AI in customer support should be about more than efficiency. Yes, you can save money by augmenting human effort with automation—but the same could be said of interactive voice response systems, a notorious case of efficiency at the expense of customer experience. With human-AI symbiosis, where humans and AI work together in complementary ways, we can improve efficiency while creating an even better customer experience. And that’s where things get interesting.
In this article, I’ll talk about four ways human-AI symbiosis can help companies deliver better results for customers while improving the bottom line.
1. Agentic AI handles customer issues end-to-end
Experiences with early chatbots left many customers wary. In a recent survey, 89% of respondents said that a company should disclose if an agent is real or AI. This view is often based on the assumption that automated customer service will be worse. Agentic has now flipped that script. The latest AI agents can handle many questions faster than a human, and at least as accurately. Agentic AI can go beyond providing information by making decisions and taking action to solve a customer’s issue.
For example, a Grammarly customer who wanted to reverse an inadvertent subscription renewal recently contacted customer service. The company’s agentic AI chatbot, built by Forethought, confirmed his eligibility for a refund and issued the payment via PayPal in under two minutes. “Funny enough, just for that, I might subscribe again,” the customer posted to LinkedIn.
Traditionally, AI and automation have best handled the simplest customer problems–and most requests fall into this category. But with agentic AI, chatbots can solve more complex problems or provide assistance that helps human agents solve them faster. We’re rapidly approaching a point where AI will earn customers’ trust and we’ll see less frequent demands to escalate issues to a human.
2. Agentic AI hands off complex issues to human agents
Another superpower of agentic AI? It knows when it doesn’t have the answer, or can’t help someone. Generative AI chatbots are known for hallucinating, or making things up. Agentic AI can admit when it doesn’t have the answer, and escalate a customer’s issue to a human agent who can help. Agentic AI can also understand context and sentiment, recognize when a customer is getting frustrated, and communicate those insights to a human.
That handoff could mean transferring the chat to the best-qualified human agent, or having someone follow up via phone or email. Over time, this process will become more fluid and seamless. For example, an AI agent might bring a human in for an especially complex step in a resolution process, then step back in to complete the interaction, freeing the human agent to focus on another customer request.
Human-AI symbiosis means that customers’ issues get resolved more efficiently, without sacrificing the high-touch human assistance needed for certain situations. This is a win for everyone: customers get answers faster, while human agents get to step up from monotonous tasks to solve more interesting problems.
3. Humans supervise agentic AI
In many cases, the decision to escalate is clear and binary—but not always. For a human agent, wavering certainty can be a cue to wave over a manager to listen in. The same can be true for an AI agent. As it works through a customer case, the AI agent can continually assess its own confidence on a numerical index. When the score drops below a certain level, it can alert a human agent to review the interaction, provide guidance behind the scenes, or step in as needed. Similarly, human managers can monitor confidence scores across the entire fleet of AI agents, zero in on those that start to lag, and decide where intervention may be required.
For customers, this added level of oversight can be a welcome change from earlier chatbots that got stuck in loops, relied on decision trees, failed to recognize rising frustration, or persisted in providing unhelpful solutions instead of taking action to solve problems.
4. AI agents help human agents
AI copilots have become ubiquitous in all types of applications—and for good reason. Even if an AI agent can’t handle a particular task on its own, it can still provide valuable assistance for the human agent who steps in. AI can monitor the interaction for cues to the types of resources the agent might need and offer them proactively. For example: “I know you’re talking about password resets. I’ll pull up that policy in your browser so you have it handy,” or “This customer is currently on the premium plan. This would be their cost to upgrade to the enterprise plan, which would provide the added functionality they’re asking about.”
In this version of human-AI symbiosis, the AI agent can serve as a steadfast teammate to the human agent, anticipating and meeting all kinds of needs. If English isn’t your first language or you’re struggling to articulate an explanation, the AI agent can offer some wording. If an interaction starts going off the rails, it can offer suggestions to get it back on track.
Beyond individual customer cases, AI agents can also offer managers insight into trends across thousands or millions of conversations. Is a team doing particularly well that we should gather best practices from? Are there product features or bugs that are generating an especially high volume of cases? Are there topics we should address more fully in our customer-facing library? In a busy contact center, it can be hard for human agents to consistently capture and convey this kind of information in the flow of their work. For AI agents, knowledge capture can be hard-wired.
As human-AI symbiosis continues to evolve, we’ll see better efficiency for agents, better experiences for customers, and better economics for businesses. Everyone can have a more delightful day with no trade-offs needed—just pure win-win-win.
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