– By Raghu Ravinutala, CEO and Co-Founder, Yellow.ai

Artificial intelligence, today, has become a global consumer technology with its use cases spreading across all industries, more so in customer-facing industries. We’ve seen CIOs and transformation leaders accelerate their adoption of AI and critically depend on it to effectively manage changing customer demands since the pandemic. It has become a critical pillar that shapes companies’ CX strategies to create differentiated and fulfilling experiences for customers across multiple touchpoints.

An important piece of this puzzle to deliver improved CX in such dynamic situations was the development of an optimized contact center automation strategy. Businesses are deploying Dynamic AI agents that not only provide fast, round-the-clock support, but also lead to higher cost savings. It wouldn’t be wrong to say that AI has the potential to completely revamp the traditional contact center setup as we know it.

However, the move towards AI-powered contact centers has raised the inevitable question: while AI is indispensable, is it sufficient to drive contact center operations without human touch?

The truth is that AI cannot completely replace human interactions, but it is an assistive technology that can facilitate and improve them. According to Forrester, companies that have combined AI with human agents report that their customer service efforts are more effective at improving both customer satisfaction (61%), agent satisfaction (69%) and employee productivity. officers (66%). Simply put, Dynamic AI agents offload simple, repetitive and monotonous tasks from human agents. This means that the introduction of AI does not displace or discourage existing customer service agents.

Let’s focus on how contact centers can harness the collaborative intelligence of the human-AI nexus to unlock greater business value.

Transparent transfer to human agents

Dynamic AI agents act as assistants to human agents. Using Yellow.ai’s dynamic AI agents, we’ve seen a 60% reduction in call diversion, freeing up time for the human agent to focus solely on complex, high-emotion conversations. While Dynamic AI agents can easily handle routine customer engagements, sometimes they are unable to resolve queries that require human intervention. For example, Dynamic AI agents can detect crucial situations that could involve turnover risk customers or high value transactions and immediately engage human agents in the conversation. In addition to this, they provide the agent with the background of the conversation through the collected information, thus saving the customer from having to repeat himself. Yellow.ai’s Dynamic AI agents also help human agents converse with customers in their preferred language by supporting machine translation of over 100 languages, delivering personalized and enhanced 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 improve the performance of human agents, allowing them to constantly improve their efficiency and productivity through real-time data analysis. They make it easy to decode large amounts of customer information into accessible and actionable data. Essentially, they help human agents understand the customer’s history, provide insight into similar issues other customers may have faced, and respond in the most effective way. For example, Dynamic AI agents can provide live call guidance where speech analytics is used to analyze phone conversations between the human agent and the customer, resulting in accurate and contextual responses. faster resolutions.

Continuous self-learning of dynamic AI agents

Powered by natural language understanding (NLU) and machine learning, dynamic AI agents have the ability to continuously self-learn from the available knowledge base. For example, by analyzing the vast repository of calls and transcripts of customer interactions with human agents, dynamic AI agents gain a deeper understanding of the vocabulary and nuances of speech used by customers when they are unhappy. or when they are happy. With each interaction, they level up in terms of interacting with customers, processing data, and generating answers to queries. This learning cycle enables Dynamic AI agents to deliver a more accurate and ultra-personalized experience to customers, across all channels and at scale.

Gartner says AI innovations will drive contact center agent automation, resulting in an 8% reduction in agent workload by 2024, compared to a 1% reduction in agent workload. agent work in 2020. But it will never be AI-only or human-only. to watch the best of both worlds. As such, companies will need to carefully assess the synergy between AI and human modalities, especially with customer service agents working in a hybrid work model – and how combining them can deliver a robust end-to-end experience. to customers.

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Disclaimer: Content Produced by ET Edge

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