Impact of Generative AI on Customer Success Software

Impact of Generative AI on Customer Success Software

Abigail Spear 3 min

Generative AI is an unstoppable force, rapidly transforming the world around us as we know it. If you’re still reeling from its ability to process unstructured data, like text, did you know the technology can reason? That’s right, we now have computer systems that can reason. Let that sink in a moment.

Every industry is feeling the implications of generative AI, as the technology poses a truly revolutionary breakthrough in a decades-long effort to develop deep learning models. According to new research from McKinsey & Company, “All of us are at the beginning of a journey to understand generative AI’s power, reach, and capabilities.” This is especially true in the world of enterprise software development.

Gainsight product experts, Karl Rumelhart, President, Products, Technology, and Global Operations, Jake Ellis, Principal Product Evangelist, and Shantan Reddy, Senior Product Manager sat down for a roundtable discussion on the impacts of generative AI on business software, and Customer Success (CS) in particular.

Here are the highlights from their conversation.

A Convergence of Human and Digital CS Powered by Data

We already know the future of the Customer Success industry is digital. Generative AI is a catalyst for this digital transformation, and we’ve just started to understand its full potential.

According to Rumelhart, “Digital techniques and human techniques have started to intertwine. I think this is going to accelerate a lot because of AI.”

Rumelhart continues, “What’s going to happen is that those self-service touches, the digital engagements, are going to get way better because they’re going to be mediated through AI. So that will make those digital tools more powerful, and frankly, more like interacting with a person on the other side,” says Rumelhart.

As self-service tools improve with AI, users will never have to leave the product to troubleshoot an issue in the product, for instance. Your CS team will also become more efficient. Or as Rumelhart puts it, “These tools are going to make your human beings more effective, more efficient, and more able to scale themselves to serve clients.”

This convergence of human-led and digital tactics is powered by platforms like Gainsight that are able to fully leverage customer data throughout the entire lifecycle. According to Rumelhart, “This is the foundation for the successful use of AI in Customer Success: In many ways, it’s as much the cleanliness as the quantity [of data], but both are important.”

Rumelhart continues, “I think we’re going to see an acceleration and a doubling down on this trend towards really rich, robust data platforms that will undergird Customer Success, and then the AI that will help drive it.”

Users Expect a Seamless End-to-End Customer Journey

From self-service to email to Community, in-app engagements, and more, Customer Success Managers (CSMs) have a variety of channels to reach customers during their adoption journey. But CSMs still struggle to deliver the right message at the right time on the right platform. What if AI could do the heavy lifting, leaving CSMs more time for strategic tasks?

Regarding the tasks traditionally handled by CSMs, Reddy says, “I expect that AI and the product itself will start to do a lot of those things. And then, through that, the expectation for Customer Success would be to give an extremely premium, seamless experience to our customers. And I see the world moving in that direction. [Customers] don’t want to go to three places: One for learning the product, one for raising a Support ticket, and another for more nuanced Customer Success. They want a very seamless experience from Sales through their entire journey, preferably with a single point of contact and a single destination for getting things done.”

That’s exactly what we’re building with the Gainsight platform, and how we envision the future of our industry.

“There are such compounding benefits when you’re on a singular platform,” says Ellis.

AI Is Simplifying the Nature of UX Design

Every day, generative AI becomes more sophisticated, yet simpler and more human to interact with. In turn, people are starting to trust it more—and expect more from it.

Reddy predicts that generative AI will change the nature of UX design, making all products drastically simpler to use, while AI provides a personalized, guided experience.

“It’s no longer you trying to understand the software, it’s the software trying to understand you,” says Reddy. “People are beginning to trust AI a lot more, and they are wanting AI to get things done … the boundaries of software and products and interfaces are going to go away and, and companies that are able to own outcomes and get them done without any boundaries of product or use case or person, they will thrive. And smaller point solutions will become more or less irrelevant.”

As software users navigate digital experiences powered by generative AI, they’ll expect systems to be so smart they can predict the next step in their journey—and seamlessly guide them there.

“This is the beginning of the realization of the sci-fi dream that has been promised with artificial intelligence,” says Reddy. “It’s going to completely change how software works, how we work, and how technology is delivered to end users.”

Learn More About Generative AI for CS

The future has arrived. Learn more about Gainsight’s products and our latest Generative AI capabilities.

Abigail Spear 3 min

Impact of Generative AI on Customer Success Software


Examining generative AI's role in reshaping customer success with advanced engagement and predictive insights


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