14-05-2025
How tech companies can use AI to strengthen customer experience
It's no secret that many technology companies have changed the way they approach customer experience and success. With the end of ZIRP (zero interest rate policy) in 2022 and 2023, budgets are much tighter today than they were in the recent past. This has led some organizations to cut corners, often at the expense of customer experience and success. In fact, Forrester's Customer Experience (CX) Index reached an all-time low in 2024—a sign of how serious the situation has become.
Even as leaders grapple with these pressures, the vast majority of tech companies continue to see the value in customer experience. ZenDesk, for example, has found that 90% of companies view customer experience as their company's main priority.
But, as leaders scramble to re-optimize customer success, one tool is frequently overlooked: AI. In this article, I'll share a few practical ways that technology companies should (and shouldn't) use AI tools to build a better customer experience that can help drive revenue and build deeper, more sustainable relationships with customers.
The end of ZIRP led some to claim that customer success in technology, especially SaaS, would drastically change, but these predictions have turned out to be seriously exaggerated. While some budgets have been cut, customer success remains vital for all technology companies, and many are now looking for cost-efficient ways to beef up customer success. In some cases, this can mean transferring low-risk, redundant work to digital tools like AI, which allows staff to focus on higher-impact tasks.
At SaaS companies, for example, customer success managers and specialists can sometimes spend hours a week combing through spreadsheets, querying technical or subject matter experts, or reading or summarizing customer communications. These are all areas where AI can have a clear and immediate impact with minimal risk.
Instead of spending substantial time perfecting customer presentations, customer success professionals can now use AI tools like Microsoft 365 Copilot or Google Gemini to quickly and easily elevate the look and content of their slide decks, which frees up time for higher-level tasks. Similarly, team members can use AI to summarize email threads and meetings, execute sentiment analysis on customer interactions, and use specialized AI agents to answer SME-level questions that might otherwise be difficult to answer.
These are all low-risk, low-effort, high-impact applications for AI in customer success. They're also cost-efficient, and allow people to focus on support tasks that are more likely to have a tangible impact on customer satisfaction and retention. Instead of spending time staring at a spreadsheet or sifting through a deck, your people can spend their time providing direct support to customers. This is something that we've had success with at AvePoint, as recently highlighted by Microsoft.
MANAGE RISKS TO MAXIMIZE BENEFITS
While AI can be transformative for customer success, it can also create new vulnerabilities and trigger unintended consequences when deployed without the proper guardrails or in the wrong scenarios.
Remember the chatbot that tried to sell a Chevy Tahoe for $1 (a transaction that the chatbot referred to as 'legally-binding')? While AI tools have applications in many different customer experience scenarios, this gaffe shows what can happen when AI is hastily deployed without proper controls. This technology has the potential to completely change and improve the customer experience, but it also has the potential to cause harm if implemented in the wrong scenarios.
Beyond that, AI also presents new data security issues that are specific to customer success. Consider, for example, what might happen if confidential communication with a customer is ingested by an LLM. This could lead to confidential information being repeated by the LLM, opening up your organization to significant legal and financial risks. That's why tech companies should use software that can identify sensitive information and categorize it based on its sensitivity, keeping it out of circulation while also ensuring that AI tools like chatbots provide more personalized, relevant recommendations for users.
It's also important to understand that customer-facing employees need guidance and training to help them use AI securely and efficiently, something I've written about in the past. This means that leaders need to set up robust training programs and implement software to secure and optimize AI data. Once they've done that, they can expect productivity boosts to follow.
THE CUSTOMER COMES FIRST—NO MATTER WHAT
Today, a world-class customer experience demands careful strategic investments. By deploying AI in the right workflows, technology companies can maintain strong customer relationships, ensuring both satisfaction and success in a post-ZIRP environment. At the end of the day, your customers are the lifeblood of your organization, so it's critical to get it right.
