Take on any CX challenge with Pipeline+ Subscribe today.

Revolutionizing Customer Service

Revolutionizing Customer Service

Revolutionizing Customer Service

Is Generative AI/ChatGPT set to transform the contact center industry?

As the world becomes increasingly digital, the use of artificial intelligence (AI) is rapidly transforming the way businesses interact with their customers.

AI has established itself as a key technology to allow customers to engage with organizations through voicebots and chatbots to quickly solve problems, gain access to specialists, and significantly improve productivity for the organizations that have embraced it.

AI is evolving at an incredibly fast pace. It was initially applied to voice and chatbots with the goal of fully or partially automating interactions. More recently, AI has started to be used to support contact center agents (customer service advisors) with suggested knowledge and next best actions but has been expensive to deploy with a less tangible ROI.

...the new wave of Generative AI technology promises to further accelerate AI’s ability by automatically generating content...

However, we fully expect the technology to rapidly take hold in the coming years as the cost to run and deploy it decreases, its performance improves, and its use cases mature.

Tapping Into the Data

Since its emergence, a main challenge of scaling AI-powered technology has been the time and effort involved in interpreting what the customer is asking and then constructing the required dialog and generating a suitable response: either to the customer or in support of a colleague.

However, the new wave of Generative AI technology promises to further accelerate AI’s ability by automatically generating content and responses from large data sets.

One example of this is ChatGPT, a large language model (LLM) trained by OpenAI that has the potential to revolutionize the contact center industry by providing more efficient and effective customer service.

...the technology should be used in conjunction with human customer service advisors...

In this article, we will explore the impact of Generative AI on the contact center, how it works, and its effect on customer service advisors. We will discuss the benefits and challenges of implementing the technology in a contact center, and the ways in which it can improve customer service while also addressing concerns about the role of human advisors.

Generative AI Benefits and Challenges

As contact centers strive to improve the customer experience (CX), many are turning to AI to help them achieve this goal. While Generative AI offers many potential benefits for contact centers, it also poses some challenges that must be addressed to ensure its effective use.

Generative AI solutions, such as ChatGPT, Google’s Bard, Salesforce’s Einstein, and potentially Microsoft’s Copilot technology, has the potential to significantly improve the efficiency and effectiveness of contact centers, leading to better CXs and efficiency savings.

However, it’s important to note that the technology should be used in conjunction with human customer service advisors to provide the best possible CXs, rather than at the expense of human advisors.

Benefits of Generative AI in the Contact Center:

  • Improved Efficiency. The technology can handle a large volume of customer inquiries simultaneously and provide immediate responses, which can help to reduce wait times and improve the overall efficiency of the contact center. This can lead to improved customer satisfaction, as customers are able to get the help they need quickly and easily.
  • Increased Availability. Generative AI can operate 24/7, providing customers with assistance outside of normal business hours. This can increase the availability of the contact center and improve customer satisfaction, as customers are able to get help whenever they need it.
  • Cost Savings. The technology can automate routine tasks, freeing up human advisors to handle more complex inquiries. Additionally, Generative AI can provide consistent responses to customer inquiries, regardless of the time of day or the particular advisor handling the inquiry. This can help to improve the overall quality of customer interactions and increase customer satisfaction.
  • Personalized Responses. Generative AI can provide personalized responses based on a customer’s specific needs and preferences, which can help to improve the overall CX. This can lead to increased customer loyalty and higher levels of customer satisfaction.
  • Enhanced Advisor Support. By using the technology to handle routine customer inquiries, contact center advisors can instead be realigned and retrained to handle more complex, time-consuming interactions where a human advisor is more suitable.
  • Improved Analytics. Generative AI can provide valuable insights into customer behavior and preferences. Contact centers can use this information to improve their services and tailor their responses to better meet customer needs.

Challenges of Generative AI in the Contact Center:

  • Accuracy. While Generative AI can provide immediate responses to customer inquiries, the quality of its responses can vary depending on the quality of the input data and the specific use case. This can lead to inaccuracies in responses, which can negatively impact the CX and reduce customer satisfaction.
  • Technical Complexity. Implementing Generative AI in the contact center can be technically complex, requiring expertise in natural language processing (NLP) and machine learning. This can lead to additional costs associated with implementation, maintenance, and training.
  • Privacy and Security. Generative AI may be handling sensitive customer information, and as such, privacy and security must be a top priority. Contact centers must ensure that proper security measures are in place to protect customer data and prevent unauthorized access.
  • Integration with Existing Systems. The technology must be integrated with existing contact center systems to provide a seamless CX. This can be challenging and may require significant resources to ensure that the integration is done correctly.

Agent/Advisor Training, Understanding

Contact center advisors would likely need to be trained to use and understand the capabilities of Generative AI should it be introduced into the contact center environment.

LLMs, such as ChatGPT, can process natural language queries and generate responses to various types of inquiries. However, the quality of its responses can vary depending on the quality of the input data and the specific use case.

Therefore, training contact center advisors to effectively use Generative AI and understand its capabilities and weaknesses can help to ensure that the system is used appropriately and efficiently. And that the responses provided are accurate and helpful to customers.

This training could include education on how to interact with the system, how to interpret its responses, and how to use the system to improve customer interactions and outcomes. It could also include ongoing training to keep advisors up to date with the latest features and capabilities of the technology.

ChatGPT Versus Other Chat Technologies

ChatGPT is the Generative AI technology that captured the imagination of the public and the wider business and technology communities, including the customer service industry: and so we’ll focus this section on this technology.

The technology itself is a new capability in the chatbot market, but it has already shown promising results when compared to other chat technologies such as live chat, virtual agents, and chatbots.

...ChatGPT technology can be integrated with other contact center systems, such as CRM systems, to provide a seamless CX.

It has demonstrated high levels of speed in generating responses to customer inquiries, thanks to its advanced NLP and machine learning capabilities. This makes it a strong competitor against rule-based chatbots, which are limited by predefined rules and may struggle to provide accurate responses to complex inquiries.

ChatGPT also has the ability to provide personalized responses to customer inquiries based on their specific needs and preferences. This gives it an edge over more generic chatbots that may provide standard responses to all customers.

In terms of complexity, ChatGPT can handle more complex inquiries than some other chat technologies, such as decision tree-based chatbots. Tree-based chatbots are limited to a predetermined set of options and cannot handle unexpected or complex queries.

On a genuinely exciting note, the ChatGPT technology can be integrated with other contact center systems, such as CRM systems, to provide a seamless CX. This makes it a strong competitor against standalone chatbots that may not be able to integrate with other systems.

However, the technology can be time-consuming and resource-intensive to develop and maintain, as it requires expertise in NLP and machine learning. This can make it a more expensive option compared to other chat technologies, such as rule-based chatbots that may be easier to develop and maintain.

Overall, ChatGPT offers several advantages over other chat technologies in terms of accuracy, personalization, complexity, and integration but will require more resources to develop and maintain than some other chat technologies. Contact centers should carefully evaluate their specific needs and resources before choosing the best chat technology for their organization.

How Ready is Generative AI?

Generative AI is a powerful technology that can provide significant benefits to contact centers. But its suitability and readiness for use depend on a variety of factors, including the specific use case, the quality of the input data, and the level of technical expertise available within the contact center.

While Generative AI has been shown to be effective in generating responses to a variety of inquiries, it is not a one-size-fits-all solution for every contact center. The technology must be customized and trained to meet the specific needs of the contact center and its customers.

Additionally, implementing Generative AI in the contact center can be technically complex, requiring expertise in NLP and machine learning. Contact centers must have the necessary technical expertise or access to it to ensure that the system is implemented and maintained correctly.

Another consideration is the potential impact on the CX. Generative AI solutions must be able to provide accurate and helpful responses to customer inquiries. If the quality of its responses is not up to par, it can negatively affect the CX and reduce customer satisfaction.

A False Dawn or New Hope?

While there are challenges associated with using ChatGPT and other Generative AI models in the contact center, the benefits it offers can make it a valuable tool for contact centers looking to improve their operations and meet the evolving needs of their customers.

To ensure its effective use, contact centers must carefully consider the challenges and take steps to address them, while also taking advantage of the benefits that Generative AI can offer.

We’re fascinated by the emergence of new technologies that can help deliver CX value. Since the emergence of Generative AI capability we’ve been in constant dialog internally and with our diverse partner network to understand its capability and what it could bring to our industry.

It is clear that Generative AI is a promising technology, but its suitability and readiness for use depend on several factors, including the specific use case, the quality of input data, and the level of technical expertise available.

Stuart Dorman

Stuart Dorman

In his role as Chief Innovation Officer, Stuart Dorman is responsible for developing Sabio’s AI, cloud, and additional emerging technology portfolio. Stuart is engrained in Sabio’s innovation culture, helping organizations think differently about how they engineer customer experiences through technology, innovation, and disruptive thinking.

Contact author

x

Most Read

Beyond ChatGPT Webinar
Upland 20231115
Cloud Racers
Beyond ChatGPT Webinar
Verint CX Automation
DSS General Campaign