provide hyper-personalized customer experiences at scale, it’s no wonder over 90% of CX leaders have already put it to use. 

In the past year, we’ve seen widespread AI adoption across CX teams of all sizes. In our recent survey on CX trends in 2025, CX leaders shared dozens of AI use cases they already found valuable and expressed optimism about the potential of future advancements. 

This year, we expect a shift from tentative experimentation to mature, large-scale implementation of AI across areas like agent assist technology, intelligent contact centers, chatbots, and omnichannel support. 

The outcome of this growth won’t be full automation—that’s not the magic of AI for the customer experience. Get ready to see more companies finally clean up and unify their CX data, track real ROI from their AI investments, and achieve the seamless AI-to-human handoff that’s so elusive without the right technology in place.

Read More: CX Trends in 2025: ROI, Scale, and a Lot More AI

The AI Market Is Booming, but Vendor Sprawl Is a Problem

Since ChatGPT stormed the market in late 2022, almost every major software vendor raced to incorporate generative AI into their existing products. Hundreds of new tools sprung up with their own version of today’s popular LLMs and predictive models, each promising the best results while creating a busy and complicated market for CX teams to navigate.

In reality, using AI for CX requires a great deal of orchestration behind the scenes to attend to customer needs, including a nonstop flow of data on customer behavior, their purchase history, past support tickets, and so much more. Even in 2025, most AI tools don’t have the infrastructure or CX specialization to support the integrations, workflows, and real-time data pipelines that are required to truly improve the customer experience. 

As a result, having more tools isn’t better. In fact, 81% of CX leaders believe they could improve the customer experience if they consolidated customer data from all interaction points into one system of record. Fewer tools, more productive conversations. 

Top CX Challenges: Data Complexity, AI Unknowns, and Limited Resources

CX leaders named a handful of data management challenges as their top concerns in 2025, including accessibility, integration, and handling the high volumes of both structured and unstructured data needed to leverage AI. 

👉 39% of CX leaders cited data integration as a challenge with AI for CX. 

In addition to hiking up technology costs, having too many CX tools and siloed data sources makes it nearly impossible to piece together a complete view of a customer in real time. But LLMs and other ML models require reliable, instant access to customer data from every touchpoint and database, from a CRM note to live call audio—without it, the practical application of AI for CX becomes severely compromised.

Although AI adoption is high, the lack of precedent and familiarity still poses a challenge for CX leaders trying to get employees and customers comfortable with using it. Support and contact center reps may wonder about their job security, customers may get frustrated with early implementations, and the regulatory environment may change often in the coming years. 

👉 33% of leaders reported that employees are worried about AI replacing them.

The good news is that this uncertainty should be expected for any emerging enterprise technology. As you experiment with and scale AI capabilities, you can remedy most issues with clear communication, consistent training, and robust analytics that will catch any friction before it diminishes customer loyalty.  

It’s also important to listen to customer feedback. Monitor customer reviews across social media and forums and collect data from customer satisfaction surveys. Some AI-enabled platforms even allow you to analyze customer sentiment across the web or from call and chat transcripts to uncover indirect feedback that’s just as valuable.

Investments Are High in AI-Powered Chatbots, Agents, Writers, and More

Over 90% of customer experience teams today are at least experimenting with AI, with just under 10% calling their AI adoption “mature.” The race is on to see who can scale their best use cases and drive consistent ROI with AI technologies. 

CX leaders are investing the most in AI writing, chat, and agent assist technology. Of the three, the first two are almost entirely customer-facing—LLMs and powerful decision-making models help CX stakeholders from multiple teams draft emails, create content, chat live with people across various products and channels, and remove hours of manual interactions from the customer journey.

Almost 40% of CX leaders already use AI writing tools with customer interactions—and another 25% plan to do so in 2025. 

The other, agent assist, can have a profound impact on how well a human agent can solve customer problems and do their work efficiently. 

👉 26% of CX leaders say agent assist technology is their biggest focus of future investments. 

This technology is poised to be the biggest new investment for CX teams in the coming year, using sophisticated machine learning models to surface contextual data in real time, highlight upsell opportunities, and anything else a rep might need while chatting with customers by phone, video, or messaging platform.

Here’s the full list of where companies are investing in AI to drive customer satisfaction, customer engagement, retention, and other top CX metrics:

• GenAI for writing to customers
• Agent assist tools 
• Self-service chat and voice bots
• QA and compliance
• Language detection and translation
• Personalization
• Call routing optimization
• Real-time sentiment analysis
• Process automation
• Predictive analytics
• Proactive issue resolution

Companies Are Racing to Unify CX Data and Unlock AI Scale

Almost every CX team that’s adopted AI-driven functionality is seeing some degree of value. The potential of AI-powered contact centers, intelligent self-service onboarding and customer support experiences, and dozens of other use cases transform the customer journey is exciting—as long as the cost isn’t too high.

👉 80% of early-stage AI adopters already reported medium to high value.

Innovative CX teams have already adopted a unified CX platform to combat complexity and lower technology costs as they scale AI. 

This type of enterprise-grade customer experience platform comes with all of the capabilities that streamlined, AI-driven CX demands. Multiple LLMs and models to choose from, built-in guardrails that keep company and customer data secure, integrations and APIs for the many tools and channels that support CX efforts, and the flexibility to test and change things as more data is available.

Related Post: What Is Unified Customer Experience Management (CXM)?

Now Is the Time for Approving Bigger AI Budgets

As CX leaders adopt AI en masse, there’s another point they largely agree on: it’s far easier to get approval for new CX investments today. 

Execs are more likely to understand the value of CX in general (79% see it as a revenue driver vs. a cost center), and improved technology has made it easier to quantify and visualize the impact CX has on company-wide goals for growth, revenue, and margins. And nearly all (96%) of CX leaders say the company’s executive leadership believes CX is a key driver of business outcomes.

If you’re wondering whether to ramp up your own team’s use of AI, it’s time to take that step. While 92% of companies have adopted AI, less than 10% are fully mature in their use of it. There’s still time to catch up, but we expect many to jump to higher levels of AI maturity in 2025.

The Ultimate Goal: Perfect AI-to-Human Handoff

The potential of AI in the world of CX is more powerful than automation alone. The right implementation of it can eliminate one of the most frustrating points of friction in the customer journey: the handoff of a customer from an AI to human agent. 

👉 98% of CX leaders recognize seamless AI-to-human transitions as critical.

The majority of CX teams that have deployed AI struggle with this.

Automating workflows without reliable data and well-designed business logic makes it almost impossible to know when to connect a customer with a live person. Even when the timing is right, customers must often share all of their information with the rep again.

To maintain trust and shorten time to resolution, CX teams must find a balance between automation and high-empathy, nuanced human interactions. Companies that are successful in doing this typically invest in three major areas, using technology designed specifically to tackle CX challenges:

• Automation – AI increases operational efficiency by automating entire repetitive tasks that don’t require empathy or difficult problem-solving. Approving small refunds, troubleshooting account issues, or answering common product questions with AI frees up CX teams for more complex interactions, routing the customer to a live agent the moment it’s needed. 
• Co-pilot technology – AI helps CX team members as they work, performing a broad range of actions that accelerate and simplify agent workflows before, during, and after customer interactions. Co-pilots reduce app switching and administrative tasks, lower time to resolution, and create a more consistent experience throughout the customer journey.
• Agent assist – AI is used specifically to help CX reps or agents have better customer interactions. During calls and chats, agents see valuable insights and real-time customer data they can use to resolve issues faster and provide personalized support. With agent assist, employees remain in control—they can choose not to act on suggestions or go off-script as needed.

Nextiva’s AI framework helps CX teams scale AI adoption without losing control. Learn more about how the platform enables automation, agent assist, and co-pilot capabilities in a personalized demo.