Broadband and telecom companies going into 2026 without customer care AI tools risk being left behind. No longer experimental, AI has quickly become critical operational infrastructure for 2026.
Customer expectations have never been higher. Nearly two-thirds of customers expect a response within 10 minutes of making a customer service inquiry. If you fail to meet their expectations, most customers won’t give you a second chance. Research shows that 96% of customers will leave after a single bad service experience. How can your call center expect to keep up?
This is where AI call center technology has become no longer a nice-to-have, but a must-have for brands looking to meet the demands of modern-day customers. It’s not only about using AI to automate processes, but also about augmenting agent performance. For example, it’s estimated that using AI in customer service could lead to as much as a 45% increase in productivity.
Legacy contact center systems without AI technology just can’t meet the demands of the modern customer. Yet it’s not enough to have tools like conversational AI chatbots. You also need to use them strategically to transform your contact center into a revenue driver. Below, we outline several AI use cases in contact centers and tips for using it to provide reliable, scalable tech support.
Use case one: Give agents faster answers with AI-powered knowledge surfacing
It's estimated that employees spend nearly 20% of their workweek looking for information or a colleague who can help with a specific task. This can increase average handle time (AHT), potentially impacting the customer experience.
Additionally, it means customers may have to call back numerous times to resolve a technical issue, which can negatively impact your first-call resolution rate (FCR) and other critical metrics.
AI tools such as Ozmo Answers API can interpret the customer's intent and surface the relevant information instantly to help the agent provide fast and efficient troubleshooting. This saves the agent the trouble of searching through disparate knowledge systems and creates a more streamlined support experience for the customer.
Additionally, AI's ability to surface validated instructions, provide device flows and app guidance makes it an effective tool for contact center agent onboarding. The onboarding process is a critical period in the employee experience. If agents can't quickly and easily find the information they need to do their jobs, they're likely to become frustrated and eventually leave. Research shows that employees who have a negative onboarding experience are twice as likely to start looking for a new job as compared to their peers.
Leveraging AI to help surface critical knowledge when it's needed most isn't just good for your customers; it's also good for your agents. This, in turn, means it can also be beneficial for your business.
Use case two: Use conversational AI that actually resolves technical issues
Many chatbots still fall short when customers need help. One study found that 63% of customers said chatbots didn't resolve their issue, and almost 80% ended up transferring to a human agent. This can cause a lot of frustration for customers, especially in telecom and broadband.
Telecom and broadband issues such as device activation, account provisioning, WiFi setup or software are known as "lifestyle problems." It can severely hinder your customers ' daily lives. For example, if a bakery owner's WiFi goes down, they're unable to receive online orders or process credit card payments. A sales rep working from home can't join a Zoom call with a prospective customer. These customers need fast and accurate answers to get back up and running quickly.
The next generation of conversational AI can bridge this gap using large language models (LLMs). With LLMs, these chatbots can better understand intent, identify the right troubleshooting path and guide the customer through it without passing them to an agent. AI technology is increasingly able to handle more complex service issues. In fact, Gartner predicts that by 2029, AI will resolve eight out of 10 service requests. Not only does this create the potential for cost savings, but it also makes it easier for your company to rapidly scale tech support to meet rising demands.
Use case three: Support agents in real time with intelligent coaching
Successful contact center agents are those who can solve problems quickly and effectively. New agents often need time to ramp up, which means more experienced agents have to step away from their caseloads to offer support. This increases average handle time and may create a poor onboarding experience, which increases the likelihood of agent turnover.
Real-time AI coaching gives agents the support they need to thrive in their roles. Instead of waiting for a supervisor or searching a knowledge base, agents receive prompts that help them resolve technical issues faster and more accurately.
This advantage is well-documented in research. A joint study by Stanford and MIT found that customer service agents using generative AI saw a 14% increase in productivity, with the most significant gains among junior agents.
For telecom and broadband teams, where agents often handle issues related to device setup, service disruptions or app configuration, this support reduces the risk of errors and streamlines the support experience. AI can surface the correct steps, flag missing details and highlight compliance needs as the call unfolds. This leads to fewer mistakes and better first-contact resolution.
It also improves the onboarding process. When agents have reliable guidance built into their workflows, they gain confidence faster and are less likely to experience burnout. That improves employee engagement and enhances agent performance.
How to choose the right AI call center technology for your business
Not all AI customer care tools are created equal. So, how can you select the right one for your business needs? You’ll want to look for a truly comprehensive customer support solution that uses AI to augment your contact center agents’ performance.
For example, it’s important to look for features such as a self-service knowledge base that allows both customers and agents to find the answers they need fast. To ensure that your agents and customers have access to reliable information and streamline the customer experience, you should look for software that dynamically updates.
You’ll also want to consider ease of implementation. How soon can your business get up and running with the tool? Sometimes it’s as easy as pasting a few lines of code into your website, while other options may take longer or require more technical implementation.
Additionally, most telecom and broadband companies serve customers who speak a variety of languages. To ensure all customers can enjoy the same high-quality AI-driven tech support, focus on vendors that offer multilingual support options. Offering AI self-service tools to customers in their preferred language can minimize frustration and streamline the customer experience, which in turn can help boost key contact center metrics.
Once you’ve narrowed down your options, schedule a product demo. This is your chance to see the product in action, and ultimately decide which one best fits your business needs. Be sure to ask good questions to evaluate which one aligns most strongly with your company’s goals.
AI is now a core component of strong CX strategies
AI has become essential to modern contact center operations. As customer expectations rise, support teams need tools that help them move faster and deliver accurate answers across every channel and touchpoint. The examples above show how AI can strengthen both agent-assisted and customer self-serve experiences, reducing friction and providing customers with the fast, reliable support they expect in 2026.
Quality AI customer service requires an accurate, trusted self-service knowledge base. Whether an agent is troubleshooting a device setup or a customer is working through an interactive tutorial, the accuracy of the guidance they receive shapes the outcome. When AI is grounded in verified information, it delivers better customer service and tech support that can scale with your business.
As contact centers plan for the year ahead, telecom and broadband companies that invest in AI tools will be better positioned to meet rising demand. AI not only helps you keep pace with customer needs, but it also builds a support experience that can grow with your business.
Are you looking for more information on how to use AI in your customer service strategy? Download our free e-book to learn more about the role of AI in the customer experience, best practices and future trends.
