Navigating Customer Support Challenges with AI: Real-world Applications and Success Stories

By Machielle Thomas

Customer support comes with its fair share of challenges. Customers are pickier and more discerning than ever before so, to achieve true customer service success, many businesses are looking for tech-driven solutions. 

Artificial intelligence (AI) has become integral to navigating and excelling in customer support. Between digital assistants like chatbots and automations, as a couple of examples, customer support is more streamlined, less fussy, and pulls from a wealth of existing business information to get the customer’s problem solved as soon as possible. Even if cases where manual or live agent help is necessary, generative AI can triage queries and prioritize them by urgency. 

Yet, sometimes, you need to see it to believe. 

Generative AI for customer support, according to Ryan Kow, head of customer experience at Skillshare, is an, “extremely powerful tool that I think we haven’t even taken the tip of the iceberg off of. It’s already been a huge player for the Skillshare support team, and it’s constantly being iterated on.”

Ahead, we’ll unpack how some companies have successfully overcome customer support challenges with Forethought AI’s generative AI, and how the technology has improved service quality and boosted customer satisfaction with AI-powered solutions. 

Get inspired here to enhance your support operations.

How generative artificial intelligence (AI) helps customer service

First, let’s take a look at a few key ways generative AI has impacted customer support and customer support representatives. 

1. Nuanced human-like assistance.
Generative AI has been so useful for providing a natural and human language texture to customer support elements such as chatbots. Instead of using pre-written or pre-programmed content, generative AI has the ability to be in conversation with a customer and pull relevant information to get to a resolution.

2. Getting information faster. 

If a virtual assistant needs product information or policy information for a customer, some common examples in customer queries, generative AI is equipped to run through the information a business provides that software and get what a customer needs in seconds. 

3. Task management for agents.  

When a live agent is needed for support calls or interactions, generative AI, too, plays a role in helping automate necessary tasks that might be needed later on. This may include chat transcripts, providing summaries on queries, and product or service recommendations useful for the customer. 

Customer support challenges with AI: Case studies and examples 

Now, let’s dig into some companies who have used generative AI to improve their customer support and enhanced customer experiences for the better. 


Crypto company Abra needed to ensure customers had the best support in the industry, and decided to focus on the self-service aspect of customer support. Here, they used Forethought AI’s chat widget to ensure the right information was provided for customer questions.

“The best part about using Forethought is their partnership with Abra to create a better experience for our customers,” said Adelaida Nobles, Customer Experience Manager at Abra. “We can change things on the fly, and it’s live within minutes. With our team being smaller, it has made our lives exponentially easier.”


For the HR space, ensuring employees feel heard and seen, and belong, too, in their organizations is paramount. Achievers helps businesses reward, recognize their employees, among other useful resources like checking the pulse of a business. Yet, employees have other needs, too, that often have a seasonal flavor to them (i.e. new year, new password needed.)

Achievers implemented customer support automation with Forethought AI’s Solve and Triage. By using generative AI, customer experience and agent support improved to a 93% first contact resolution rate and a 44% deflection rate. 


Customer support will always need a human element to it. Generative AI works with live agents as stellar partners in an effort to get faster resolutions for customers. So when health company, iFit, needed to smooth out operational ineffectiveness, generative AI became the key. 

By using a chat widget, iFit could go through and solve common questions and queries with speed, saving agent time and effort on more complex issues. 

For ops manager Dustin Auman, Forethought’s generative AI “knows where the customer needs to go.” He continues: “It makes it quicker, easier, and more clear for customers to engage with us. You feel the difference with their AI–it’s been huge for me.”


Customer support isn’t a 9-5 gig. Many customers will need help at any point in the day, and that’s why self-service has become a huge and successful part of generative AI. For Kickfin, a payment software, ensuring customers could get the support they needed while also being able to pay their employees was crucial. Larisa Thomas, vice-president of operations at Kickfin, put it this way: “I wanted to be able to find a way to provide 24-hour customer service without needing to have an agent on 24 hours a day. Part of my goal of being able to scale customer support and provide support to a non-traditional customer base.” 

Using Solve empowered customers to get solutions to their queries fast, by pulling from the existing large language model the technology is trained on, and Kickfin’s own resources. 


Response times can be a drag on any customer support organization. For larger, global companies, being able to respond to customer issues with speed is paramount to success. Lime is trying to build its own global, ethically-mind and sustainable transportation company and that comes with local and regional nuances where customers might need help.

To support this goal and scale as a company, generative AI had to become part of the solution. A customer’s query is sent to the right agent in the language they prefer, as well as ensuring that those specificities on location can be answered with ease. Lime is also enabled with AI technology to prioritize, triage, and predict queries based on severity levels. 


Customers crave consistent interactions across the board. No customer wants to hear that their experience on a support call or chat was different (and, we hope not, worse!) than someone else’s. Upwork decided this was important to focus on for their vast freelancer pool who may need assistance getting onboarded with the company. 

“Our teams work remotely all over the world and are loosely connected. Ensuring they have the same access to the same answers, are trained consistently, and deliver accurate responses is so important,” says Brandon Savage, Upwork’s vice-president of experience and trust. 

Generative AI helped Upwork’s agents accurately solve issues and surface relevant information the customer needed. 

There are many different challenges that can occur in customer support, and often there aren’t enough hours or live agents that can truly handle all of them. With generative AI tools like Forethought AI’s Solve, or triaging functionality to route tickets and issues where they need to be, agents and companies at large are able to more efficiently and consistently support their customers the best way possible. 

Dive in.

Interested in generative AI for customer support? Check out this guide to learn about the 3 key pillars you need to get started.

Get your copy
Decor Half Circle Orange
Call to action decor Call to action decor