Gartner: GenAI the next evolutionary step in customer service excellence.

Customer Service and Support Leaders Should Assess Generative AI Technology Options to Enhance Their Organization’s Function

Q&A with Uma Challa from Gartner Customer Service & Support Practice.

By 2026, investment in generative AI will lead to a 20% to 30% reduction of customer service and support agents, and will create new jobs to enable generative AI in customer service and support, according to Gartner.

Many organizations have already made headlines by drastically reducing or even eliminating their customer service employees and replacing them with generative AI-enabled chatbots.

However, when we talked with Uma Challa, Senior Director in the Gartner Customer Service & Support practice, he shared how this approach is unrealistic for many organizations – plus a short-sighted idea – as well as how leaders can better integrate generative AI into their operations.

Q: Will AI replace customer service representatives?

A: Not fully. While the latest advances in generative AI, including OpenAI’s ChatGPT and Google Bard, have propelled the technology forward, they can’t be compared to human agency.

The hype around workforce reduction needs to be quelled. As we stated earlier, Gartner predicts that investment in generative AI will lead to a 20-30% reduction in customer service and support agents by 2026, but not a wholesale shuttering of the live customer service function. Here’s why:

  1. Generative AI is still not advanced enough to demonstrate human-like agency. It can be applied effectively to act as an assistant to service agents, automate recurring tasks, resolve low-complexity issues or perform specific tasks the generative AI model is trained on, but it cannot take on the complex issues that require human judgment to resolve.

  2. Customer service organizations can’t wake up one day and decide to implement generative AI. Depending on the type of investment, it could take a few months or even a few years to adopt the technology depending on many factors such as access, language model type and risk management, which brings us to the third reason.

  3. The use of generative AI comes with significant risks, such as exposure of sensitive data, inaccuracy (hallucinations) and bias in responses, which can be damaging to the brand and will prevent broader application of the technology near-term.

Q: If not rep replacement, what are the more likely use cases for generative AI in customer service?

A: The use of generative AI in customer service and support is not limited to virtual agents. It has many other applications, including the ability to generate content, provide content utility functions, such as text summarization, formatting and translations, and other special purpose use cases, such as agent assistance or case summarization.

Initially, leaders should invest in generative AI capabilities that help reps better serve the customer. More specifically, the generative AI use cases with the highest ROI are ones that provide reps with context around the customer, product and interaction, as well as guidance on how to best solve the customer's issue. In fact, our recent research shows that reps whose technology provides them with context and guidance tend to perform better than those without these capabilities.

Consider the ability of generative AI to generate next best actions tailored to the customer’s specific circumstance or automating regular rep activities – like call note summarization – to free up rep time to focus more on the customer interaction.

By initially focusing on improving the agent experience and productivity internally, service and support leaders can reap the benefits of generative AI while managing the risks.

Q: Gartner research shows reps were already worried that advances in technology will eliminate their jobs, and we imagine generative AI makes this fear worse. How can customer service and support leaders deal with employees’ concerns?

A: It’s reasonable for customer service employees to be worried about the impact of AI. This worry has an impact - our research shows that when customer service reps worry that technology will replace them, attrition actually gets worse. In fact, reps who are very worried about being replaced by technology are 84% more likely to be actively looking for a new job than those who aren’t worried.

To assuage fears and stem attrition, customers service and support leaders must set realistic expectations for generative AI’s impact on reps, and transparently communicate the following:

  • Plans of the organization to adopt with focus on how generative AI can help reps to be more productive. Detail how the technology will act as an assistant to the agent.
  • The impact generative AI adoption will have on certain agent activities, how the role will change as a result, and the new opportunities that will be created to enable generative AI.
  • Their plans to future-proof the workforce, which include upskilling and reskilling current employees’ skill sets so the reps can thrive amid the new technology adoption.