There has been much chatter recently about Generative AI. So, let’s deep dive into it and discover how it can help contact centers.
Generative AI is a type of artificial intelligence (AI) that focuses on creating new content or output based on an understanding of data inputs and patterns, referred to as “prompts.” Unlike traditional AI systems that follow predefined rules and patterns, Generative AI uses deep learning algorithms to analyze existing data and generate new outputs that are not limited to existing data.
The outputs generated by Generative AI can be in various forms, including text, images, audio, and other types of media. This makes Generative AI a valuable tool for a wide range of applications, including content creation, product design, and customer service.
In the context of the contact center, Generative AI is excellent at processing and generating human-like text in response to a wide range of questions and prompts.
Specifically, it excels at natural language processing (NLP), meaning it can understand and interpret human language. This can improve the efficiency and accuracy of customer support and can also improve overall customer experience (CX).
In a world where improving CX is critical for building and maintaining brands, companies are actively seeking solutions that will help them establish next-generation service levels. As we will see, Generative AI, combined with an enterprise Conversational AI platform (ECAIP), has the potential to deliver enhanced customer service in ways never seen before.
In a Nutshell: How Generative AI Works
Generative AI works by analyzing existing data patterns and using deep learning algorithms such as Generative Adversarial Networks (GANs) to generate new outputs. The Generative AI system is trained on large amounts of data and, as it analyzes the data, it learns the patterns and relationships within the data.
Generative AI...covers a broad range of needs. It is designed to create new and original content, such as text or speech...
Once the AI system has learned the patterns and relationships, it can generate new outputs that are similar to existing data but not identical. This allows the AI system to create novel content and outputs that are not limited to existing data and that are unique to the generative AI system.
Generative AI versus Conversational AI: Understanding the Differences
Let’s now look at Generative AI and Conversational AI. Both are two types of AI that have become increasingly popular in recent years. While they share some similarities, they also have significant differences that make them better suited for different applications.
Generative AI is a general purpose technology that covers a broad range of needs. It is designed to create new and original content, such as text or speech, and is therefore non-deterministic: which means it neither can predict nor review exactly what and why it says what it says.
Conversational AI, on the other hand, is a type of AI that focuses on creating natural language interactions between humans and AI systems using an ECAIP.
Generative AI in Contact Centers: Benefits and Challenges
When integrated with an ECAIP, Generative AI can provide the following benefits:
- Improved efficiency. Generative AI can automate repetitive and time-consuming tasks, freeing up agents to focus on more complex and creative tasks. For example, it can generate automated responses to common customer inquiries, thus reducing the need for bot builders to manually create responses to these requests.
- Enhanced CX. Generative AI has a fundamental, built-in knowledge of the world which it can use, combined with the contexts of conversations, to generate personalized content that helps build stronger relationships with customers. It is also capable of some reasoning and can pretend to be empathetic.
- Increased accuracy. Generative AI can help reduce human error, such as typos and incorrect information, which can improve the accuracy of customer interactions. It can also provide next-generation agent assist by “listening in” to a live conversation and suggesting responses based on the context of the call.
Despite the potential benefits of Generative AI, there are also several challenges associated with this technology, which means it cannot be used in isolation in the contact center.
Without an ECAIP, Generative AI doesn’t know your company or your use cases. It can’t do anything for your customers because it is not connected to your back-end systems or to your customer-facing solutions. And it cannot perform the handover of conversations to humans, like your agents.
ChatGPT and Generative AI
ChatGPT has burst on the scene recently and continues to gain attention. Here briefly is what it is, in its growing number of iterations, and the relationship it has with Generative AI.
ChatGPT is a chatbot developed by OpenAI that was launched in November 2022 and is available online for free. It is built on top of OpenAI’s GPT family of Large Language Models (LLMs), which is also known as Generative AI.
OpenAI has most recently released GPT-4 and there are several improvements since its last version, GPT-3, including the ability to be more coherent, more accurate, and less likely to make up facts.
The new features in GPT-4 will help contact centers offer better customer service and be more effective in their ability to respond quickly, accurately, and more human-like to customer inquiries.
The combination of Generative AI with a Conversational AI platform is promising for contact centers worldwide. This powerful AI duo will enhance conversations by tailoring to an individual’s context and preferences and improve agent performance resulting in increased efficiency and cost savings.
The Best Types of Contact Centers for Using Generative AI
When used with an ECAIP, Generative AI will be beneficial to a majority of contact centers. The technology can automate repetitive and time-consuming tasks, thereby freeing up agents to focus on more complex and creative tasks. And it can handle a large volume of customer interactions during peak periods.
Omnichannel contact centers...can benefit from Generative AI...by providing consistent responses across all channels...
Contact centers that are focused on self-service and automation will benefit from using Generative AI as it can provide quick and accurate responses to customer inquiries, ultimately reducing the need for agents to be involved in every interaction. This can improve CX and reduce wait times for customers.
Omnichannel contact centers, which operate across multiple channels such as phone, email, chat, video, and social media, can benefit from Generative AI as part of an overall contact center solution by providing consistent responses across all channels, thereby improving CX.
...a thorough assessment of the needs and objectives of the contact center should be undertaken before implementing this technology.
It’s important to note that Generative AI may not be appropriate for every type of contact center and use case. For instance, in situations where compliance is crucial, such as in the pharmaceutical industry, Generative AI may lack the explainability and fully deterministic behavior of traditional bot experiences.
Nevertheless, when Generative AI is employed to develop bots (as opposed to being used with live customer input), conversation designers may benefit from a faster time-to-ROI while maintaining complete control over the end-user experience.
Therefore, a thorough assessment of the needs and objectives of the contact center should be undertaken before implementing this technology. Additionally, effective training and support should be provided for agents to help them work effectively with Generative AI.
Recommendations When Considering Generative AI
Generative AI is an exciting and rapidly evolving technology that has the potential to transform contact centers by improving efficiency and enhancing CX.
However, effectively implementing Generative AI in a contact center requires careful planning and a well-thought-out strategy, which includes integration with an ECAIP.
Here are some recommendations for contact center managers who are considering using Generative AI.
- Assess your needs. Start by conducting a thorough assessment of your contact center’s needs and objectives. Identify areas where Generative AI can add value and improve efficiency and consider whether it is the right technology for your contact center.
- Develop a clear strategy. Before implementing Generative AI, develop a clear strategy that outlines the goals, objectives, and expected outcomes of the technology. This will help ensure that the implementation is successful and meets the needs of the contact center.
- Provide effective training and support. Agents play a critical role in the success of Generative AI, so it is important to provide them with effective training and support to help them work effectively with the technology. This can include training on the use of the technology, as well as training on the company’s customer service policies and procedures.
- Focus on quality control. Ensuring the quality of the automated responses generated by Generative AI is critical to its success. Regularly review and update the AI models to ensure that the responses are accurate, relevant, and consistent with the brand’s tone of voice.
- Monitor and evaluate performance. Regularly monitor and evaluate the performance of Generative AI in your contact center, including its impact on efficiency, customer satisfaction, and agent workload. This will help identify areas for improvement and ensure that the technology continues to meet the needs of the contact center.
- Be prepared for challenges. Implementing Generative AI in a contact center will come with its own set of challenges, such as building trust with customers and overcoming skepticism. Be prepared for these challenges and have a plan in place to address them.
With the right planning and implementation, Generative AI can be a valuable tool for contact centers to achieve their efficiency goals and improve their CX.