Is Generative AI Takeover of Customer Service Operations Inevitable?

Generative AI is a new technology with the potential to revolutionize customer service. But is customer service ideally suited for generative AI applications? And are the suitable applications currently accessible? These are the questions we'll explore in this blog post.

Is Generative AI Takeover of Customer Service Operations Inevitable?
Customer Service Operations: Generative AI or Humans?

Imagine a world where your frustration with customer service calls is a thing of the past. We've all been there: stuck on the phone for what seems like an eternity, navigating a maze of automated options and being passed from one agent to the next. But fear not, you are not alone. And there is hope on the horizon.

The promise of Generative AI replacing traditional customer operations is generating a lot of excitement. In fact, Mckinsey has published an article titled "The Economic Potential of Generative AI: The Next Productivity Revolution", which states that applying generative AI to customer operations will increase productivity by 30 to 45 percent. Therefore, let's delve into whether customer service operations are ideally suited for Generative AI applications and whether the suitable applications are currently accessible.

What is Customer Service?

Let's begin by understanding the basic requirements of Customer Service. Customer Service is helping solve customer problems, and these include
- Teaching customers how to use products
- Answering questions and resolving issues
- Providing support over common platforms including phone, email, text and online chat.

Skill Sets Of a Customer Service Representative

Skill sets of a Customer Service representative as defined by linkedin for hiring the right person.

The description of the skillsets largely falls under the requirements for the job across most customer service roles. From a business perspective, humans will not provide the same consistent support as each individual has different personalities and approaches. The skill sets and the costs related to customer-related operations broadly fall into these categories

  • Product Knowledge :
    Human customer service can be helpful when you need to troubleshoot a complex issue or have a question that requires specialized knowledge. However, the knowledge of human customer representatives can vary, and you may sometimes get someone who doesn't know much about the product you're calling about.

    Generative AI can be used to create customer service applications that can provide accurate and timely answers to customer queries. These applications can be trained to understand everything about a product, including its features, functionality, and troubleshooting tips. They can also learn from historical data to better understand the possible queries that customers may have. This means you can get the answers you need quickly and accurately, even if you get a representative who doesn't know much about the product
  • Cost:
    Human customer service can incur significant costs due to salaries, benefits, and training for representatives. Furthermore, the availability of human customer service is limited to the hours when representatives are accessible.

    On the other hand, generative AI applications offer a cost-effective alternative for customer service. They can operate 24/7, reducing labor expenses. Additionally, they provide multilingual support, enabling companies to expand their reach economically. These AI applications also automate common tasks, freeing up human representatives to handle more complex issues. In summary, generative AI offers round-the-clock, multilingual, and automated assistance, providing cost savings for businesses.
  • Communication:
    Generative AI's communication skills excel in consistency and precision, providing a reliable baseline. It's a steady, monotone source of information, ideal for scenarios demanding accuracy and predictability. However, generative AI lacks the human touch and empathy, unable to read emotional nuances.

    In contrast, human customer service agents offer warmth and personal connection, making them indispensable for emotionally-driven interactions. In summary, generative AI's communication skills are better for reliability, while human agents shine in providing empathy and understanding. The choice depends on the specific needs and context of the interaction, but most of the time, one is interested in getting their immediate problem solved, and if AI can do it, I would go with AI than a human.
  • Availability:
    Picture this: It's 2 AM, and you're in the midst of an online shopping dilemma. Desperate for help, you grab your phone, hoping that somewhere, a customer service hero is on standby. Unfortunately, the reality often falls short, and finding 24/7 human customer service is a rare feat.

    Now, enter the world of generative AI applications, the unwavering sidekick of customer support. This virtual assistant knows no concept of 'rest.' It stands at the ready 24/7, like a loyal companion, always there to lend a hand, day or night. No more enduring endless hold times or tedious elevator music – just immediate, 'round-the-clock assistance, right at your fingertips.
  • Languages:
    Customer service often falls short due to the limitations of human agents who can't match generative AI's multilingual capabilities. We humans may know a couple of languages, but are proficient usually at most in one or two. This means the customer service operations need too many people for the same job for the language requirement.

    In contrast, generative AI seamlessly handles multiple languages, eliminating language barriers. It can instantly translate and assist customers in their preferred language, enhancing satisfaction while reducing costs associated with maintaining multilingual support teams. It empowers businesses to deliver exceptional service to a diverse global audience, a feat human agents simply can't replicate to the same extent.

Generative AI Applications for Customer Service

The foundation for creating an AI-driven customer service hub exists in the form of generative AI tools and applications designed for various customer service functions. These functions include chat interactions, intelligent email responses, and phone conversations.
Notable examples such as OpenAI, Google's BARD, Meta's open-source Llama2, and Anthropic's Claude 2 possess capabilities that can address diverse facets of customer service operations. These capabilities encompass answering customer inquiries, generating personalized replies, resolving intricate issues, offering multilingual support, and handling repetitive tasks like scheduling, refunds, and order status updates. In the future, we can anticipate more specialized applications tailored to specific customer service needs.


Generative AI is on the brink of revolutionizing customer service. It can enhance the customer experience, reduce operational costs, and free up human agents for more intricate responsibilities.

Also, the customer service industry is under pressure to meet its key customer service priorities according to Gartner. Businesses actively seek ways to optimize their operations for efficiency and revenue growth. Generative AI offers a promising avenue to achieve these objectives by automating tasks, enhancing the customer journey, and enabling human agents to tackle complex challenges.

While integrating generative AI into customer service is still in its early stages, it's gaining momentum. As generative AI continue to advance, they will become invaluable tools for businesses aiming to elevate customer service quality. One thing is certain, in the not too distant future the customer service operations as we know of today will be transformed.