According to Gartner, agentic AI will automate 80 percent of customer service queries by 2028.
Additionally, the analyst predicts that it will reduce costs by 30 percent.
Summarizing these findings, Daniel O’Sullivan, Senior Director and Analyst in the Gartner Customer Service & Support Practice, said:
“Agentic AI has emerged as a game-changer for customer service, paving the way for autonomous and low-effort customer experiences.”
However, vendor definitions of agentic AI vary, causing confusion around the implications of the technology in the contact center. That’s a problem.
As such, let's consider a definitive definition and, from there, the technology's true potential across the contact center space beyond conversation automation alone.
What Is Agentic AI?
Agentic AI is not a new-fangled term for a contact center chatbot or virtual agent.
Instead, agentic AI represents a new category of technology.
An “AI agent” can ingest communications and data, understand the context and reason to make decisions, adapt, and automate. It learns from every interaction to take autonomous action with minimal human involvement.
Various departments across the enterprise may deploy AI agents to automate specific processes.
Think beyond customer service for a moment. Marketing teams could deploy AI agents that interpret successful past projects to generate new campaign briefs, create relevant audience segments, and build much of the campaign themselves.
Now, think about commerce. Brands could deploy AI agents on their websites as personal shoppers to listen to customer needs and deliver personalized recommendations.
There are many more possibilities spanning different functions. But, the bottom line is: this is not purely a customer service technology; it's enterprise-wide.
That said, there are many fascinating agentic AI use cases in customer service beyond conversation automation alone.
How Will Agentic AI Transform Customer Service?
The most common use case for AI agents in the contact center is as a replacement for previous-generation chatbots.
These required the developer to predefine the types of conversations the bot would likely encounter and instruct the AI on what tasks to perform based on those categories.
The rigidity of these applications meant that the interaction broke down when customers said anything unexpected.
Thankfully, agentic AI has changed that. As Ram Rajagopalan, Head of AI Product at Zoom CX, said: “We’re moving away from scripted, intent-based models and replacing them with a system based on skills and prompts.
“Instead of programming exact decision trees, you can set broad objectives and allow the AI to reason, adapt, and act autonomously based on real-time context.”
Ultimately, that enables more nuanced conversations, with AI agents sifting through knowledge bases and data sets to answer customer queries.
These AI agents may also reason about how sure they are of surfacing the correct answer and escalate when they are not certain. That’s a critical guardrail within a powerful agentic AI use case.
Alongside transforming virtual agents, there are many other use cases, which Ram highlighted, including AI agents that deliver proactive customer service.
Here, an AI agent can detect signals from systems that indicate a customer issue. They may then fix the problem and communicate their actions with the customer.
Consider a telco company. Let’s say it has a network outage. An AI agent could spot this, check the CRM to isolate impacted customers, and proactively warn them of the issue before they call in. The agent can then offer updates until the system is restored.
Other possible examples of AI agents in customer service include those that automate post-contact processes, simulate conversations for training, and generate new knowledge content.
Yet, businesses won’t necessarily have to configure these AI agents themselves. Over time, CCaaS providers will embed preconfigured agents into their applications, making it much easier for enterprises to realize their benefits.
Contact centers may, however, start noticing customers using AI agents to reach out to them.
In the future, these may live on smartphones, with consumers asking Bixby, Google Assistant, or Siri to contact customer support for them. Even more spooky, they may take outbound calls on their behalf…