Generative AI: powering the next generation of customer service for communications providers

Predictive AI has been around for years and is already being widely used to help service agents and field technicians figure out next best actions, product recommendations, efficient scheduling, and more. However, the emergence of generative AI is truly a game changer, especially when it comes to customer service.

Generative AI capabilities enable service providers to deliver personalization and drive efficiency at an enormous scale. It’s what allows employees to draft hundreds of personalized emails at once, field technicians to efficiently generate service reports, and service agents to summarize calls in an instant.

Generative AI also has the ability to ingest unstructured data and use it to drive results. This is useful in telecommunications, where data often takes different forms. It’s what could potentially create differentiated experiences in things like quote generation, billing, report summation, personalized call scripts, and more.

Generative AI and predictive AI work together to maximize opportunity at every touchpoint. For example, field agents might use predictive AI to help suggest additional products and services based on personalized recommendations and then use generative AI to prepare a quote at the click of a button.

AI enables agents and technicians to deliver the individualized treatment customers have come to expect. Field technicians and service agents can come to the table fully informed with a 360-degree view of the customer. They can quickly and easily pull up that customer’s profile and get up to date on recent incidents, past issues, billing, and service history. For example, a field technician can know at a glance whether the issue at hand is new or recurring. If recurring, they can look at what fixes have already been tried. It also enables field agents to look at each issue in the context of the customer’s history, allowing them to assess whether previous issues and/or previously applied solutions may be contributing to the current problem. Once the issue has been resolved, the technician can review the customer’s products/services and get instant, personalized, AI-generated recommendations for other adjacent products they might be interested in. This results in better, more personalized, and more productive service.

Generative AI’s ability to make sense out of unstructured data also enables field technicians and service agents to analyze all the information at hand and generate an explanation tailored to the particular customer and/or situation at hand. This is especially useful in helping to manage things like billing inquiries (a subject that makes up the majority of a service provider’s incoming calls). Even though basic billing consists of structured information, the answer to a question like “Why is my bill so high?” must also take into account unstructured data like rate plan entitlements, contract entitlements, vast quantities of billing records across multiple systems, and any past history and conversations that the customer has had with the company.

Generative AI can help service agents get to the heart of the matter immediately. It ingests the totality of the data (structured and unstructured) and then generates a personalized recommendation in a matter of seconds. The technology can also help service providers identify customers who are regularly exceeding their rate plans and proactively reach out to suggest a different plan that might better suit their needs. Or, because it is actually of value to have some customers have to pay overage, they could use AI to figure out which of those customers are most vulnerable and highest value, and then offer them a more suitable plan. This allows them to minimize risk and make better, more-nuanced market decisions.

Whether a field service visit, call-center conversation, or online interaction, a great service experience is defined by a few things: Was the issue fixed? Was it done so as quickly as possible? Was the customer satisfied? And, did the agent or technician understand the customer’s needs without forcing them to tell their story twice?

AI can help streamline every facet of service center interactions. It can look at which technicians have worked on specific issues in the past, understand how successful they’ve been at solving them, and identify what areas they know best, ensuring that the best available field technician is assigned to each individual service call. It can also help in diagnostic situations by analyzing data like case history, past issues, and fixes for similar issues to help agents get to the problem (and the solution) more efficiently. With the call center, AI can help ease the flow of calls and give agents the insight and information they need to help people more efficiently and effectively. For example, service providers could proactively and automatically send customers a text informing them that their service is down and give an estimated time of restoration. This would cut down the number of calls. Or, for situations in which customers do call in, agents can use AI to identify other internet options, like a higher bandwidth package or switching to fiber that may ameliorate the customer’s issue.

AI also boosts productivity, enabling technicians and service agents to move from case to case in less time. Things like AI-generated pre- and post-visit work summaries, proactive monitoring of networks and equipment, automatically scheduled service appointments, and AI-generated instructions specifying required tools, relevant technicians, and estimated time to resolution takes manual work off employees’ plates and allows them to focus on more valuable, complex, and fulfilling work.

Success depends on ensuring that every opportunity is fully realized. AI makes it possible to turn regular interactions into revenue-generating experiences. This is especially true when it comes to the role of the field service technician. Field service technician appointments take place in a customer’s home (or business). Service providers can leverage this type of face-to-face opportunity to drive business. Most techs don’t want to be salespeople—pitching products and services is not necessarily in their wheelhouse. But, being able to rely on AI to recommend personalized offers, sales scripts, or even prebuild a quote and order might help address that reticence, allowing providers to enjoy more cross sell/upsell successes.

Human and AI collaboration makes for a better customer service experience by shifting an agent’s focus from resolving simple issues to engaging in more complex interactions that have the potential to generate revenue.

These technologies have myriad potential applications in the service center environment. Generative AI can act as a virtual assistant, helping agents to automatically generate personalized emails or text message responses to customers. It can also be used to generate articles and create knowledge databases that both agents and customers can surface. It does this by ingesting data like case notes, service calls, incidents, and other documentation and then using that data to create the content of the article or database in question. These capabilities boost the efficiency of knowledge creation. This not only benefits the knowledge database, it can also make things like self-service portals and chatbots more valuable by giving them more, higher-quality information to draw from.

Generative AI capabilities are also enabling the creation of smarter, more human-like chatbots with the ability to better understand, anticipate, and respond to customer issues.

AI is a powerful tool. However, using it safely encompasses the understanding that human oversight is paramount in order to maintain trust and integrity. Without it, service providers risk common AI issues—such as hallucinations, toxicity, and bias. If left unsolved, these issues have the potential to erode customer experience as well as overall trust in the organization. Service providers committed to data integrity, privacy, and security need to ensure that they engage a technology partner with a secure trust layer that enables their employees to benefit from generative AI without compromising customer data.

Communications service providers are up against a host of challenges. From complex systems and increasing customer expectations to decreasing margins and a need to differentiate themselves in a crowded market, communications service providers need tools and technology that will help them contend with an ever-evolving industry.

Harnessing the power of both predictive and generative AI technologies can help service providers redefine their approach to customer service operations so they are meeting as well as exceeding customer expectations. This ability to unlock productivity, increase personalization, and deliver deep insights at scale will make it possible for providers to turn service engagements into wide-scale opportunities for growth.