Tag-Team Champions of Customer Service


The Gist

  • AI-Human collaboration. Humans and AI combine strengths for improved customer experience.
  • AI in customer service. AI augments tasks but human involvement is still crucial.
  • Organizational importance. Success with AI relies on organizational changes, not just technology.

The rapid evolution of artificial intelligence in recent months has many organizations looking to incorporate the technologies into a number of business processes, including customer service. 

The answer is generally an AI-human collaboration — known as collaborative intelligence — where the organization taps what each is best at. That means the social skills, creativity and leadership abilities of human agents, with the speed, quantitative capabilities and scalability of AI. By combining efforts, humans and AI applications can enhance the strengths of the other for a hoped-for improved customer experience.

“Customer service operations — as in other enterprise areas — seek to improve efficiencies, lower costs, and improve results,” explained Bern Elliot, distinguished vice president and analyst at research firm Gartner Inc. “The types of benefits from such collaborations seek to improve user experiences, insights, accuracy, timeliness, costs, and revenues.”

This Is Not Your Father’s Artificial Intelligence

While artificial intelligence has been around for decades, the technology is becoming much more robust, Elliot stressed. As a result, he expects it to be a critical part of advanced customer service operations at many organizations if they aren’t already.

“There is general awareness of the value of combining advanced AI methods into customer service operations with human activities, sometimes called AI augmentation of agent actions and tasks,” Elliot explained. 

As AI becomes more capable, it will enable the automation of a growing number of tasks, Elliot said. It can currently assist humans in many aspects of customer service and engagement, especially in the area of decision-making or by finding and providing information quickly to a customer seeking assistance. 

But because customer service is such a delicate and critical area to get right, there are many situations where a person’s direct involvement is still needed, and AI serves in a largely supporting role. 

“There will be many opportunities for AI solutions to focus on assisting, or augmenting, or collaborating with individuals to assist them in their tasks,” Elliot explained. 

Still, overall, Elliot said adoption varies greatly at this time.

“The maturity of AI usage overall in an enterprise is often a good predictor for the adoption of AI augmented agent capabilities,” Elliot said. 

Related Article: How Human Insight Enhances AI-Driven Marketing Personalization

How Organizations Are Using AI and LLMs in Customer Service

Elliot cites the following as some common examples of how organizations are incorporating large language models into customer service functions:

  • Using LLMs to generate alternative phrase suggestions for people writing responses.
  • Using LLMs to summarize conversation with a customer, and then the agent can review and accept the summary.
  • Using LLMs to collect and summarize information about previous interactions with a customer and prepare a summary for an agent before the agent gets on the call.

Organizations that have made significant strides in these areas have no doubt learned that the most significant factors to success are organizational, not technological, Elliot stressed.

“Yes, the technology has to be there. But that can be done in a POC or MVP, and then scaled as needed,” Elliot said. “However, in order to implement the AI-human collaboration, agent actions and processes must often change. Sometimes business process must also change, to properly leverage the new functions. Those changes can be the greater challenge.”

Related Article: Most Consumers: Don’t Use AI to Personalize My Experience


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