AI in Customer Experience: Benefits, Examples, and Best Practices | Talkdesk
AI in customer experience: Benefits, examples, and best practices
By Celia Cerdeira
May 4, 2026
09:24 min read
Strong customer experience is the competitive edge that sets organizations apart in an era of instant expectations.
By 2028, 68% of all customer service and support interactions with technology vendors are predicted to be handled by agentic AI. Across the customer journey, AI is helping teams work more efficiently while giving customers exactly what they need, when they need it. From always-on self-service to virtual assistants designed to support human agents, AI is reshaping customer experience.
In this article, we’ll break down 10 practical ways AI is improving customer experience, the benefits it delivers to customers and CX teams, real-world examples, and best practices for putting AI to work.
What is AI in customer experience?
AI in customer experience makes interactions smoother, smarter, and more intuitive. Beyond speed, AI makes each interaction feel relevant and personal. CX teams are increasingly adopting agentic AI—systems that can understand goals, take action, and collaborate with other AI agents to complete tasks. With multi-agent orchestration, these systems work together behind the scenes to automate processes, assist human agents in real time, and deliver tailored experiences at scale.
As companies integrate AI more deeply into their strategies, they’re finding that it does more than improve satisfaction. It helps strengthen customer loyalty and retention, pairing personalization with operational efficiency to deliver exceptional customer experiences.
Why is AI in customer experience important?
Today’s customers expect seamless, end-to-end journeys—not fragmented interactions. They want fast responses, personalized support, and consistent service across every touchpoint. Meeting those expectations at scale is challenging for CX teams as interaction volumes grow and needs become more complex. AI helps close that gap.
Agentic AI gives organizations the ability to understand customer needs in real time, analyze large amounts of data, and make decisions quickly. It also improves operations by helping teams spot issues earlier and streamline their workflows. While adopting new technology can seem daunting, organizations that test, learn, and implement AI thoughtfully often see meaningful gains in customer satisfaction, loyalty, and trust.
10 ways AI makes customer experience better.
AI is redefining how organizations support and engage customers. Here are ten ways it’s creating the biggest impact.
1. Offer customer self-service.
AI-powered self-service options transform how organizations handle routine inquiries by making it faster and easier for customers to get help on their own—anytime, day or night. Agentic AI systems can understand customer questions, locate the right information, and deliver clear responses instantly. Instead of waiting in a queue, customers can access accurate answers pulled directly from a company’s knowledge base, creating a smoother, more convenient experience.
2. Provide automated agent assistance during customer interactions.
AI empowers human agents by providing real-time assistance during customer interactions. AI-powered live agent assistance tools offer valuable support through features like automated transcription, sentiment analysis, and suggested responses. These tools analyze conversations in real time, detecting key issues while giving agents insights to respond more accurately and efficiently.
3. Scale operations more easily.
AI makes it simpler to scale customer operations by adding new agents with specific skills as needed—without retraining the existing system. These AI agents can complete real tasks across service, sales, and support, working alongside human teams and effectively expanding the workforce during peak periods.
4. Give customers the fastest possible path to a resolution.
By intelligently routing queries, AI delivers quick, effective resolutions to meet customer needs. For instance, when a customer submits a question, AI-powered systems can instantly analyze the inquiry to determine its complexity.
5. Analyze data to make customer service even more efficient.
The best-performing organizations don’t just handle customer issues; they learn from them. By analyzing customer data, companies can uncover patterns, identify areas for improvement, and fine-tune future interactions. Here are a few critical KPIs every organization should monitor to help improve customer experience.
- First contact resolution (FCR).
- Customer effort score (CES).
- Net promoter score (NPS).
- Average handle time (AHT).
- Customer satisfaction score (CSAT).
6. Engage customers across the channels they prefer.
Customers expect flexibility, and an omnichannel experience allows them to connect in their preferred channel—whether through phone, email, social media, live chat, or text.
7. Improve knowledge management processes.
Strong knowledge management is essential to delivering fast, accurate customer support. When information is easy to find and consistently maintained, agents can resolve issues with confidence and customers get clearer answers with far less effort.
8. Improve employee collaboration.
AI customer experience platforms enhance employee collaboration by seamlessly connecting teams across channels.
9. Prevent customers from repeating themselves.
Customers don’t like repeating information, particularly if they’re already frustrated with their product or support experience. AI solutions address this by summarizing conversations at the end of each interaction.
10. Learn how customers feel about a brand.
To truly understand why customers are leaving angry or frustrated, organizations can now go beyond traditional sentiment analysis and identify emotional cues to uncover how customers are feeling and why they feel that way.
How does AI improve the customer experience? Three case studies.
Michaels: Transforming agent experience to improve customer satisfaction.
With more than 1,200 stores, Michaels is one of North America’s largest arts and crafts retailers.
Serta Simmons Bedding: Making agents even more effective.
Leading mattress manufacturer, Serta Simmons Bedding, improved agent efficiency and productivity with AI-powered solutions from Talkdesk.
Municipal Credit Union: Empowering customers to solve their own problems.
Serving over 600,000 members across 15 branch locations, Municipal Credit Union (MCU) has transformed financial services support with AI-driven self-service tools.
Improve your customer experience with Talkdesk CXA.
AI is now a core part of delivering standout customer experiences, and organizations that embrace automation are seeing faster resolutions, stronger loyalty, and more efficient operations. Talkdesk Customer Experience Automation (CXA) takes this a step further by helping enterprises automate entire customer journeys, not just individual tasks.
Discover how Talkdesk Customer Experience Automation (CXA) can help your organization improve customer satisfaction.
AI in customer experience FAQs.
What is AI for customer experience?
AI for customer experience uses advanced technologies—like large language models, agentic AI, semantic search, and machine learning—to understand customer needs and make interactions smoother.
What are the benefits of AI in customer experience?
AI enhances customer experience by enabling faster, more accurate resolution through intelligent agents that can complete tasks, coordinate workflows, and provide always-on support.
Why is AI for CX so important?
AI is essential for CX because customers expect fast, seamless, and personalized experiences that are difficult for teams to deliver manually at scale.
What future AI trends should CX experts monitor?
CX experts should watch for advancements in agentic AI and multi-agent orchestration, which will automate more complex, cross-system tasks.
Is AI safe and reliable to use in customer experience?
Responsible AI-powered CX platforms use safeguards like auditability, data controls, human oversight, and accuracy monitoring to ensure AI behaves reliably.