In an era of technology revolutionizing various aspects of business operations, customer service stands at the forefront of the transformation. As businesses strive to streamline processes, provide exceptional support, and deliver personalized experiences, the emergence of large language model (LLM) chatbots offers new possibilities. LLM chatbots, which are designed to understand and generate text-based responses that mimic human conversation, hold the potential to augment customer service capabilities and elevate the overall customer experience.
However, rather than replacing human agents, businesses can harness the power of LLMs in collaboration with human agents. By working in tandem, companies can leverage the unique strengths of both AI and human operators, ensuring that customer service remains a blend of technological innovation and human touch.
The rise of advanced chatbots sparks inquiries about the relevance of humans
While integrating chatbots into customer service is nothing new, recent advancements in LLM technology and the rise of tools like ChatGPT have introduced a new level of sophistication to automated customer support. As a result, the implementation of chatbots is predicted to grow from just 2% in 2022 to over 15% by 2026.
However, while these models can provide automated support and deliver detailed and relevant responses, they still lack emotional intelligence and are occasionally prone to ‘hallucinations,’ offering wholly inaccurate answers. Therefore it remains essential that a human agent remains in the mix. LLMs are better suited to complement human representatives, assisting them in their communications with customers.
Incorporating LLMs, without losing the human touchpoint
As some customer inquiries are simple to solve but can be time-consuming, and others require a more lengthy investigation and careful explanation, it’s essential to have various communication tools available to meet different customers’ needs.
While live human agents can provide empathy and handle more complex queries, LLM-based chatbots can respond to a wide range of topics and generate responses automatically. This makes them a valuable tool for improving speed-of-response.
And customers are not overlooking the value of AI-based chatbots either; 73% believe there is potential for a positive impact on CX. Notably, the effects of AI-based chatbots extend beyond the initial experience. One study indicates that they can foster customer loyalty and retention by providing helpful information during future interactions.
Businesses are just beginning to discover the various ways to use LLM chatbots to enhance human communication:
- Providing real-time information to agents: Chatbots can be integrated with various data sources and organizational systems to retrieve up-to-date information. This enables agents to access relevant data, such as order status, inventory availability, or account details, swiftly and efficiently during customer interactions, just by asking a chatbot.
- Assisting with language support: AI chatbots have the potential to be a game-changing tool to break down language barriers and facilitate communication with customers from diverse language backgrounds. Their multilingual capabilities enable seamless interactions, ensuring language differences do not hinder the support process, and allowing companies to cater to a broader customer base.
- First point of contact: Chatbots can perform initial assessments of customers, gathering information, providing necessary triage, and then intelligently routing customer inquiries to the appropriate human agent based on their expertise or skill set.
- Preparing responses and suggestions: Companies can use LLMs to summarize customer conversations, presenting information in a digestible format that helps agents swiftly grasp the context of inquiries and offer streamlined support. Additionally, chatbots excel at preparing agent responses by providing ready-to-use templates and relevant information. This assistance enables agents to deliver consistent, high-quality answers, saving time and improving response accuracy.
- Follow-up assistance: AI-integrated communication apps can provide great administrative assistance following an interaction with a customer. In addition to providing a summary of communication, they can create a list of action points from the summary for the human agent and draft a follow-up email to send to the customer.
Through these means, live agents can monitor chatbot output ensuring relevance and quality, while at the same benefitting from AI assistance. Both human agents and smart chatbots participate in each customer interaction. Agents continue to provide a human touchpoint, with chatbots serving as digital assistants to minimize communication barriers and facilitate faster access to information.
The synergy of human expertise and AI: Driving continuous learning and improvement
Each time humans take in new information, they learn something—the same applies to AI too. But sharing learnings between agents and chatbots is what will help the partnership truly soar.
Proper training of an LLM involves extensive and precise datasets—it’s the difference between bias or performance errors and operational success. That’s why keeping the agent as the main point of contact works as the perfect guardrail. Chatbots can suggest responses and save agents time, while the agent approves and sends them.
Incorporating this human-in-the-loop approach prevents the chatbot from deviating from its intended purpose. For instance, if a customer asks a chatbot a specific question related to a product or the whereabouts of a delivery, a purely generic response that doesn’t answer the question is bound to generate customer frustration. With the human in control of what generated responses are delivered, companies can mitigate the risks associated with AI decision-making.
It’s also important to recognize the vast potential for learning and improvement for ChatGPT-powered chatbots, as they can extract insights from interactions with customers and human agents. The more agents analyze successful resolutions and train the tools with agent-customer conversations, the more chatbots can provide precise and relevant suggestions independently, ultimately strengthening human agents’ customer service.
When incorporating AI chatbots into customer service, achieving a balance is essential: harnessing chatbots’ ability to swiftly sift through vast amounts of information and analyze content while leveraging human intelligence. By utilizing the strengths of both humans and machines, and embracing the synergy between them, companies can improve customer experiences and increase operational efficiency.
About the Author
Nate MacLeitch is Founder and CEO of QuickBlox. Nate is a seasoned business professional with over 20 years of experience in various industries, including telecom, media, software, and technology. He started his career as a foreign Trade Representative for the State of California and has held various leadership positions, including Head of Sales at WIN Plc (Cisco), COO at Twistbox Entertainment, and CEO of QuickBlox. In addition to his work experience, Nate is also a seasoned advisor, having mentored and invested in startups like Springboard Mobile and TechStars. He’s a graduate of the University of California, Davis and The London School of Economics and Political Science.
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