– By Raghu Ravinutala, CEO & Co-founder, Yellow.ai
Artificial Intelligence, today, has become a global mainstream technology with its use-cases permeating across industries, more so in the customer-facing industries. We have seen CIOs and transformation leaders accelerate their AI adoption and critically depend on it to effectively manage the changing demands of customers since the pandemic. It has become a pivotal pillar that is shaping CX strategies of enterprises in order to create differentiated and fulfilling experiences for customers across multiple touchpoints.
An important piece in this puzzle of delivering improved CX amid such dynamic situations has been developing an optimised contact centre automation strategy. Enterprises are deploying Dynamic AI agents that not only offer quick and around-the-clock support but also result in higher cost efficiencies. It would not be wrong to say that AI has the potential to absolutely revamp the traditional contact centre setup as we know it.
However, the move towards AI-powered contact centres has raised the inevitable question- While AI is indispensable but is it enough to drive contact centre operations without human touch?
The truth is, AI cannot completely replace human interactions but it is an assistive technology that can facilitate and enhance it. According to Forrester, enterprises that have blended AI with human agents report that their customer service efforts are more effective at improving both customer satisfaction (61%), agent satisfaction (69%) and agent productivity (66%). Simply put, Dynamic AI agents offload simple, repetitive, monotonous tasks from human agents. This means that bringing in AI does not displace or dispirit existing customer service agents.
Let’s focus on how contact centres can tap the collaborative intelligence of the Human-AI nexus to unlock greater business value.
Seamless handoff to human agents
Dynamic AI agents act as assistants to human agents. Through Yellow.ai’s Dynamic AI Agents we have noticed a 60 percent reduction in call deflection that frees up the human agent’s time to focus on only the complex, high-sentiment conversations. While it is true Dynamic AI agents can easily address routine engagements with customers, sometimes they are not able to resolve queries that need human intervention. For instance, Dynamic AI agents can detect crucial situations that might involve customers at risk of churning or high-value transactions and immediately involve human agents in the conversation. In addition to this, they provide the agent with the background of conversation through collected information, thereby, saving the customer from having to repeat themselves. Yellow.ai’s Dynamic AI Agents also help human agents to converse with customers in the latter’s preferred language by supporting auto-translation of 100+ languages, providing personalised and improved experiences.
Real-time analytics for human agent augmentation
According to Gartner, by 2027, 45% of agent-assisted interactions will use real-time analytics to improve business and customer outcomes. Dynamic AI agents will play a key role in enabling this. These AI powered virtual assistants help enhance human agents’ performance, empowering them to constantly improve efficiency and productivity through real-time data analytics. They facilitate decoding of large amounts of customer information into accessible and actionable data. Essentially, they help human agents understand the customer’s history, give an overview of similar issues that other customers might have faced and respond in the most effective way. For instance, Dynamic AI agents can provide live call guidance where speech analysis is utilised to analyze phone conversations between the human agent and customer, helping with accurate context-based responses and quicker resolutions.
Continuous Self-learning of Dynamic AI Agents
Powered by Natural Language Understanding (NLU) and Machine Learning, Dynamic AI agents have the capability to continuously self-learn from the available knowledge base. For instance, by analyzing the vast repository of calls and transcripts of customer interactions with human agents, Dynamic AI agents get a deeper understanding of vocabulary and speech nuances used by customers when they are disgruntled or when they are happy. With each interaction, they upgrade themselves in terms of customer interaction, data churning, and generating responses for queries. This cycle of learning enables Dynamic AI agents to deliver a more accurate and uber-personalised experience to customers, across channels and at scale.
Gartner states that AI innovations will drive contact center agent automation, resulting in an 8% agent workload reduction by 2024, up from a 1% agent workload reduction in 2020. But it will never be about just AI or just humans- the way forward is to look at the best of both worlds. As such, enterprises will have to carefully evaluate the synergy between AI and human modalities, especially with customer service agents working in a hybrid work model — and how blending them together can deliver a robust end-to-end experience for customers.
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Disclaimer: Content Produced by ET Edge
