Flag

We stand with Ukraine and our team members from Ukraine. Here are ways you can help

Get exclusive access to thought-provoking articles, bonus podcast content, and cutting-edge whitepapers. Become a member of the UX Magazine community today!

Home ›› Artificial Intelligence ›› AI Agents in Customer Service: 24×7 Support Without Burnout

AI Agents in Customer Service: 24×7 Support Without Burnout

by Josh Tyson
6 min read
Share this post on
Tweet
Share
Post
Share
Email
Print

Save

As customer experience hits record lows and frontline service staff face rising burnout, companies are searching for smarter solutions. This article explores how agentic AI — intelligent, autonomous systems that guide both employees and customers — can revolutionize service delivery. Real-world examples from T-Mobile and a leading national retailer show how AI-led orchestration reduces friction, improves satisfaction on both sides of the counter, and drives measurable business gains. For organizations ready to embrace this shift, the rewards include happier teams, loyal customers, and a clear competitive edge.

According to last year’s US Customer Experience Index from Forrester, “Customer Experience (CX) quality among brands in the U.S. sits at an all-time low after declining for an unprecedented third year in a row.”1 The report points to several factors, among them an inability to provide a seamless customer and employee experience as well as an underwhelming rollout of chatbots.

This is exacerbated by burnout among customer service agents. “Instead of being able to focus on doing their jobs well, frontline employees have been forced into new roles,” Forbes contributor Blake Morgan points out. “They don’t just answer customer questions or sell products — now they are security guards, mask mandate enforcers, listening ears, and bearers of bad news. Across every industry, from retail to hospitality, employees are facing increasingly rude and unruly customers.”2

The two problems can feed into one another, as poorly executed chatbots fail to meet customer needs, increasing the frustrations they might unleash on a human agent who is also deeply unsatisfied. This article shows how properly leveraging agentic AI-led orchestration can decrease friction and pain on both sides of this frayed relationship by providing better CX, all day, every day.  

A prescription for leveraging agentic AI in customer service

Shortly after the announcement of COVID-19 lockdowns, T-Mobile, the third-largest wireless carrier in the United States, moved its Colorado Springs call center to an all-remote operation3. After equipping reps with the right tech — which was logistically challenging but not insurmountable — the wireless provider faced a more difficult task: supporting the team remotely. 

They made an impressive pivot, distributing printed guides, organizing virtual training sessions, and creating an IT war room for in-the-moment tech issues. However, all of this work uncovered a problem: there were never enough experienced call center leads to guide and mentor reps as they wrestled with unique customer problems.

Here’s how agentic AI solves this problem. A remote sales rep gets a call from a disgruntled customer about a purchase they made online. While the rep listens patiently, an AI agent processes the conversation in real time, prompting the rep with possible responses and solutions. This has become drastically easier using large language models (LLMs), which are proficient at summarizing unstructured data and extracting data points.

This is one of many agentic AI use cases that create a better experience on both sides of the interaction. For the agent, there’s no one-page guide to dig up, no virtual training to wait for, no war room to lean on. With all relevant company and customer-released data at its digital fingertips, a human agent can offer practical solutions tailored to each situation. The customer gets targeted help on a much shorter timeline.

Beyond alleviating the burden of an organization scrambling to find support channels for its team, agentic AI also makes higher-level training superfluous. If an AI agent is always at the ready to instruct and guide, employees won’t have to drudge through onsite training; they can simply walk through a quick tutorial guided by the agent and dive into work.

Customer service revitalized with AI agents

OneReach.ai recently worked with a leading national retailer in the U.S. that sought to effectively automate and manage phone calls in its physical locations. This required a new, comprehensive customer contact center, intelligent SMS strategies for customer-facing applications, and centralized customer communication channels for better analytics.

For this company — already recognized by Forbes as a Customer Experience All-Star — the first phase of agentic AI-led orchestration included the following components:

  • AI agents for managing retail-location phone calls
  • A brand new customer contact center, with human-in-the-loop (HITL) and live agent tools
  • SMS for all customer-facing applications, including intelligent outbound marketing campaigns.

Over the course of a year, the project included 350+ individual production releases across store locations nationwide. The initial pilot in 2022 led to a $3 million increase in gross profit, with a projected annual increase of $80 million. The agentic solutions created using OneReach.ai’s Generative Studio X (GSX) orchestration platform significantly reduced calls to stores by 47% and achieved a net promoter score (NPS)  of 65%.

Figure 1: Project results over the course of one year. Image source: OneReach.ai

By taking an agentic AI-led approach to automation, this company is in a position to expand its agent AI solutions, including internal service desk capabilities, enhancing point-of-sale options, enabling omnichannel text-to-pay, and integrating deeper with customer relationship management (CRM) applications to improve  CX even further.

Want to learn more about agentic AI? Download a free whitepaper from OneReach.ai.

Better employee experience leads to a better customer experience 

Often, organizations hoping to improve experiences for their customers can begin by improving workflows for employees. The advantages of this approach can be twofold. By creating meaningful automations that improve the quality of customer-facing jobs, you put employees in a better position to provide excellent service. There’s also a distinct advantage to beginning a journey with agentic AI without exposing customers to early deployments that will inevitably be less than optimal.

As Robb Wilson (OneReach.ai CEO) and Josh Tyson write in their bestselling book about agentic AI, Age of Invisible Machines: “By working directly with employees to automate specific tasks, you begin setting up the structure for future automation. You can continuously improve on automations with the people who understand the specific tasks, and, because these initial applications won’t be customer-facing, you can build, test, iterate, test, iterate, test, and deploy as frequently as needed. The better your organization becomes at rolling out successful skills and internal automations, the faster your ecosystem will evolve. “

For most organizations, customer experience and employee experience are deeply intertwined. The companies that find ways to create value out of this relationship will not only surge ahead of their competitors in terms of technology adoption, but they will also further expose just how fractured and inefficient non-agentic approaches to user experience have become. 

There is a clear return on investment (RoI) for adopting AI agents for customer service

Clearly, an appetite exists for the kind of enhanced CX that agentic AI can create for organizations. There are already examples like Lemonade (a lauded tech company that happens to sell insurance) that were built around the pursuit of agentic AI and are reaping the results.

“The biggest thing that pushed me to convert to Lemonade was the utterly charming AI chatbot,” Juliette van Winden wrote more than five years ago in a Medium post dedicated to their chatbot, Maya. “24/7, 365, day or night, Maya is there to answer any questions and guide the user through the sign-up process. Unlike the drag of signing up with other providers, it took me a total of two minutes to walk through all the steps with Maya… What intrigued me the most is that it didn’t feel like I was chatting with a bot. Maya is funny and charismatic, which made the exchange feel authentic.”4

Being a young, tech-first company put fewer hurdles in Lemonade’s path, but established enterprises can’t expect to sit out the race toward the adoption of agentic AI and survive. As Gartner has predicted, “By 2029, agentic AI will autonomously resolve 80% of common customer service issues without human intervention.”5

According to Rick Parrish, VP and research director at Forrester, while organizations will struggle with the scale of change required to truly put customers at the center of their operations, “It’s worth it… our research finds that firms that are customer-obsessed grow revenue, profit, and customer loyalty faster than their competitors.”

  1. 1Forrester’s 2024 US Customer Experience Index: Brands’ CX Quality Is At An All-Time Low
  2. 2Customer-Facing Employees Are Burned Out: Here’s What To Do About It, Forbes
  3. 3T-Mobile moved 860-employee call center to remote work in four days, The Denver Gazette
  4. 4Love At First Chat, With Lemonade’s AI Chatbot Maya, Medium
  5. 5Gartner Predicts Agentic AI Will Autonomously Resolve 80% of Common Customer Service Issues Without Human Intervention by 2029

The article originally appeared on OneReach.ai.

Featured image courtesy: Pawel Czerwinski.

post authorJosh Tyson

Josh Tyson
Josh Tyson is the co-author of the first bestselling book about conversational AI, Age of Invisible Machines. He is also the Director of Creative Content at OneReach.ai and co-host of both the Invisible Machines and N9K podcasts. His writing has appeared in numerous publications over the years, including Chicago Reader, Fast Company, FLAUNT, The New York Times, Observer, SLAP, Stop Smiling, Thrasher, and Westword. 

Tweet
Share
Post
Share
Email
Print
Ideas In Brief
  • The article explains how agentic AI can improve both customer and employee experiences by reducing service friction and alleviating staff burnout.
  • It highlights real-world cases, such as T-Mobile and a major retailer, where AI agents enhanced operational efficiency, customer satisfaction, and profitability.
  • The piece argues that companies embracing AI-led orchestration early will gain a competitive edge, while those resisting risk falling behind in customer service quality and innovation.

Related Articles

Design systems were meant to streamline design and boost creativity — so why do they often do the opposite?

Article by Itai Vonshak
The Broken Promises of Design Systems: Why Following the Rules Won’t Get You to Great Products
  • The article questions whether design systems really help create better products.
  • It explains how they often limit creativity, are hard to maintain, and don’t scale well.
  • It suggests we need more flexible, AI-powered tools to support great design.
Share:The Broken Promises of Design Systems: Why Following the Rules Won’t Get You to Great Products
3 min read

If we can automate a 787, why not an entire company? Discover how conversational AI and intelligent ecosystems are reshaping the future of work.

Article by Robb Wilson
You Can Automate a 787 — You Can Automate a Company
  • The article explores how automating a plane cockpit led to deeper insights about business automation.
  • It shows how conversational AI and agent-based systems can reduce cognitive load and improve decision-making.
  • It argues that organizations need intelligent ecosystems — not just tools like ChatGPT — to thrive in the age of automation.
Share:You Can Automate a 787 — You Can Automate a Company
8 min read

Unlock the future of AI with open, modular systems that power hyperautomation. Discover how orchestrating LLMs and AI agents leads to smarter, scalable innovation.

Article by Robb Wilson, Josh Tyson
Orchestrating LLMs, AI Agents, and Other Generative Tools
  • The article explores how conversation connects LLMs, AI agents, and generative tools in business automation.
  • It stresses the need for open, modular systems over relying on single vendors for scalability and innovation.
  • The article highlights the drawbacks of isolated LLMs and emphasizes interconnected systems for effective AI-driven workflows.
  • It encourages embracing the complexity of AI ecosystems to enable flexibility, iteration, and hyperautomation.
Share:Orchestrating LLMs, AI Agents, and Other Generative Tools
5 min read

Join the UX Magazine community!

Stay informed with exclusive content on the intersection of UX, AI agents, and agentic automation—essential reading for future-focused professionals.

Hello!

You're officially a member of the UX Magazine Community.
We're excited to have you with us!

Thank you!

To begin viewing member content, please verify your email.

Tell us about you. Enroll in the course.

    This website uses cookies to ensure you get the best experience on our website. Check our privacy policy and