Generative AI: The Future of Customer Service is Now
What is Generative AI? Artificial Intelligence, or AI, has been around for years. Machine learning algorithms, natural language processing, and the like are now ubiquitous in the IT applications we use on a daily basis. However, only with the advent of various Generative AI technologies such as ChatGPT, MidJourney, DALL-E, and Bard has AI claimed the spotlight and headlines across the Globe. Generative AI is a type of Artificial Intelligence that can create new, and arguably “original”, content based on the models it was trained on. It has revolutionized what AI can be used for and how accessible it has now become. Before, AI was a niche field useful to organizations that generated large amounts of data and had the resources to hire data scientists and build powerful servers to analyze them. It is now a tool that can be used and prove useful to practically anyone. From the students asking ChatGPT to help with their homework, to graphics designers who can now create in a matter of seconds what took days if not weeks before, and to office workers who can ask AI to create and summarize worksheets of data into a report they can pass on to management. Generative AI in Customer Service A key segment of your business that can greatly benefit from Generative AI today is customer service. Unlike traditional rule-based chatbots that operate based on pre-defined scripts, generative AI has the ability to understand context, learn from data, and produce human-like responses that adapt to the unique needs and preferences of each customer. Personalized Interactions Generative AI is unique in that it improves its answers to your customer’s queries as the conversation develops. The more information it has about your customer, the more tailored its responses will be. For instance, when a customer contacts a retail company regarding a previous purchase, generative AI can use the customer’s order history and preferences to suggest complementary products, providing a seamless cross-selling experience. 24/7 Global Availability Your business is often limited to interacting with customers in your time zone and in the language you are familiar with. Generative AI effectively eliminates this barrier by being available 24/7 to customers who speak different languages. Generative AI not only detects and translates the queries of your customers for you; it can also reply to the customer in his or her native language. As such, Generative AI has the potential to open up completely new markets for your products and services. Handling Complex Interactions Generative AI can learn from the vast amounts of data your business generates. It is capable of handling customer service scenarios that previous chatbots could not. As the AI interacts with customers, it learns from each interaction and gains a deeper understanding of nuanced queries. This empowers the AI to provide accurate and relevant responses even to intricate questions, contributing to a smoother and more efficient customer service experience. Unlike the previous generation of chatbots, which were completely dependent on the script they were following, a Generative AI chatbot can actually assess the intent, mood, and flow of the conversation and automatically escalate the interaction to a human agent if the need arises. Generative AI Customer Service Use Cases Limitations of Generative AI and how to overcome them Risk of Misinterpretation and Miscommunication Generative AI relies on generating responses based on the the data it has. While it can detect some sentiment and intent from its users, it does not have true understanding of emotions. As such, it could have a tendency to produce incorrect responses or ignore emotional cues that can cause frustration for the customer. To address these issues, it is important not to be over reliant in AI for all interactions. For example, once a negative conversation is detected, this should trigger an alert for a human agent to take over the customer interaction. Continuously monitoring interactions and fine tuning the AI through training and updating can also help address and prevent issues from repeatedly occurring. Inability to Handle Unforeseen Situations When faced with unprecedented or highly unique situations outside of its training data, an AI may struggle to provide accurate and helpful responses. This causes the AI to have “hallucinations” or make it appear that the AI is lying to the customer. The solution to prevent or at least limit hallucinations is through thorough fine-tuning, prompt engineering, and training of the Generative AI. You can also program them to limit responses to only the custom trained data and to self analyze their response before replying. It is critical that the AI interactions are regularly reviewed and any issues remedied through fine tuning. Privacy and Security Concerns Customer service often involves handling sensitive information, such as personal details or account credentials. Generative AI’s ability to generate human-like text raises concerns about data privacy and security. If not properly managed, there is a risk that sensitive information could be mishandled or exploited. Compliance to existing privacy and security regulations must be at the top of the list when deploying a Generative AI system. Proper data encryption and storage should always be practiced and where applicable anonymization and proper filtering of Personal Identifiable Information (PII) should be conducted. Finally, ensure that the AI requests and shares only the minimum personal information needed to address the needs of the customers and make all customers and users aware of the risks involved when utilizing the system. Dependency on Quality and Quantity of Training Data The quality and timeliness of the the training data is what will define the capabilities of your Generative AI platform. Incomplete, outdated, and inaccurate data will reflect in the responses of your AI to your customers. Hence, maintaining and managing your Generative AI platform is an on-going concern. Fine tuning, monitoring and updating should be done on a regular basis. Thorough testing of the system before pushing it live to your customers should be a priority. Generative AI is not General AI While it can generate very informative and useful responses, Generative AI