Ryan Falkenberg, CEO of CLEVVA takes a look at how AI agents are changing diagnostic and troubleshooting processes, and how consumer and enterprise-facing businesses can benefit from them.

Very few businesses today don’t have at least one core customer-facing piece of technology. Whether that’s an actual product, an app or even just e-commerce and customer service functionality on their website, all have become crucial to surviving and thriving in today’s business environment.

As critical as these pieces of technology have become, they also present new demands on a company’s support teams. No matter how well-built and easy-to-use a piece of tech is, support agents will have to regularly troubleshoot it for customers. And while some customers can pinpoint the exact issue they’ve encountered, others will simply say, “It’s not working.”

You might think that’s predominantly an issue for consumer-facing businesses, but it affects enterprise-facing organisations too. Let’s take a fuel supplier, for example. A petrol station owner might call the fuel supplier’s support centre because one of their pumps isn’t working. The pump may not be their product, but the fact that it is not working impacts their fuel sales. Yet only a few technical experts in the company would know what could be causing a blockage and what needs to be done to fix it. There’s a diagnostic process involved in determining the "why", and if that can’t be done over the phone, the supplier will need to send out one of their technicians. That inevitably involves a callout fee, with further fees involved if the problem turns out to not be in the technician's field of expertise.

Correctly diagnosing the root cause of the pump problem goes a long way to resolving it. It ensures that the right person, with the right parts and tools, is dispatched the first time around. But that’s not something most support agents are equipped to do. The chances of them having a full, or even working, knowledge of different models and makes of fuel pump are slim.

The same is true of consumer-facing products like smart TVs, or services like video streaming. Even if you are technologically inclined, you’ll know how frustrating it is trying to troubleshoot an elderly relative’s technological issues over the phone. And that’s someone who you love and, hopefully, have a lot of patience for. Now imagine being a contact centre agent trying to do that for a stranger, who’s taking all their frustration with the technology out on you. The net result is a poor customer experience and a poor employee experience. Nobody wins.

Troubleshooting is an inherently complex exercise and it requires expert-level capability. That’s where technologies such as AI Agents can be incredibly helpful. They can be trained to have the diagnostic conversations that human experts would have, and be skilled to then perform the actions required to fix the identified problem e.g. trigger a work order for a technician or update an account.

Importantly, the AI Agents can now have voice conversations with you. They understand what you are saying and can guide you through the right troubleshooting process to get the outcome you require. Think of them like human agents, only they operate digitally. And because they can have concurrent conversations, they can support hundreds of people at once. This means customers don’t need to wait to get their support query resolved. There is always an expert ready to help them.

Human contact centre agents can benefit too. Most of the high volume, rule-bound support queries can be handled by AI Agents, meaning they get more time to handle the more complex or emotionally demanding support calls. It takes the pressure off the clock, and allows richer more impactful support engagements. AI Agents can also offer staff real time support so they don’t need to be an expert in everything to offer effective support.

Historically, troubleshooting has been a complex and expensive exercise. By utilising technology effectively, however, it no longer has to be. Through the use of AI agents and other remote diagnostic tools, it’s possible to turn troubleshooting into something that is frictionless and which benefits all concerned parties.